#my goal is to spend the next two weeks collecting data and then analysis it the following week

[antlerknives]

currently working on the early stages (ie. user research) of a spotify user interface redesign as a personal portfolio project and i am ridiculously excited about it

[timextoxhajima]

HOSTIS, Chapter III: Aemulatio, Rivalry

Previous Chapter (II: Antiquum Fabulum)

Member: Lee Hyunjae (tbz)

Genre (by chapter): drama, comedy

Category: Short Novel/Long Series

“if it’s anybody who knows what you’re thinking... it’s me.”

two weeks of pure torture. 

and even after that, there was no way of telling how long you were going to be stuck in the same building, same wing, same office area, with lucifer; with the other half of two areses. 

of all tracks and professions to choose, he just had to choose neurology. the ones who birthed you were one a cardiologist and the other a psychiatrist. 

so why the hell did i choose neurology? 

had i chosen any other track, i wouldn’t be stuck here, in the same room as him, needing to breathe the same air as him, listening to the same words, and treating him like my partner in kindergarten.

“hmm, let’s see what i have in my schedule today...” doctor choi gets off the leather seat and looks through his file. lucifer was standing near the corner of the office, eyes scanning the plaques and framed certificates on the wall while the pen in your pocket rolls around your fingerpads. 

“i’ll be making rounds today from ten to twelve, and two to four... and since you can get off at six, your last two hours in the evening could be well spent familiarising yourself with the research department,” the glasses on his nose slips a little and he pushes it back up before looking at you. “and doctor kim, of course.”

lucifer gives a kind chuckle, and the sound of it makes your skin crawl with displeasure. “do you have any tips for us to get on doctor kim’s good side?”

us? yeah, right.

“if it’s anybody who needs tips, it’s me,” doctor choi scratches his forehead and picks up his file. “anyway, there’s still about an hour left before i start doing my rounds. till then, you can go back to your office and settle in. second day of work usually calls for more admin cleaning.”

the consistent staring and typing on your keyboard starts you drag you away from the thought of lucifer being in his office right next to yours, and the soft, classical music that was orchestrating itself in the air momentarily takes you back to med school.

back then, the nights you spent burying your nose in textbooks, files and notes were both torturous and fulfilling, and with how efficient the music was in calming your nerves, you remember thinking about all the times you lost your temper at lucifer. 

maybe if you listened to classical music since the start, you wouldn’t have such a fiery hatred for him. 

but then again, classical music didn’t really do much for your patience the entire time you were away. otherwise, you wouldn’t have packed up and moved into your own apartment after you came back from med school in the united kingdom. 

neither of your parents were fond of the idea, but thanks to your father being a psychiatrist, he was able to convince your mother into letting you stay alone. honestly, you moving away was simply to reduce the friction you knew you would have with her. your father was just the one with a higher emotional quotient to read that off you without needing you to say it explicitly. 

the alarm in your phone goes off, telling you that it was five minutes to ten, and a little ‘swoosh’ emits from your computer. 

from: kim ryuk hoon 

to: y/n, lee hyunjae, choi young joon

subject: research department data collection

to the newcomers, 

the research department welcomes you with opened arms. we hope you have been settling in well and the staff here has been kind to you. 

before you embark on your journey to becoming a full-fledged in-practise doctor, the research department would like to invite you to take up a task most will find arduous. i imagine that it’s not for the both of you. 

doctor choi will verify and validate this email first. if this invitation acquires his approval, then i will see the both of you this friday before you clock out.

i’ve already checked doctor choi’s hospital round timings, and he does not have anything scheduled after 5 on friday. there’s absolutely no reason for him to decline/disapprove this invitation.

have a great day, and i look forward to doctor choi’s approval. 

regards,

doctor kim

a smile naturally spreads on your face, but a sharp knock peels it off your lips like masking tape. the door of your office swings open and lucifer sticks his head in with an innocent grin baring his teeth at you. 

“did you zone out from being the little bitch you are or are you waiting for another invitation to be a doctor?”

annoyance rushes through you like race cars, and you grab a pen from the pencil holder by your computer, hurling it so hard that it sent a loud ‘tong’ sound through the glass of your office. lucifer ducks a little and winces at the harsh ring, looking behind him and out into the rest of the office to see if anybody heard.

you slam the laptop screen shut and turn off the office computer, eyes never once leaving his awfully arrogant mischief. slipping a tiny notebook into your coat, you push the chair back under the desk and walk towards the door where he pulls away, giving you just enough space to shove your way past him. 

his ribs run against your shoulder, and the mere contact makes you want to step on him and ruin his unrealistically shiny, polished dress shoes. 

fortunately, he doesn’t say one word to you the entire time the both of you tailed doctor choi on his rounds. he introduced the two of you to some of his not-so-critical patients and says they may be transferred to be taken care by either of you. 

the interactions with some of them were so heartwarming, despite half of the patients looking at lucifer like they just saw an angel. 

but there was still that overwhelming admiration and respect for those who chose to dedicate their lives to saving others. it was just unfortunate that you hated one of those people. 

every second spent with lucifer in your sights felt eternally long, but the week flashed by and it was like life was reminding you that time waits for no man. 

doctor choi had no choice but to give into doctor kim’s invitation for lucifer and you to take up that data analysis assignment. by friday, it had been four days since you felt like you were thrown back to your life prior to med school. 

back then, you spent every conscious second studying with only one goal in mind: to out do lee hyunjae. 

despite the difference in setting and environment where there were no longer grades or teacher appraisals to feed your pride and ego over his, now you were starting to feel the destructive force of motivation pushing you to earn the commends of the senior doctors and colleagues around you. 

after that, your new goal would to get a promotion before lucifer does. but sticking to reality was one of the best traits a doctor could have, so you were careful not to get too ahead of yourself. 

“here are the document sheets,” doctor kim hands you each identical files, but yours was black and his was blue. “and some of the information you need will be emailed you by tonight. so spend the weekend studying the material and you can use whatever time you have next week and even after your welcome party to finish this.”

“it’s not urgent?” you raise a brow, looking at the top sheet in the folder. 

“it’s not, but we do value quality data and findings.”

“wait, are you saying that the documents are exactly the same but we could be submitting different sets of data?” lucifer queries, and confusion starts to seep through your neurons. 

“correct,” doctor kim runs his wrinkly fingers on his chin where a little stubble grew since the last time you saw him. “the data that the both of you submit might be different. in fact, it may look completely different but as equally as valuable.”

oh, this is going to be fun.

“the last section of the documents includes data pointers from the oncology sector. it’s not very long and it’s highly likely you’re not going to find anything from that department--”

“why?”

doctor kim hesitates for a moment upon your question, and lucifer looks at him, waiting for a response as well. 

“oh, well,” doctor kim clears his throat and waves the two of you in. a frown forms on your forehead, but lucifer leaning in urges you to follow. doctor kim’s bony hand cups his mouth from the side and looks around before whispering, “the oncology department head is crazy. she doesn’t like doctors who don’t belong there to even be on that floor.”

“ah,” lucifer sighs exasperatedly. “and which wing is the oncology department in? just so i can know where to avoid it.”

there we go, the selfishness hopped right out at ‘i’.

“if the neuro department’s in the north wing, and we are in the east wing, then...”

“it’s the other way round, doctor,” you quickly point out when he stops for a moment to remember where the oncology department was. “research department’s in the north.”

“oh!” he lifts a finger in the air, as if he didn’t hear you. the way his eyes lit up like a child brings a little smile to your lips, and his finger starts to wriggle when the neurons in his head click. “oncology is in the west, which makes it opposite the building that neuro is in-- yes, thank you for correcting me.”

call it childish, but that little display of gratitude seeps into you like a praise, and you could almost feel lucifer’s disgust when he realises you were busking in it. 

“yes, so avoid the west wing as far as possible. doctor choi will force me into retirement if doctor shin realises his mentees are strutting around in her department looking for answers to a worksheet...”

the desire to outdo lee hyunjae crawls back into your gut like the ghost crawling out from the television in ring. you didn’t even need to look at lucifer standing right next to you to know he was thinking and feeling the exact same thing. 

in this realm, zeus created two areses and decided putting them in the same hospital -- the same building, same room, -- was a good idea. 

“alright, i got it,” lucifer lifts the file as a sign of acknowledgement. 

“very well!” doctor kim beams brightly at the both of you, heels turning to return to his desk. “if there are any questions you have for me, don’t hesitate to drop me and email or come to look for me. of course, don’t let doctor choi know. he might just start filling up my retirement sheets for me.”

a gentle laugh runs through your throat and lucifer looks at doctor kim like that was his father. the both of you bow slightly before turning around, heading for the lift so that you could return to your office. 

ignoring lucifer standing right behind you was so easy, especially when you haven’t seen him for four years. but knowing that the both of you had the exact same goal in mind? 

that was difficult to swallow. 

you ran the thought through your head, the memory of spending nearly six full years fighting with the same person, both mentally and physically, sparking your eagerness to win. the only reason why you didn’t spend ten full years fighting with him was because you were no longer in the same institution. 

“i know what you’re thinking of,” a deep breath gets sucked into your lungs as he turns his head enough for you to see his cheek. “so just know that four years didn’t do much to curb whatever threat you see in me.”

lucifer scoffs and turns back to face the doors of the lift, the glazed over metal allowing you to lock eyes with him through the reflection.

“i know. i already knew the moment he said that the data sets might be different.”

then he looks away and up at the display panel inside the lift with the floor number on it. 

“if it’s anybody who knows what you’re thinking...” he turns around and lightly taps your chest with the file he was holding, the gesture making you want to take it and whack him across the face. 

“it’s me. the other half to our two areses.”

your arm finds his shoulder to push him back away from you, and you wipe your palm on your coat with exaggeration. 

“so rest assured, y/n. you’re not the only one who’s not going down without a fight.”

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Chapter IV: Vetiti Fructus In

[elizabronx]

On how to write a thesis and survive school

As a person who has spent the last few months stuck behind her computer writing her thesis (research, whatever, see my post about it here) or whining about it, I am just discovering my newfound freedom. The deadline of my thesis happened to fall on a day two days before another deadline, which happened to be the second-biggest thing after my research I have to do all year. 

So, needless to say, the weeks leading up to these deadlines were busy as hell. Here are a few things that helped me throughout my process or what I discovered that might be helpful to someone else. Some of these may help you with just schoolwork as well.

Choose your topic wisely. I know some people who chose a random topic and were unhappy with it or let other people decide for themselves and ended up hating a thing they once loved. If you happen to have the freedom to choose your topic for yourself, go for it. I chose an element of a book series I have loved for almost half my life knowing I would never turn against it.

Fandom-themed researches may be a good choice but they give you more chances for procrastination. You may find that in the busiest times you’d like to reread the almost 3000 pages that inspire your work. I wrote my thesis on Christopher Paolini’s Ancient language, which made me miss rereading his books for months but I know they would have taken too much time. If you are likely to actually go and procrastinate like that, given a chance, fandom-themed research may not be the right choice for you.

Know who you’re choosing as your mentor. Often people get to choose or are given an adviser or mentor to guide then through the process. If you are a responsible student, a strict mentor might not be for you. What worked for me was a mentor I didn’t want to disappoint. This guilt-tripped me into working harder and harder. But beware, this only works if you can be guilt-tripped into working hard. If not, a strict mentor might be the only chance you could give yourself to get the work done in time.

Set realistic deadlines... and keep them. Planning ahead is key when writing a long project and in that case setting yourself realistic goals once in a while to get a large portion of work done is crucial. Talking about these deadlines with your mentor and promising to keep them is what keeps you on track but I wouldn’t recommend that very often - only with large parts of work. Otherwise a sudden illness or a test may put you far off schedule and may end up doing more harm than good.

Set unrealistic deadlines... and try to keep them. If you are someone who doesn’t really beat yourself up but still tries to keep every deadline, this is the approach for you. Set yourself a goal you know you’ll never achieve and do all you can to complete half. But keep in mind that this is the approach to use only in the early stages of your work when the real deadlines are not pressing yet.

Start working early. If you know your work has to be done by early March but you have to choose your assignment in May, you have almost a year to do it. I would recommend either doing a lot in the summer when you have free time or letting it all set a bit. The summer is an excellent time to think it all through and figure out what to do. This part of the work takes time but is not something you have to do hands-on all the time. Just think about what you want to do once a week for a while when you still have all the time in the world.

Don’t underestimate the early stages. People often think that writing the work itself is the most difficult part but I can say that’s only a small part of it all. Data collection and analysis take up at least as much if not more time if done properly. Start it early and don’t underestimate the time you could spend on excel.

Know your work schedule. If you have a free day or few to work on your project but you know you have to do a lot, knowing when you work best is key. I for one knew that my most unproductive part of the day falls between 1 pm and 6 pm. So I planned to wake up early, write before noon and in my productivity low-point do more routine work like formatting and excel, to return to writing in the evening. 

A fresh look could be what you need. A few weeks before the final deadline I, known for being meticulous and sometimes more critical than teachers, read a friend’s research. It was not yet complete but I went in detail and spent a few hours correcting it. This resulted in her seeing mistakes she hadn’t noticed before and being able to complete her work a bit more easily. 

Proofreading must come from the outside. At one point you and your mentor no longer see the typos. You are too much in the work yourself and it is important to have someone from the outside (a friend or a family member if they are good at this will do) proofread and correct all typos and other mistakes.

Know who’s grading your paper and what the points stand for. If you are able to see the grading scale before and know what the points are for, go over your work and keep them in mind. This will help you notice what’s missing and improve all there is to improve. If you (like us) gain points by communicating with your mentor and not leaving them in the dark all the time, do that. You don’t want to lose points because you didn’t take ten minutes to write an email at the beginning of the process.

Don’t underestimate lack of sleep, food or breaks. They are the fuel that keeps you alive and you can’t ever underestimate. Proper sleep keeps your mind working and breaks and food give you the little bit you need to keep productivity up. However, don’t take very long breaks as you will get distracted.

Music may help you. I for one took a CD at a time, working for as long as it lasted (about an hour) and then taking a break. Some people work well with only certain types of music. Do what works for you.

I hope this helped you, but do keep in mind that I am just a student myself and this is just what has helped me. If I remember anything else or someone tells me something, I may do a part 2 as well. But in the mean time, you can ask me all you want about my thesis and I will see you next time.

[dawnfelagund]

In the course of talking about FanFiction.net on my journal, a number of people mentioned that they were considering posting there again if only because they perceived they might get more comments there than on AO3. I have started posting again to FanFiction.net in order to access their very detailed click/comment data, and I wasn’t seeing more comments than I was getting on AO3, which led me to ask: Is there a difference between Silmarillion sections on the different sites in terms of the comments the average author can expect to receive?

I also dredged up some new data and revisited the question @simaethae asked me a couple weeks ago of whether and how commenting has changed in the last decade-plus of the Silmarillion fanfic community. Has commenting really dropped?

The short answers to both questions, based on this research: Not really and yes.

For data, analysis, and to discuss the research, click the link above to read the article on my blog The Heretic Loremaster. However, I will also put the full text below the jump here, since it’s not terribly long (for me).

The conversation here and on my tumblr lately has focused on comments and the history of commenting in the Tolkien fandom. (See this conversation with Simaethae on Tumblr for discussion of how commenting has changed in the past twelve years.) I’ve also been thinking a lot about commenting data and how it is best to collect and interpret this data.

In the course of doing the latter, I’ve begun posting again to FanFiction.net, mostly to have access to the very specific statistics they collect about comments. I heard from a few people, when I wrote on my journal about trying this, that they were considering posting again to FanFiction.net because they believed they might get some comments on their work there, whereas they were not receiving many comments on AO3. (I had stopped posting at FanFiction.net when the administration refused to take any action against bullying, especially against teenage authors.)

This made me wonder: Do authors get more comments on FanFiction.net than elsewhere? Is there something of the older fandom culture there? One of my theories about why feedback has decreased in the Silmarillion fanfic community is that, ten years ago, there was a wide perception that people wrote fanfic in order to improve as writers, and we tended to perceive ourselves as all helping each other toward that goal. FanFiction.net still expresses that philosophy, once near-universal in the Tolkien fanfic community, in their Story Guidelines that are available when posting a new story to the site:

3. Respect the reviewers. Not all reviews will strictly praise the work. If someone rightfully criticizes a portion of the writing, take it as a compliment that the reviewer has opted to spend his/her valuable time to help improve your writing.

4. Everyone here is an aspiring writer. Respect your fellow members and lend a helping a hand when they need it. Like many things, the path to becoming a better writer is often a two way street.

The idea that we are all writing because we are aspiring toward writing excellence seems far less prevalent today than it once was, and I wondered if this was behind the drop in commenting in recent years.

So I decided to take a look to see if there is a difference in commenting across the Silmarillion sections of multiple sites. I looked at An Archive of Our Own (AO3), FanFiction.net (FFN), Many Paths to Tread (MPTT), and the Silmarillion Writers’ Guild (SWG). All of these sites make it possible to filter out only the Silmarillion stories.

The methodology I used:

I started with stories posted two weeks ago, beginning on December 10, and worked back from there. There’s a good reason why a story posted in the last 48 hours wouldn’t have many (or any!) comments: People just haven’t had a chance to read and react to it yet! Going back two weeks made my data more fair toward sites like AO3 that have a large number of stories being posted per day.

I looked only at one-chapter stories in the Silmarillion section.

I looked only at stories written in English.

I listed the number of comments and clicks beginning on December 10 and worked back from there, until I had collected data from ten stories on each site. On AO3, I counted only top-level comments since comment replies count toward the comment count reported on the story stats. FFN, unfortunately, does not make click data public, so that data is missing.

Here is the data chart:

Some observations:

On all sites except MPTT–which had dismally low comment rates in its Silmarillion section–you can expect to get about the same number of comments: one, maybe two, per single-chapter story.

You are more likely to get more than two comments on AO3 and FFN.

You are most likely to hear from at least one reader on the SWG: Only 10% of the stories I looked at had no comments. That number was 20% on AO3 and 30% on FFN.

Reading rates, however, were much more variable. Surprisingly, your story is going to get the most readers on MPTT–however, you’ll hardly ever hear from them. I expected higher click counts on AO3, which is by far the busiest Silmarillion section online right now. However, it doesn’t seem like the high number of users necessarily translates into a lot of traffic on individual stories, perhaps because there are enough stories being posted there that readers can afford to be particular. Click counts were lower than I expected on the SWG (although I have suspected they were falling for a while now, I was still startled by how low they actually are), but even with relatively few readers, you’re likely to hear something on your story.

Comment-to-click ratios were the highest on the SWG, where one reader out of thirty-nine comments. On AO3, one reader out of sixty-four comments.

I wish I had click data for FFN, but even without it, it doesn’t seem like a Silmarillion author is going to do much better there than on AO3 or the SWG.

Overall, I think this data also presents a pretty glum picture of commenting in the Silmarillion fanfic community right now. If you post a Silmarillion story today, in two weeks, you might hear from one, maybe two, readers. Obviously, some authors have much higher rates of feedback–but at the same time, there are authors who hear nothing, or almost nothing, on their work.

On this post about commenting, I suggested that many readers might lack the confidence and skills to write comments that they feel are meaningful to authors. The discussion around this idea was really good, and I won’t say much more on it here, but what did arise during that discussion that changed my thinking somewhat is the difference between small, intimate archives and large, generalized archives and quality of relationships most users form there. I think the data does bear this out, keeping in mind that it is a very limited sample. (I should start doing this regularly to see if these trends hold.) The SWG, based on click data alone, is the smallest of the three sites for which click data is available. My own experience as the owner of that site is that it tends to be a more intimate setting, and most people who participate there tend to be acquainted with each other (and, in some cases, have deep, years-long friendships). And you’re more likely to hear from a reader there than on AO3 and especially MPTT, which seem to have more people willing to read a Silmarillion story but less likely to speak to an author about it.

In conclusion, it seems to me that, if we aspire to raise rates of commenting in the Silmarillion community, it might require a couple of approaches. First is to increase the resources and systems available to help readers develop the skills to write comments. But I think that increasing the intimacy in the community will also help. Talking with some friends–most of them SWG users–in response to my complaint that Tumblr is the primary place where discussions of The Silmarillion occur (and Tumblr is universally regarded as terrible for discussions), many were interested in having the ability to discuss Tolkien in a location off of Tumblr. As I ponder the direction for the SWG site redesign, this is definitely at the forefront of my mind.

And one final footnote about commenting in earlier eras of fandom history: I am perusing old Metafandom posts for a paper I’m researching, and I encountered numerous posts bemoaning the lack of comments and making the same pleas that I hear today about the need for readers to do their part in supporting the work of authors they enjoy. Metafandom was a multifandom community that collected links to discussions in fandom. It was not heavily used by the Tolkienfic community. But it reminds me that dissatisfaction with the amount of comments one receives is certainly not a new complaint.

However, I do think the situation has worsened. I looked back at the Silmarillion section on FFN for 29 November 2004. Unfortunately, the Wayback Machine only saved the first page, so I could not follow  the methodology of going two weeks back and looking at the data for the ten single-chapter stories posted on or before that date. Instead, I looked at the ten oldest single-chapter stories on that page, which were all posted two weeks or before November 29. The median number of reviews was two.

By the next snapshot I was able to find for 20 February 2009, activity in the Silmarillion section has slowed to where I could follow the methodology using just the first page of stories; the median number of comments is still two. Same for 3 March 2009: The median is two for the ten oldest stories on the first page.

By 9 October 2013, however–in the heart of the Hobbit film trilogy and with activity clearly picked up in the Silmarillion section of FFN–the median number of comments is down to one per story, following the methodology where all stories had been posted for at least two weeks. Same by 20 September 2015. I’m not sure what happened around that time, but it seems the narrowest I’ve been able to pinpoint a drop in commenting so far: right around the release of the Hobbit trilogy. The easiest explanation is that an increase in activity in a fanfic community does not translate into increased commenting, which could also support my explanation that more intimate communities bring about more commenting. However, I’m open to other theories in the comments.

[because-its-important]

what’s the most annoying question to ask a nun* in 1967?

tl;dr - In 1967, a very long survey was administered to nearly 140,000 American women in Catholic ministry. I wrote this script, which makes the survey data work-ready and satisfies a very silly initial inquiry: Which survey question did the sisters find most annoying?

* The study participants are never referred to as nuns, so I kind of suspect that not all sisters are nuns, but I couldn't find a definitive answer about this during a brief search. 'Nun' seemed like an efficient shorthand for purposes of an already long title, but if this is wrong please holler at me!

During my first week at Recurse I made a quick game using a new language and a new toolset. Making a game on my own had been a long-running item on my list of arbitrary-but-personally-meaningful goals, so being able to cross it off felt pretty good! 

Another such goal I’ve had for a while goes something like this: “Develop the skills to be able to find a compelling data set, ask some questions, and share the results.” As such, I spent last week familiarizing myself with Python 🐍, selecting a fun dataset, prepping it for analysis, and indulging my curiosity.

the process

On recommendation from Robert Schuessler, another Recurser in my batch, I read through the first ten chapters in Python Crash Course and did the data analysis project. This section takes you through comparing time series data using weather reports for two different locations, then through plotting country populations on a world map.

During data analysis study group, Robert suggested that we find a few datasets and write scripts to get them ready to work with as a sample starter-pack for the group. Jeremy Singer-Vines’ collection of esoteric datasets, Data Is Plural, came to mind immediately. I was super excited to finally have an excuse to pour through it and eagerly set about picking a real mixed bag of 6 different data sets.

One of those datasets was The Sister Survey, a huge, one-of-its-kind collection of data on the opinions of American Catholic sisters about religious life. When I read the first question, I was hooked. 

“It seems to me that all our concepts of God and His activity are to some degree historically and culturally conditioned, and therefore we must always be open to new ways of approaching Him.” 

I decided I wanted to start with this survey and spend enough time with it to answer at least one easy question. A quick skim of the Questions and Responses file showed that of the multiple choice answer options, a recurring one was: “The statement is so annoying to me that I cannot answer.” 

I thought this was a pretty funny option, especially given that participants were already tolerant enough to take such an enormous survey! How many questions can one answer before any question is too annoying to answer? 🤔 I decided it’d be fairly simple to find the most annoying question, so I started there. 

I discovered pretty quickly that while the survey responses are in a large yet blessedly simple csv, the file with the question and answers key is just a big ole plain text. My solution was to regex through every line in the txt file and build out a survey_key dict that holds the question text and another dict of the set of possible answers for each question. This works pretty well, though I’ve spotted at least one instance where the txt file is inconsistently formatted and therefore breaks answer retrieval.

Next, I ran over each question in the survey, counted how many responses include the phrase “so annoying” and selected the question with the highest count of matching responses.

the most annoying question

Turns out it’s this one! The survey asks participants to indicate whether they agree or disagree with the following statement:

“Christian virginity goes all the way along a road on which marriage stops half way.”

3702 sisters (3%) responded that they found the statement too annoying to answer. The most popular answer was No at 56% of respondents. 

I’m not really sure how to interpret this question! So far I have two running theories about the responses:

The survey participants were also confused and boy, being confused is annoying!

The sisters generally weren’t down for claiming superiority over other women on the basis of their marital-sexual status.

Both of these interpretations align suspiciously well with my own opinions on the matter, though, so, ymmv.

9x speed improvement in one lil refactor

The first time I ran a working version of the full script it took around 27 minutes. 

I didn’t (still don’t) have the experience to know if this is fast or slow for the size of the dataset, but I did figure that it was worth making at least one attempt to speed up. Half an hour is a long time to wait for a punchline!

As you can see in this commit, I originally had a function called unify that rewrote the answers in the survey from the floats which they'd initially been stored as, to plain text returned from the survey_key. I figured that it made sense to build a dataframe with the complete info, then perform my queries against that dataframe alone. 

However, the script was spending over 80% of its time in this function, which I knew from aggressively outputting the script’s progress and timing it. I also knew that I didn’t strictly need to be doing any answer rewriting at all. So, I spent a little while refactoring find_the_most_annoying_question to use a new function, get_answer_text, which returns the descriptive answer text when passed the answer key and its question. This shaved 9 lines (roughly 12%) off my entire script.

Upon running the script post-refactor, I knew right away that this approach was much, much faster - but I still wasn’t prepared when it finished after only 3 minutes! And since I knew between one and two of those minutes were spent downloading the initial csv alone, that meant I’d effectively neutralized the most egregious time hog in the script. 👍

I still don’t know exactly why this is so much more efficient. The best explanation I have right now is “welp, writing data must be much more expensive than comparing it!” Perhaps this Nand2Tetris course I’ll be starting this week will help me better articulate these sorts of things.

flourishes 💚💛💜

Working on a script that takes forever to run foments at least two desires:

to know what the script is doing Right Now

to spruce the place up a bit

I added an otherwise unnecessary index while running over all the questions in the survey so that I could use it to cycle through a small set of characters. Last week I wrote in my mini-RC blog, "Find out wtf modulo is good for." Well, well, well.

Here’s what my script looks like when it’s iterating over each question in the survey:

I justified my vanity with the (true!) fact that it is easier to work in a friendly-feeling environment.

Plus, this was good excuse to play with constructing emojis dynamically. I thought I’d find a rainbow of hearts with sequential unicode ids, but it turns out that ❤️ 💙 and 🖤 all have very different values. ¯\_(ツ)_/¯

the data set

One of the central joys of working with this dataset has been having cause to learn some history that I’d otherwise never be exposed to. Here’s a rundown of some interesting things I learned:

This dataset was only made accessible in October this year. The effort to digitize and publicly release The Sister Survey was spearheaded by Helen Hockx-Yu, Notre Dame’s Program Manager for Digital Product Access and Dissemination, and Charles Lamb, a senior archivist at Notre Dame. After attending one of her forums on digital preservation, Lamb approached Hockx-Yu with a dataset he thought “would generate enormous scholarly interest but was not publicly accessible.”

Previously, the data had been stored on “21 magnetic tapes dating from 1966 to 1990” (Ibid) and an enormous amount of work went into making it usable. This included both transferring the raw data from the tapes, but also deciphering it once it’d been translated into a digital form.

The timing of the original survey in 1967 was not arbitrary: it was a response to the Second Vatican Council (Vatican II). Vatican II was a Big Deal! Half a century later, it remains the most recent Catholic council of its magnitude. For example, before Vatican II, mass was delivered in Latin by a priest who faced away from his congregation and Catholics were forbidden from attending Protestant services or reading from a Protestant Bible. Vatican II decreed that mass should be more participatory and conducted in the vernacular, that women should be allowed into roles as “readers, lectors, and Eucharistic ministers,” and that the Jewish people should be considered as “brothers and sisters under the same God” (Ibid).

The survey’s author, Marie Augusta Neal, SND, dedicated her life of scholarship towards studying the “sources of values and attitudes towards change” (Ibid)  among religious figures. A primary criticism of the survey was that Neal’s questions were leading, and in particular, leading respondents towards greater political activation. ✊

As someone with next to zero conception of religious history, working with this dataset was a way to expand my knowledge in a few directons all at once. Pretty pumped to keep developing my working-with-data skills.

[educaffetechieblogs]

How To Learn Data Science If You’re Broke

Over the last year, I taught myself data science. I learned from hundreds of online resources and studied 6–8 hours every day. 

In the following article, I give guidelines and advice so you can make your own data science curriculum. I hope to give others the tools to begin their own educational journey. So they can begin to work towards a more passionate career in data science.

A Quick Note

When I say “data science”, I am referring to the collection of tools that turn data into real-world actions. These include machine learning, database technologies, statistics, programming, and domain-specific technologies.

A few resources to start out your journey.

The internet is a chaotic mess. Learning from it can often feel like drinking from the fun end of a fire-hose.

There are simpler alternatives that offer to sort the mess for you.

Sites like Dataquest, DataCamp, and Udacity all offer to teach you data science skills. Each creating an education program that shepherds you from topic to topic. Each requires little course-planning on your part.

The problem? They cost too much, they don’t teach you how to apply concepts in a job setting, and they prevent you from exploring your own interests and passions.

There are free alternatives like edX and coursera which offer one-off courses diving into specific topics. If you learn well from videos or a classroom setting, these are excellent ways to learn data science.

Check out this website for a listing of available data science courses. There are also a few free course curricula you can use. Check out David Venturi’s post, or the Open Source DS Masters (a more traditional education plan).

If you learn well from reading, look at the Data Science From Scratch book. This textbook is a full learning plan that can be supplemented with online resources. You can find the full book online or get a physical copy from Amazon ($27).

These are just a few of the free resources that provide a detailed learning path for data science. There are many more.

To better understand the skills you need to acquire on your educational journey, in the next section I detail a broader curriculum guideline. This is intended to be high-level, and not just a list of courses to take or books to read.

A Curriculum Guideline

Python Programming

Programming is a fundamental skill of data scientists. Get comfortable with the syntax of Python. Understand how to run a python program in many different ways. (Jupyter notebook vs. command line vs IDE)

I took about a month to review the Python docs, the Hitchhiker’s Guide to Python, and coding challenges on CodeSignal.

Hint: Keep an ear out for common problem-solving techniques used by programmers. (pronounced “algorithms”)

Statistics & Linear Algebra

A prerequisite for machine learning and data analysis. If you already have a solid understanding spend a week or two brushing up on key concepts.

Focus especially hard on descriptive statistics. Being able to understand a data set is a skill worth its weight in gold.

Numpy, Pandas, & Matplotlib

Learn how to load, manipulate, and visualize data. Mastery of these libraries will be crucial to your personal projects.

Quick hint: Don’t feel like you have to memorize every method or function name, that comes with practice. If you forget, Google it.

Check out the Pandas Docs, Numpy Docs, and Matplotlib Tutorials. There are better resources out there, but these are what I used.

Remember, the only way you will learn these libraries is by using them!

Machine Learning

Learn the theory and application of machine learning algorithms. Then apply the concepts you learn to real-world data that you care about.

Most beginners start by working with toy data-sets from the UCI ML Repository. Play around with the data and go through guided ML tutorials.

The Scikit-learn documentation has excellent tutorials on the application of common algorithms. I also found this podcast to be a great (and free) educational resource behind the theory of ML. You can listen to it on your commute or while working out.

Production Systems

Getting a job means being able to take real-world data and turn it into action.

To do this you will need to learn how to use a business’ computational resources to get, transform, and process data.

This is the most under-taught part of the data science curriculum. Mainly because the specific tools you use depend on the industry you are going in to.

However, database manipulation is a required skill set. You can learn how to manipulate databases with code on ModeAnalytics or Codecademy. You can also implement your own database (cheaply) on DigitalOcean.

Another (often) required skill is version control. You can acquire this skill easily by creating a GitHub account and using the command line to commit your code daily.

When considering what other technologies to learn, it is important to think about your interests and passions. For example, if you are interested in web development, then look into the tools used by companies in that industry.

Advice for executing your curriculum.

1. Concepts will come at you faster than you can learn them.

There are literally thousands of web pages and forums explaining the use of common data science tools. Because of this, it is very easy to get side-tracked while learning online.

When you start researching a topic you need to hold your goal in mind. If you don’t, you risk getting caught up in whatever catchy link draws your eye.

The solution, get a good storage system to save interesting web-resources. This way you can save material for later, and focus on the topic that is relevant to you at the moment.

If you do this right, you can make an ordered learning path that shows you what you should be focused on. You will also learn faster and avoid being distracted.

Warning, your reading list will quickly grow into the hundreds as you explore new topics that interest you. Don’t worry, this leads us to my second piece of advice.

2. Don’t stress. Its a marathon, not a sprint.

Having a self-driven education can often feel like trying to read a never-ending library of knowledge.

If you’re going to be successful in data science you need to think of your education as a lifelong process.

Just remember, the process of learning is its own reward.

Throughout your educational journey, you will explore your interests and discover more about what drives you. The more you learn about yourself, the more enjoyment you will get out of learning.

3. Learn -> Apply -> Repeat

Don’t settle for just learning a concept and then moving to the next thing. The process of learning doesn’t stop until you can apply a concept to the real world.

Not every concept needs to have a dedicated project in your portfolio. But it is important to stay grounded and remember that you are learning so you can make an impact in the world.

4. Build a portfolio, it shows others they can trust you.

When it comes down to it, skepticism is one of the biggest adversities you will face when learning data science.

This may come from others, or it may come from yourself.

Your portfolio is your way of showing the world that you are capable and confident in your own skills.

Because of this, building a portfolio is the single most important thing you can do while studying data science. A good portfolio can land you a job and make you a more confident data scientist.

Fill your portfolio with projects that you are proud of.

Did you build your own web app from scratch? Did you make your own IMDB database? Have you written an interesting data analysis of healthcare data?

Put it in your portfolio.

Just make sure write-ups are readable, the code is well documented, and the portfolio itself looks good.

This is my portfolio. A simpler method to publish your portfolio is to create a GitHub repository that includes a great ReadMe (summary page) as well as relevant project files.

Here is an aesthetically pleasing, yet simple, GitHub portfolio. For a more advanced portfolio, look into GitHub-IO to host your own free website. (example)

5. Data Science + _______ = A Passionate CareerFill in the blank.

Data science is a set of tools intended to make a change in the world. Some data scientists build computer vision systems to diagnose medical images, others traverse billions of data entries to find patterns in website user preferences.

The applications of data science are endless, that’s why it is important to find what applications excite you.

If you find topics that you are passionate about, you will be more willing to put in the work to make a great project. This leads to my favorite piece of advice in this article.

When you are learning, keep your eyes open for projects or ideas that excite you.

Once you have spent time learning, try to connect the dots. Find similarities between projects that fascinate you. Then spend some time researching industries that work on those types of projects.

Once you find an industry that you are passionate about, make it your goal to acquire the skills and technical expertise needed in that business.

If you can do this, you will be primed to turn your hard work and dedication for learning into a passionate and successful career.

[hirenpatelbct-blog]

Reflective Journal

Outline of the assignment

In this assignment, you are revisiting your previous blogs and creating a reflective journal blog. Journal should be a reflective document that provides personal and thoughtful analysis of your individual participation/progress and reflection.  You are required to submit a full reflective journal, aggregated collection of entries so that your “final” journal covers the entire semester analysis of your thinking process and articulating what you learned as a creative thinker.  HOWEVER, it is very important that you be honest in your journal entries.

________________________________________________________________

 I used to always think that I was not a creative person and that Ideas that I usually come up with on a daily basis weren’t good enough to become noticeable by others.  When coming into the BCT environment I first noticed that there was no wrong answer if you put your mind to the test, dedicate your time to your craft and passion you can achieve anything. This semester in my first year of BCT I have been studying three core papers which are called Introduction to Creative Technologies, Creative Technologies Studio and Programming for Creativity. In these courses I have been learning how to think outside the box of and become a Creative technologist. I have also been learning how to showcase my ideas on Projects whether that’s by myself or in a group. In the Creative technologies studio, so far I have completed a total of three projects which I am reasonably happy with the final results. The projects that I have done so far this semester have been Cards for Play, Sound and Spaceship Earth 2050. These projects have been very challenging but fun I feel I have gained a lot of important skills and creative ideas which can be useful in the later projects in the next coming years of my degree and hopefully when I go into the workforce.

Introduction to Creative technologies. This where I learned the basics of the Creative technologies. I learned about how to understand creative ideas and way to write blog entries. Blogging personally, I was never really fond of especially using Tumblr. I used to always think that nerds only do blogs and that it wasn’t really wasn’t necessary at all. The assessments in ICT such as videos and blogs has really boosted my self-confidence up. Before being in front of a camera was a mission for me, I would feel very scared but now It’s just a piece of cake. Plus, sharing Videos on YouTube of myself has made me feel more confident in communicating with my peers as trying to showcase my mind towards Creative Technologies and my personality I was no longer the shy kid However It took a lot of time, dedication and effort to collect my ideas and feelings together towards the course to video myself. It was also quite daunting and scary because of the realization that our Videos and Blogs are going to be marked by the lectures. Everyday thinking hoping that they don’t hate my video or my blog, did I explain myself well and Is my Idea up to the standards required. However, as the semester went I began to realize that as Creative Technologists our goal is to become creative and original we should not care of what someone else thinks of our video, blog or any material we have made and I mean yes they are teachers their marking it however we should be proud of the work we produced and if they don’t like it look for ways to improve it nothing is always. Also I told myself that if the teachers did not like my work I decided to never give up and keep improving to make my work better. This went great for me. 

In ICT I have noticed that the thinking process are the most variable methods for being creative original and solving the problems. The thinking process includes empathising, define, ideate, prototype and test. The empathising represent engaging and encouraging while working in a group to share the ideas and understanding by communicating and discussing. The define is where I have to gather all information and ideas together to create the prototype or concept.  In the ideate, I used in my induvial and group projects were brainstorming to stimulate the concept by adding positive and negative effects, this can support my concept by finding any solutions for problems that might occur in the future. The prototype, it is experimental process to where you have to self-check the concept or the ideas by producing the prototype. The testing, testing is the process to test the prototype by sharing with our lectures such as Clinton or some others. Therefore, it leads to feedback which can be used to change the concept or starting the whole process over. These thinking process supported me to solve the several problems that have occurred during the studio projects.

My second core paper is “Programming for Creativity. I am quite new to programming and it has to been a tough semester of it so far. I feel that it just not my area of learning. I have learnt so far Pure Data and Processing so far both I feel have been difficult for me to learn. I love computers but programming I just find it to find hard. In high school we always had the option to do what we wanted weather that’s programming or data basing so I always went with data basing and now it’s kind of flipped on me. The test and assignment for Pure data I felt went well however It didn’t as I missed out on passing. However, with processing my goal is to ace the assignment and test and pass the course so I don’t have to take it again next year. In programing I have learned that everything requires practice. Just reading notes is not going to help you have to physically do programming to get better. That’s happened with me so far with Processing I have done a couple of exercises and I’m slowly getting better.

Studio is my third core paper. I really did not know what studio was going to be about. I was quite anxious to know what’s the semester going to be like. Hearing words like collaborating and exploring made me realize that this course will make me and others come out of comfort zone and will challenge myself to make brilliant new original ideas. My first project that I did this Semester was the Cards for Play. I worked in a group with three other people and I was required to produce a Card Game that was is creative and original. My original thinking was that the task would not be too hard whatsoever as we are only producing a game however this completely back flipped. As a group we were struggling to come up with an Idea as it took us a week to think of. I remember we were excited and motivated toward the production feeling we had nailed the project. But when the prototype cards were shown to our lecturer Ben it ended up being very disappointing.  The lecturer said our Card Game Concept was boring and ideas are too basic and did not have the wow factor I still remember his words “It’s boring; you can’t destroy anyone”. My group members including myself lost motivation, even though this was the great experience to understand how important the feedbacks can be. With the feedback I feel that it really benefited us and that if we didn’t get it we wouldn’t have made a card game enjoyable for others. We then decided to change the concept of the cards for play from the script and started with a brand-new idea with mathematical number cards which end up well. This ended up being much better than the drinking game as It was more interesting. I learned in this project that you cannot skip the thinking process if you don’t spend time developing your idea it will not turn out good. In the future I have to be careful and use my time wisely when making something.

My second project was Sound. There were three tasks of Sound which was Creating instrument, Soundscape and Performance. The first two tasks, producing instrument and soundscape were individual work. I found these two very fun, with Soundscape it was cool getting different sounds and mixing them into a soundtrack. I took sounds from my favourite games and mixed them and did sound very funny to me personally. The soundscape I felt lived up to my expectation I felt that I made something that was original was unique and that was well composed.   With making an instrument it was a struggle thinking of something but when Clinton gave me the advice of “Try to get away from making an already made instrument” I had an Idea. I decided to make a Whistle piano. The production of the instrument was enjoyable as I bought whistles from the $2 shop and my materials from the workshop it was cool spending time making something that you feel could be a great showcase of yourself as a Creative Technologist. The only negative with my instrument was that when I glued the whistles onto the wood it was staying and continually falling of which led me to be very careful with it when playing and walking around with it. The performance task was another group project so I decided to work with my previous group from Cards for Play. We had to share our instruments and soundscapes but all our concept was different from other. This made the concept mixed up and gave a problem to solve. Therefore, we had an idea to create a soundscape by using all the members sound samples and play the instrument toward the sound of beats which we felt could be very cool. It was a difficult and complicate task but there was only one way to complete the project in our minds. I was assigned to make sure that our instruments were up to sound scratch meaning that I had to figure how loud each instrument has to be by for the performance to be also I was in charge of finding good background music as well. Overall it felt daunting as a group to go up and perform but in the end we had to come over fear and we did. With sound I learned that even if we aren’t good with it we should at least give it a shot and test our creative mind. I kept thinking I am not good with sound and I am going to fail it no! that’s not right as a Creative Technologist I have to think positive and challenge myself as well as believing myself that I can achieve anything possible.

The last project I did for Studio Was Spaceship Earth 2050. This was the project I felt was I did not enjoy the most. Even though I kept reading the brief I still did not understand what it was asking me to do as well as what’s the point we are trying to get across. The task was to create a movie film based on e-waste and 2050. I was having the problem of what I should do, do I talk about the future technologies in 2050 or e-waste in 2050. Even though it was a group work all of my group was struggling to understand the project. I had then decided with my group to work on how e-waste can affect the environment in 2050. The script and storyboard was written by teammate Sushmita with struggle we would continually disagree on when a scene would come in or which information shows up however this helped us in to making a video sharper, clever and better. We wanted our video to stand out from the rest so we decided to make it animation. This required heaps of time however it was worth it as it was so fun to play around with different animations. Personally I was confident with the script I thought we did a good job with it but still need a bit of fixing up. In the end my group and I had decided with a script which explains the e-waste and how it can end up in 2050’s environment. This was the project which I felt was more confusing and challenging however thanks to the lecturer’s continuous feedback we became more confident and ended up making a good unique original video. From the E-Waste Project I learned that we should not be scared of asking the teacher for help. Any problems we are having we have to address with them it will help and benefit us in the long run plus it help us achieve great grades.

Overall in the 10 weeks of this course so I far I have made the conclusion that creative technologies are about being yourself it’s about showcasing your true self and your creative mind. In creative technologies it’s not about the end outcome or being perfect it’s about the time that you put into your work, collaborating with other people and stepping to the limit to see how creative you can be. One thing I have noticed is that in Creative Technologies the words perfect or done is like a cuss word it does not exist because each day your trying to improve your idea and as a creative technologist we should not feel satisfied with our ideas we always want to keep thinking of ways to improve them. Sometimes I lost motivation however because of collaboration I have builded relationships with people I like to call friends and family they support me whenever on my ideas and give me feedback in a respectable manner. I feel being challenged and getting out of our comfort zone is the main component of this course it helps me and others think outside the box, becoming more original and creative as well it could be a big asset in the upcoming years of my degree. Creative technologies have help me learn about reflecting my work and blog posting. Blog posting has just become a common thing to do now every day for me.

[topicprinter]

I and my marketing team are always on the lookout for new and better ways of paid advertising to reap maximum results from our marketing budget. Lately, we were evaluating Quora as an option. The great thing about Quora is that most of the traffic to the website is from search engines and the user already has the desired intent. So, say you want to hire a content writer to come up with an ad copy. What do you do? You Google. You search for, “Where can I find the best ad copywriter,” and Quora ranks atop.Screenshot of Google search result: ImgurOnce the user clicks on the search result, they are taken to Quora's website where they see our ad. Quora ad screenshot: ImgurOur ad copy is aimed at reiterating the needs of the user, informing them of the benefits they will reap from availing our service and the next step they need to take. After the user clicks on the ad, they are taken to the landing page where we elaborate about our service, why they should choose us, and they are encouraged to fill out our consultation form with their contact details and requirements.As compared to Facebook ads, we got a higher CTR (Click Through Rate) on Quora and Quora ads were also quite cheaper than Google's search ads, although the CTR was lesser in comparison. We found Quora Ads to be a nice middle ground between Facebook and Google. They simplify the first stage of the marketing funnel by bringing in only those users who have the desired internet and are also cheaper at the same time.We used ads - such as the one you saw above - and got 12x returns. We created several campaigns with variations in the campaign objective (Quora offers four choices: conversions, app installs, traffic, awareness), targeting (there are four options here: contextual targeting, audience targeting, behavioral targeting, and broad targeting), target location and device types (mobile or desktop). Each campaign was given a daily cap of $30. We let the campaigns run for a week and monitored them closely. We found that some of the campaigns did not even touch $10/day while others reached their limits within a few hours). The campaigns that were getting the desired response were promoted further. What's our secret sauce? Umm, okay. Here are some things which helped in making our ad campaigns successful:1. Quora Pixel installationQuora's Pixel is similar to Facebook Pixel and Google's Tag Manager. It is a piece of JavaScript code that allows you to track visitor activity. Quora's Pixel helped us in tracking conversions and creating a remarketing campaign. You can install the Pixel directly on the website or integrate it with Google's Tag Manager. We recommend the latter option since it saves you the hassle of inserting multiple code pieces into your website. Quora Pixel is primarily intended for tracking conversion campaigns but it will be useful to set up Pixel from the get-go so that you can use it later to create remarketing campaigns. Even if you don't run conversion campaigns, the Pixel will continue to collect data for remarketing.2. Creating separate ad sets for mobile and desktopOne of the issues with Quora's Ad Manager is it doesn't provide separate statistics for mobile and desktop. If you want to run an ad on both the platforms, we would recommend to set up individual ad sets for each. The separate ad sets also helped us in setting different bidding amounts for both small and large screen devices. For the desktop campaigns, our CPC bid was $3.4, while for mobile campaigns, it was $0.4. With those bids, we were able to win about 40% of the auctions. 3. Designing separate ad copies for different geographiesWe created different ads for different countries and varied our ad content across the ads. For example, the ad content for developing countries emphasized more on affordability, while the ad content for developed countries emphasized more on the quality and quickness of our service. This helped in relating better with our audience.4. Focusing more on Question targeted ads:The question targeted ads of Quora are extremely precise and produce the best results (the ad you saw, in the beginning, was targetted at questions). But the volume of traffic from question-based ads is relatively low and difficult to scale. The question targeted ads require a lot of research effort but once they are set, you can leave them running for a long time as they are slow to produce results but are extremely effective. If you don’t have time to manually research for each question, you can enter your target keyword and bulk import all the related questions. Quora caps the number of questions to 50 for every ad set, so if you want to target more questions, create a new ad set within the same campaign.5. Experiment, experiment, experiment:The key to success on any ad platform is experimentation. The more you experiment, the more likely you are to hit the combination that works for you. As we mentioned before, some of our ads weren't completing their daily budget and meeting the expected goals, so we analyzed those ads, tried to figure out the fault points and made changes to make the ad successful. The changes can be as small as the device type, but it is important to regularly monitor and update your ad. 6. Regular analysis via Google AnalyticsQuora's Ad Manager is rather limited in the statistics it provides, so you shouldn't solely rely on it. We regularly analyzed the performance of our ad campaigns with the help of Quora Ads Manager + Google Analytics. Analytics helped us in gaining deeper insights and in identifying campaigns which were performing poorly due to bad targeting. Google Analytics is a learning curve in itself, our marketing team continues to discover new uses for it but it is an extremely powerful tool for analyzing user behavior, tracking sources and meeting goals.7. Designing ad in a question-answer styleMany believe that the term 'Quora' is the fusion of Qu(estion) + or + A(nswer). Although that's now true, it aptly summarizes the format of the platform. It turns out that ads that are designed in a question-answer style produced a much better CTR and consequently a lower CPC. if you think about it, it seems natural. After all, when a user is scrolling through their Quora feed, they have a glance at the question and read the answer only if the question appeals to them. Ads that don't follow have a question as the headline tends to be ignored by the user. The question-answer style ads resembled the very format which Quora is built on and that made it appear less intrusive to our target audience.8. Choosing red color scheme in our image-based adsQuora offers two types of ads: text ads and image ads. Text ads are simpler since you only need to write the textual ad copy. Image ads, on the other hand, are diverse and have more room for experimentation. You can play with the image colors, font-size and much more. We found that using Quora's red color (the red in their logo) as the background produced much more engagement. This was true for both desktop and mobile devices, but the increase in engagement on mobile devices was far more than desktop devices. We believe the red menu bar housing the Quora logo and the tinted red status bar on mobile devices made the ads look more natural, which is why they got higher engagements. (PS: another bonus - Quora's red is #AA2200).9. Scheduling our campaigns:Depending on the geography you are targeting, you may restrict the time for which the ads to run. For example, if your viewers are likely to be daytime visitors, it is better to shut down the ad for nighttime. Also, preparing an ad campaign in advance (and scheduling it) for special occasions helped us in getting better results.ConclusionQuora Ads is a very interesting and relatively new advertising platform with lots of potential for both B2B and B2C advertising. It has an easier learning curve in comparison to other advertisement platforms and you should be well versed with Quora ads in less than a month. And surprisingly, the traffic we received from Quora Ads was of very high quality -the users filled our lead forms with their detailed requirements, and some of them ended up having a chat with our customer care for over 2 hours. Now that's some insight, isn't it!?Bonus StatisticsQuora Ad Manager screenshot: ImgurAs promised, here is a quick summary of our ad campaign:Total Impressions: 217,374Total Clicks: 608Total Conversions: 348Spend: $935Revenue Generated: $12,100​I hope you liked the insights from my recent marketing campaign. You may view the complete article with images here.Thanks for reading and hopefully all of you will keep crushing it in this new year!

[samanthasweeney-blog]

where to from here?

They don’t teach you that the period immediately after you graduate university and leave, for the first time in your life, the education system, contains a lot of manic, circular thinking: what do I do now? That’s probably the point, though. They can teach you the intricacies of the Australian political system, what counts as negligence and what doesn’t, and how to analyse quantitative data, but they absolutely cannot teach you what to do with yourself after your degree ends. Nobody can. So, I am writing this blog partially out of the need to put some part of me into the universe and cry I am here! I haven’t disappeared! And also, to give myself a project, some kind of mental nourishment, while I figure out what to do now. As humans tend to do, I looked at graduating through an idealistic lens, impervious to the truistic notion of the grass is greener on the other side. Fed up with a tiresome routine of uni, work, repeat, I was eager to slow down. There is irony in the nostalgia I now feel thinking about my final semester, the sentimental longing I have for all of the plates I was juggling carefully, if a little frenziedly, in my mind. The proverbial rose-coloured glasses fell off after about a month, and the grass is not, in fact, any greener. My discomfort is rooted in having too much time, rather than too little. I learned recently about the ‘adaptation principle,’ which describes the mind’s ability to adapt to new stimuli over time, creating a new psychological baseline. As Jonathan Haidt writes: “nerve cells respond vigorously to new stimuli, but gradually they ‘habituate,’ firing less to stimuli that they have become used to.” What is initially novel and exciting can quickly become the revised norm, and our enchantment fades. While this explains why things are not as exciting as I’d (misguidedly) predicted, it does little to console a racing mind. Much of my discomfort stems from a lack of direction, like finding an open field at the end of a narrow path. I am an achievement-oriented person, and also a human being who is fundamentally programmed to seek purpose (hello, Jonathan Haidt) and to suddenly find myself void of a significant and meaningful pursuit does not a smooth transition make. What’s more, I’ve realised that this change of dynamic necessitates redefining how I measure my own success and achievement. How do measure your progress or your success without a framework, such as what academia provides? Is eating a good breakfast a success? Though a semi-rhetorical question, there is room to argue yes, eating a good breakfast is success. I discussed this with a close friend over coffee last week. Do we absolutely need a tangible and predominant pursuit or project in order to attribute purpose and meaning to our lives? Or do we need to reframe the way we assign meaning to our lives? My answer: a little bit of column A, a little bit of column B. With this in mind, I am trying to engage with the things that bring me joy, like writing and cooking, spending time with my friends, running. Some of these hobbies, like writing, nurture the part of me seeking a purposeful existence; the need to create. Others, done purely for the sake of enjoyment, help me reframe my perception of productivity and achievement, outside of the prescribed career-pursuit model. It’s a tough process, and I’m not immune to feeling like I’m stagnating or falling behind, like I should be working harder to pursue my career goals. But unlearning takes time. A helpful reassurance is reminding myself that I am exactly where my past-self wanted to be, an important achievement we all too often forget. Now reading: Breaking out of the repressive belief that you should only read one book at a time has been one of my greatest successes of 2019. I now love to read multiple books at a time, usually one fiction and at least one non-fiction, sometimes more non-fiction depending on the subject matter and the mood I’m in. Fiction is great to read before bed (but sometimes, you just get stuck into a really good psychology book and that before bed is great, too). Fiction-wise, I’m reading Choose Someone Else by Yvonne Fein, a collection of short stories centring on the moments when people feel ‘chosen,’ whether by a divine being or as the object of someone’s attraction. Written by a Jewish author, the contemporary Jewish experience and what it is to be the children of Holocaust survivors underscore her stories. When it comes to short stories, I am unashamedly voyeuristic: I enjoy most the (quasi) realistic stories that insert your directly into a character’s life for a period of time, a temporary window into another person’s existence. Fein is a master of this. Non-fiction, I’ve just started Big Coal by Guy Pearse, David McKnight and Bob Burton, which illustrates Australia’s infatuation with the coal industry and exposes the industry’s influence in the development (or lack thereof) of our economic and environmental policy. It is both eye-opening and infuriating to read about the extent to which mining companies can undermine laws designed to protect farmers, Indigenous communities, the environment. Perhaps most disappointing, yet unsurprising, is how the Federal and State governments enable this. An honourable mention goes to The Happiness Hypothesis by Jonathan Haidt, which may just be one of my all-time favourite reads. I love a good psychology book, and this one combines psychology, philosophy and neuroscience to examine ancient edicts of wisdom regarding happiness. The analysis is saturated with insight, and nurtures essential self-awareness. Self-awareness is something we all need more of, and learning about the ways our brain is programmed to function and subsequently learning to identify these processes in action is valuable for all of us when it comes to being better versions of ourselves. Now listening: My October Spotify playlist is currently this:

On top of that, I’ve been enjoying 80s disco-electronic (is there a better name for this? I would love to know). Think, M People, Chaka Khan, Soulsearcher. The kind of music you can groove to, that is super catchy, and has a funky bass line. I’m also revisiting my love for Foals and Duke Ellington (partially inspired by the latest season of Big Mouth). Podcasts are among my favourite things on this Earth. On trend with this period of existential pondering I’m floating around in right now, two podcasts have provided me with endless ideas for contemplation. I Said What I Said – Growing Pains speaks on the difficulty of transition, discussing whether difficulty is inherent or arises from our resistance (subconscious or otherwise) to whatever transition/growth/evolution we’re experiencing. I’ve found the sentiment that our suffering is in our resistance to be weirdly soothing, and trusting in myself to figure things out with time, and to be open to new opportunities, has been a huge help. Ten Percent Happier – A Radical Approach to Productivity, Self Compassion Series, Jocelyn K. Glei, is so full of bites of wisdom I don’t even know where to start. I find that the concept of productivity can be really burdensome sometimes, another form of internal pressure we place on ourselves, sometimes without a clear intent or purpose in mind. This podcast challenges and redefines our understanding of productivity, placing emphasis on the need for us to accept our human limitations and value our successes as much as we value aspiring towards our next goal. The overarching message is one of self-acceptance and engaging with meaningful work. It’s imperative that we accept our achievements, our failures, our progress or lack thereof as vital parts of our experience overall, and prioritise what’s meaningful to us (in any form – not just work) rather than ‘performing’ productivity which is, really, not that fulfilling at all.

[jccamus]

One subscriber or 48,000 pageviews: Why every journalist should know the “unit economics” of their content

One subscriber or 48,000 pageviews: Why every journalist should know the “unit economics” of their content https://ift.tt/2VlNjBP

Imagine you’re a barista at a coffee shop. You may have no background in business, finance, or data analysis — but you still probably have a decent handle on how the company you work for makes money and what role you play in that process.

You know that each cup of coffee you sell costs the customer $2 or $3. The company makes that amount minus the cost of the coffee grounds and the cup, with some fixed overhead costs. If you sell more cups of coffee, or get customers to buy more expensive drinks, the company makes more money — and with even basic arithmetic skills, you can probably estimate in your head about how much more. If you waste supplies or work a slow shift, the company makes less money. Simple.

I’ve thought about this in recent years because I’ve spent a lot of time sitting in coffee shops crunching data about business models for digital news. A collection of benchmarks and best practices from that work was published in the digital pay-meter playbook, released last month in a partnership between The Lenfest Institute and Harvard’s Shorenstein Center.

Through the course of that reporting, it struck me that baristas — and most employees in other industries — have a better understanding of their roles in their organization’s overall business than journalists do.

Most journalists know only a few things about the companies they work for: They know the news industry, especially the local news business, is struggling. They may generally know that if their articles attract more pageviews, the company makes more money from advertising— though they likely have little sense of how much. And in the last year or two, they’ve probably heard an announcement or two from an eager executive about the company’s new, or newly emphasized, digital subscription or membership initiative.

What they don’t know are the answers to some important questions, like: How much revenue does a typical article I write generate from advertising? What if it goes viral? Is it better for my article to get lots of pageviews or for it to attract digital subscribers? How do those two goals relate? After all, the coverage that generates the most clicks may by completely different from the stories that attract subscribers.

Indeed, when trying to get basic metrics from publishers about the value of a subscriber, the marginal impact of a pageview on advertising revenue, and other key metrics, I found that many publishers either didn’t have clear answers or that the information was siloed — with the advertising people looking at the ad metrics, the subscription people looking at subscription metrics, and journalists looking at outdated metrics such as how often their articles made the front page of the newspaper. Nobody was looking at these metrics together to get a clear view of the business as a whole.

It’s time for the news industry to have a clear grasp on the unit economics of journalism content. And while we don’t yet have all of the answers, some of the research and metrics we’ve gathered to date can point us in the right direction.

Unit economics for news: Some key metrics

There are a number of different metrics that can help journalists and news organizations understand their businesses better — but to start, publishers can go a long way by starting with just two key data points.

Customer lifetime value (CLV)

The metric publishers should know is customer lifetime value, a common metric in subscription businesses that looks at the average revenue generated by one new subscriber over the lifetime of the subscription.

There are many ways to calculate CLV, but in the simplest terms, it can be calculated by multiplying the average monthly revenue per subscriber by the expected lifetime of the digital subscription, meaning how long the average user will remain subscribed before they cancel. For a subscription business that averages $10/month per user and retains its subscribers for 20 months on average, the CLV would be $200. Every new subscription sold will generate, on average, $200 in new revenue.

The average revenue per subscriber can be calculated by dividing total monthly subscription revenue by total subscribers over a 6- or 12-month period. The average lifetime of a subscription can be calculated in a number of ways — some publishers have sophisticated retention curve models — but one simple and easy calculation that works for most purposes is:

1 ÷ monthly churn rate

This tells you the average number of months a subscription will last. Publishers who run paid advertising campaigns to acquire new subscribers may also choose to subtract the average cost per new acquisition — which is

total paid marketing spend per month ÷ total new subscribers generated per month

— from their CLV.

Our benchmarks show that a publisher performing in the 80th percentile — the typical range for a daily newspaper putting at least some effort into digital subscription sales — has a CLV of $217 for a digital subscriber. For publishers putting more focus on digital subscriptions the numbers can be substantially higher — often in the $300–$350 range.

Most publishers have some calculation of CLV used by their finance or consumer marketing departments — and if they don’t, they should. But beyond a relatively small team managing digital subscriptions, most people at a typical media company don’t know this number.

Digital ad revenue per 1,000 impressions (RPM)

The second metric publishers can look at to understand the unit economics of their digital business is digital ad revenue per 1,000 impressions, also called RPM. In its simplest form, RPM is calculated by dividing digital ad revenue by total pageviews and multiplying that number times 1,000. Put simply, it tells a publisher how much ad revenue they generate for every 1,000 pageviews they serve.

However, while every publisher should know their overall RPM number, it can also be a bit misleading because not every pageview generates the same amount of ad revenue. Most publishers do not sell out all of their available inventory with high-rate, directly sold advertisements. Instead, at the margins, their pageviews are primarily monetized by programmatic ads that can yield relatively little revenue per pageview. If a publisher increases their pageviews marginally above their usual baseline, their increase in ad revenue primarily comes from this category of lower-yield advertisement.

For day-to-day editorial decisions, then, what may matter more is marginal RPM: the ad revenue generated from the next 1,000 pageviews a publisher might generate. For most publishers, this means RPM for programmatic advertising only.

It’s also best to look at this metric, if possible, for content pages only. Ads sold on the home page or section front pages are still relevant to the business, but are not relevant to the impact one article or another might have on the business.

Though we weren’t able to gather a full benchmark for this metric from hundreds of publications, my informal survey of publishers suggests that most publishers are monetizing their pageviews in the range of $20–$25 per thousand pageviews overall and in the range of $6–$10 at the margins, primarily from programmatic advertising. As with CLV, in many organizations, knowledge of this metric is largely siloed within the digital advertising department.

Case study: 1 digital subscriber or 48,000 pageviews?

By knowing just these two basic metrics, publishers (and journalists) can learn quite a bit about the unit economics of their business and the value of their day-to-day work.

As a case study, consider this metro daily newspaper — we’ll call it Newspaper A — that was kind enough to share these two metrics and some basic traffic data with me.

Newspaper A has a customer lifetime value of $345, a bit higher than the norm. Based on its calculations, the average new digital subscription sold will be worth about that much over the course of the subscription. (If this seems high, it’s because the publisher in question has a higher-than-average subscription price and very good retention metrics.)

Newspaper A also generates $21.44 in total advertising per 1,000 pageviews, or $7.16 per 1,000 pageviews from programmatic advertising only. Its sell-through rates for non-programmatic ads are well below 100 percent of impressions, meaning that the programmatic number is a good proxy for total revenue from the next 1,000 pageviews they generate.

From just these few facts, we can learn a lot about the unit economics of Newspaper A’s journalism.

For example, we can tell that an article that attracts one new digital subscriber will, on average, generate as much revenue for the company as an article that generates 16,000 pageviews monetized through direct-sold advertising, or an article that generates 48,000 new pageviews monetized through programmatic advertising.

We reached that figure by taking the $345 CLV dividing it by the $21.44 and $7.16 figures in digital ad revenue per 1,000 pageviews and then multiplying each 1,000.

$345 ÷ $21.44 × 1,000 = 16,090

$345 ÷ $7.16, × 1,000 = 48,184

As a journalist or editor, knowing this fact alone could shift your perspective about what kind of coverage to focus on.

Looking at data for all articles published by Newspaper A in a particular week, the average article generated about 4,250 pageviews in the month after it was published. Using the CLV and marginal ad revenue metrics, we can therefore say that the average article generates $30.43 in programmatic ad revenue for the company.

Put another way, an article that attracts one new subscriber generates the same revenue as about 10 average-performing articles.

In contrast, the top-performing article from that time period attracted about 128,000 pageviews, or $916.48, equivalent to the revenue generated by about 2.6 subscribers.

Newspaper A cautioned that its CLV metric may be a bit inflated because its subscription system does not make it easy to gather reliable data. If we assume the more typical CLV benchmark of $217, the numbers tell a similar — if less extreme — story:

One new subscriber would be worth the same as ad revenue from 30,000 pageviews monetized through programmatic ads.

Ad revenue from one new subscriber would be worth the same as programmatic ad revenue from seven average-performing articles.

The top-performing article would be worth about 4.2 subscribers worth of programmatic ad revenue.

Revenue metrics and the newsroom

What would happen if news organizations shared and socialized this kind of information across their entire company — and, in particular, within the newsroom?

While no organization I know of has fully shared this information, my prediction is that it would help journalists do their jobs better. In today’s metrics-driven environment, the metrics actually available to journalists are primarily measures of total reach: ranked lists of articles by pageviews and in some cases more detailed data related to time spent on a page or other engagement metrics.

Even if they aren’t doing it intentionally, it would be natural for reporters and editors to respond to their successes and failures on these metrics and to adjust how they produce stories. Articles with sensational clickbait headlines get more pageviews; people producing headlines see that, and respond in kind. Stories that mention particular celebrities or politicians attract more clicks, so of course journalists are tempted to shoehorn those characters into otherwise unrelated stories. Stories covering a national or international issue generate a lot of broad interest in national media, so of course local journalists are tempted to rehash those same stories — even when there’s nothing new to add.

But we know that the coverage that attracts and retains subscribers is often different from the reporting that generates the most pageviews. Sometimes a niche topic — such as coverage of a high school sports team or highly local issue like weather — will be the sole reason for subscribing for a subset of users. More generally, users who subscribe tend to prefer reporting that is distinctive, local, and relevant to their daily lives over stories that are sensational or a rewrite of news they’ve seen elsewhere.

If newsrooms could view successful coverage not just as content that generates clicks, but also as journalism that delivers value to subscribers, it stands to reason that they would respond to those cues in the decisions they make day-to-day. (Indeed, clarifying and measuring success across the entire company is the only way I’ve seen businesses transform in the way that many news organizations must in order to survive.)

So how can publishers do this? While no publisher I know would say they’ve fully figured it out, many have experimented with versions of this approach. Here are four simple starting points based on what we’ve seen work across the industry:

Socialize key “unit economics” metrics. Start with the basics: For most publishers, there’s no reason that everyone in the company shouldn’t understand and know key metrics such as CLV and marginal ad revenue.

Basic daily reporting. This is similarly straightforward, but many publishers don’t do it: Everyone in the newsroom should know daily — or at worst, weekly — how many digital subscriptions were sold and from which sections of the site. One publisher who shared its report with me sends out a daily email to the newsroom that recaps the site’s traffic from the previous day. The report shows the number of new subscriptions per section, lists every URL that led to a new subscription, and highlights the authors of those articles.

Subscriber content-consumption reporting. If a publisher has the ability to segment subscriber traffic from non-subscriber traffic, they should provide this data to the newsroom as well. Knowing that subscribers are engaging more deeply with article X while non-subscribers are clicking on article Y can tell us a lot. I know from publishers who have tried this, for example, that the content viewed by subscribers correlates at least loosely with the coverage that generates new subscriptions. One publisher implemented a simple version of this using Parsely: On their typical article traffic report, they added a section that shows what the top story read by subscribers was the day before.

Subscription influence reporting. Some publishers have experimented with a “subscription influence” ranking chart meant to mimic the look and feel of the typical “most viewed” rankings that journalists see. This ranks a particular week’s articles by what percentage of new subscribers viewed that article on their path to subscribing or immediately after subscribing. One publisher with this kind of dashboard segmented the data to show, for each article, show how many subscriptions the article influenced at all (meaning the user viewed the article in the 30 days before subscribing), how many subscriptions it “highly influenced” (meaning the user viewed the article within 7 days of subscribing) and how many it “directly influenced” (meaning the user viewed the article in the same session as or directly after subscribing). This is better than simply looking at the last article a user viewed before subscribing, which seems not to be a very good predictor of anything in and of itself.

These four steps just scratch the surface of what is possible with this shift in thinking. Hopefully, as data becomes more easily available and publishers become increasingly focused on digital revenue, these kinds of developments will make their way into many news organizations.

Looking beyond content

Beyond understanding the relative value of different content produced by the newsroom, having a firm grasp on these kinds of metrics can also have broader implications for how publishers look at their business models.

For example, publishers can use these metrics day-to-day as they make decisions about meter limits and other access rules. If a publication lowers its meter limit from 5 free articles per month to three, it should ask not only how many pageviews it might lose, but also what those pageviews are worth — and how many new subscriptions the change would need to generate to constitute a net positive.

More broadly, understanding these metrics can help publishers understand how they should be allocating their resources. In a recent survey for the Reuters Institute’s Journalism, Media and Technology Trends and Predictions 2019 report, three quarters of news publishers surveyed said they devoted less than 25 percent of their company’s resources to growing their subscription products, and almost 4 in 10 said the percentage of their resources devoted to subscriptions was in the single digits. If publishers were more focused on metrics like CLV, they might be inclined to shift that balance so that — at the very least — subscriptions and advertising were treated as equal goals.

https://ift.tt/2MEuA0A via Nieman Lab October 13, 2019 at 10:33PM

[filipeteimuraz]

The Most Important Skills For Content Marketing

Some jobs are easy to define and prepare for:

Want to be an engineer? Go to school and get an engineering degree.

Want to code for Google? Go to school and study computer science.

What do you do when you want to be a content marketer?

Go to school and study content marketing? Hmm…there doesn’t seem to be a program for that, please try again.

Sure, it wouldn’t hurt to study general business or marketing, but that’s not enough either. You’ll end up learning many things you don’t really need and not learning those you do need.

All the top content marketers I know have a wide variety of useful skills that closely relate to content marketing.

This is largely out of necessity.

Content marketing—the modern version of it—didn’t really become popular until the last few years.

If you really want to be a great content marketer, there’s only one place for you to get your education:

The real world.

But do note that the bar has been raised.

Creating great content isn’t enough anymore if you want your content marketing to be successful.

Today, you need to not only create that content but also promote it.

Many marketers have started to wake up to this fact, which is a good thing.

However, just because they recognize that promotion is important doesn’t mean they know how to do it effectively.

In my experience, only a small percentage of marketers possess the skills that make them effective promoters as well.

The big problem is that if you don’t have these skills, you’ll struggle to learn how to promote effectively.

The reason for this is that there isn’t much help out there.

When it comes to creating great content, you can study the content your favorite blogs publish and attempt to replicate it.

But it’s next to impossible to understand all the work that goes on behind the scenes to promote that content unless the creators are generous enough to share it with you.

It takes a special kind of marketer—the cream of the crop—to learn both from resources (like blog posts) and experience.

These are the complete content marketers that get the results everyone else wants.

In this post, I’ll explain in detail the most important skills that I believe all great content marketers need.

Let’s dive in.

1. The best content marketers all have this skill…

This first skill might be the most important.

Critical thinking.

As a marketer who is still finding your way, you’ll be spending a lot of time learning about different tactics you can use to promote your content.

These might be email outreach tactics, link building tactics, or social media tactics…you get the picture.

But not all marketers who try a specific tactic will succeed with it. You probably know that already from firsthand experience.

It’s not because of luck or skill. Although these factors may play a role, the main factor that determines how successful you are with a tactic is fit.

Some tactics work in some niches and situations better than in others.

If you blindly try different tactics, you’ll have some success but not as much as you’d like.

The really good marketers, or the ones who seem to “get it” really quickly, are the ones who can critically think about a tactic.

They don’t just read a blog post and think, “This is pretty cool; I’d better try it!”

Instead, they think about questions like these:

Why does this tactic work?

What niches would it work best in? why?

Will this work for my content?

Can I can tweak it in any way to make it even more effective?

How can I test this?

Understanding a tactic before using it is different from just applying it blindly. I hope the reason behind those questions is clear.

Once you truly understand the tactics you learn, all of a sudden you are able to see where they fit together in an overall strategy.

The good news is that no one is born with critical thinking skills—these skills are developed.

And even better news is that you probably already have some, but maybe just need to consciously use them more often.

Regardless of where you are, let’s go through a complete example of how you would approach a tactic in real life.

Examining infographics with critical thinking: Here’s the situation: you come across an article I wrote about creating and promoting infographics.

Of course, your first reaction is excitement when I explain how infographics can be used to get thousands of visits.

And they can, for sure. But not in all situations.

After you read the post, you want to ask yourself the same questions I listed above.

Q: Why does this tactic work?

Infographics work because they are attractive, easy to consume, and can convey complex information quickly.

On top of that, really good ones stand out and get extra attention.

Because infographics are so shareable, you’ll get a ton of traffic if you can get the initial views to them. Providing an embed code underneath the infographic makes it easy to share (and gets you extra links).

Q: What niches would it work best in? Why?

Infographics are an image-based type of content. Therefore, they probably work best in image dominated niches. Think clothing, design, food, and even marketing to a degree.

The most important factor mentioned was that the topic needs to be interesting, which means that viewers need to care about it.

In “boring” niches like heating or bug removal, which are not that interesting to people (in general), it’s going to be tough to get the infographic to spread.

Q: Can I tweak it in any way to make it even more effective?

The reason why the effectiveness of infographics seems to be declining is that they’re becoming more commonplace.

So, if I can come up with a way to make mine more unique, I should be able to get better results. Perhaps, I can make a gifographic instead.

Q: How can I test this?

To test this tactic fairly, I would need to produce at least 5-10 professionally designed infographics.

This means I’ll likely need a budget of around $2,000-4,000.

I will then determine its effectiveness by looking at a few key metrics:

cost per subscriber

cost per link

cost per visit

Then, I will compare those metrics to the metrics of other tactics I’ve used to determine if I should produce more infographics.

End questions. In reality, you’d probably want to ask yourself even more questions.

How many readers of this blog or any other marketing blog honestly do this after reading about a tactic?

While I have some of the most active readers I’ve ever seen, which is great, I would guess far fewer than half of the readers who read a post do this.

If you want to develop critical thinking skills, you simply need to practice thinking. Ask yourself hard questions and try to get the best answers you can.

It’s okay if they’re not perfect; you’ll get better over time.

2. A love for data analysis sets you apart

A great content marketer is a lover of both content and numbers, which is a rare package.

A great content marketer is results-based: It starts with knowing that you need a way of measuring your results.

To do this, you need to understand the role of metrics in a business. These metrics are also being called key performance indicators (KPIs).

Metrics are a way of describing goals.

If your goal is to increase readership, the metrics you’ll be concerned with are traffic and subscribers.

You can monitor metrics over time to see if you are making progress. If the progress is too slow, you can test different approaches and look at the metrics to see if they are working.

Although every content marketing plan has its own goals, there are a few metrics that are important in nearly every scenario.

You’ll notice that those metrics cover numbers both before and after a sale.

The most common purpose of content marketing is to improve sales, so you’d better see an increase in revenue if you’re doing it right.

Data collection and analysis are the basic skills a content marketer needs: The first step is realizing that metrics are a necessary part of business.

You don’t need to obsess over them, but you do need to make sure you know how to track and analyze them.

Tracking is very simple.

Know how to install something like Google Analytics or KISSmetrics.

Analytics software not only tracks your readers’ behavior but also provides you with a dashboard for quickly organizing and analyzing it.

The first big obstacle content marketers need to overcome is learning how to use the analytics software.

You can find tutorials online to help with this, but the simplest way is to simply play around with it yourself and look through different tabs and settings.

The second obstacle is much larger.

You need to learn how to analyze that data.

You can get the basics of this pretty quickly:

choose your metrics

look at them over a valid time period

assess whether the metrics have improved or worsened

The hard part is knowing how to analyze data properly.

Really good content marketers know how to look at the situation, conduct very specific tests, and segment the analytics data to provide meaningful information.

Often, new marketers will make decisions based on analytics, but they don’t look at the right set of users.

For example, if you had two versions of a blog layout and saw that one had a better time on-page, you might conclude that it’s better.

However, it’s possible that it’s really not if you dig into things like:

browser

returning visitors

time of week

It may turn out that the second page performs better in all browsers except Internet Explorer.

That would lead you to investigate why that is, and you’d probably find out that it’s not showing up correctly. Fixing the errors would change the results of your experiment.

By having more experience and knowledge, that content marketer may have just made his or her business tens of thousands of dollars. Repeat that over the course of several years, and you see why a good content marketer is worth a lot.

This is a skill that needs to be developed through experience or mentorship by an expert. There are no shortcuts, e.g., you can’t just read a blog post about it and become an expert.

Every marketer should be able to do basic A/B testing: I’ve already mentioned testing a few times.

While there are a few types of experiments you can run, the most basic is an A/B split test.

First, you should understand what split tests are and why they are valuable.

They allow you to test two different versions of content to see which one leads to better metrics.

Split-testing is very useful for gaining continual small improvements in metrics such as conversion rate.

These small improvements add up to impressive results over time.

Second, you need to know how to run split tests and analyze the results.

Fortunately, it’s very simple now with modern software.

If you want a more detailed look at running a split test, you can refer to my guide on conversion optimization. Otherwise, there are just a few main steps.

First, you’ll need to pick a piece of software to help set up the test and track the results. For example, you can use Optimizely.

Then, you’ll need to create a hypothesis for a test.

The best split testers know how to test something that is likely to have a big impact on the metric you’re trying to improve.

These aren’t usually pulled out of thin air. Instead, they are determined based on analyzing analytics and user behavior data.

Software like Crazy Egg can show you how visitors use your website. You can use that information to make an educated guess about how to improve the clarity of your content.

Finally, you’ll need to determine a significant sample size and collect data. Most types of software do this for you nowadays.

At the end, you pick the winner and start again.

It will be a big benefit to understand the statistics behind split testing to spot mistakes and set up useful tests.

If you’ve never taken a statistics class, you can take one online free.

There are many, but here one popular class is Intro to Statistics: Making Decisions Based on Data

It’s not mandatory, but it’s a nice asset to have.

3. How far can you dig?

One question that I get all the time is: “How long does it take you to write your posts?”

Truthfully, it doesn’t take that long. Typically, I can do the actual writing in about 3 hours plus some time for editing.

But creating a post takes longer than that. It also takes a lot of research. Some posts, of course, will require more research than others.

Research is one of the most undervalued skills in a content marketer.

With respect to content marketing, there are a few main reasons why your ability to research effectively is so important.

Reason #1 – To understand your customer: If you want to be a good content marketer, you need to understand the type of reader you’re trying to attract.

If you don’t, you can’t produce content that they will be interested in.

You won’t be able to write about the right topics, and you won’t know how your readers enjoy consuming the information.

If you don’t research your target reader and understand them, you’re basically just guessing what they might like.

It can still work, but be prepared to produce hundreds of pieces of content until you learn what works.

Or do some research, and get it right the first time. Clients don’t want to pay you for months on end while you figure things out by trial and error.

So, how do you actually research your reader and customer?

There are tons of ways.

And there are no wrong answers.

You might start by paying attention to what readers are saying in the comments of your, or your competitor’s, website.

Answer questions like:

what do they like about the content?

what don’t they like?

what other subjects are they interested in?

what kind of job/life do they have (readers will often tell you)?

Or you can hunt down small niche forums and spend time digging into threads:

This is a great way to find out about their problems, which make great content ideas.

Or you can research demographic data using sites like Alexa.

Demographics are a key part of building a reader profile.

These are three of many options.

Great content marketers keep digging until they have as clear of a picture of their reader as possible.

They do this before they ever start writing.

An hour of research here might save several hours of work in the future.

Research #2 – To understand your product: Selling products isn’t an accident. You need to have a plan to effectively sell anything with content marketing.

Many inexperienced content marketers will say, “I’ll worry about the product later,” and focus on just producing content.

BIG mistake. Why?

Because when you do that, you don’t ensure that your product matches your audience’s needs.

This is called product-market fit.

Instead, you need to figure out how your content should relate to and add to the promotion of any products you sell.

This is where research comes in.

There are two main scenarios that you’ll need to be comfortable in.

The first is when you’re hired by a company that already sells a product. You need to research the product and understand what it does (and sometimes how it does it).

Pretend I hired you to manage the Crazy Egg blog. How could you do it without understanding the product?

You wouldn’t be able to create product tutorials or content that features the software until you get familiar with it:

While that’s far from the only content produced on the blog, it’s a type of content that plays an important role in the sales process.

The other scenario is when you don’t have a product yet.

Research is even more important in this case.

You’ll need to find out which products your audience will pay for and potentially how to create those products as well.

Finally, and most importantly, a great content marketer knows how to research content topics.

You need to know what you’re talking about in order to write a high quality article.

This involves knowing how to look up high quality journal articles as well as other resources:

It also involves spending the time understanding those resources.

If you’re writing about advanced topics, this takes considerable persistence, and many weak content marketers will simply find a lower quality resource instead.

Great content marketers aren’t lazy.

Reason #3 – To solve problems independently: The final main reason why research is an important skill for content marketers to have is because without it, you’ll often get stuck.

Content marketers will always be faced with questions and problems:

What should I write about?

What’s the best format for this content?

How do I create this form of content?

I don’t understand this topic, so what do I do?

Let me give you a realistic scenario…

Let’s say you’re keeping up with the latest SEO posts, and you see this filter before a list of tools on Backlinko:

And you think: “A filter like that would really improve a piece of content I’m working on.”

Here’s the problem: there’s no simple plugin to do it for you.

So, what then? Most will give up. A great content marketer, however, will dig in and figure it out.

They will learn that the filter uses a simple Javascript script.

Now, most content marketers don’t know how to create one of their own. However, the best will find someone who can make one.

They’ll head over to Odesk or Upwork and create a job posting for a developer.

(That’s not a relevant posting to this problem, by the way.)

The big difference between a good and bad content marketer is persistence.

Great marketers will keep researching until they find the answer to their problem. That’s what makes them stand out from everyone else.

Reason #4 – To improve your email outreach results: A lot of modern day promotion is based on email outreach, and it’s important you understand some basic numbers.

Most effective tactics will have a conversion rate of 5-10%. That means that for every 100 emails you send, 5 to 10 will end up in links. The actual percentage will depend on a lot of factors, e.g., your niche, copywriting skills, and quality of content.

Keep in mind that the conversion rate I quoted above is for the best tactics. Most tactics will have a lower conversion rate.

What does this mean in terms of research?

It means that you’ll have to send a ton of emails as part of your promotional campaigns. You’ll want to get at least 20-30 links to the content you’ve spent a few hundred dollars on creating.

In most cases, that means you’re sending 400+ emails, sometimes thousands.

Over time, that number won’t seem that big, but at first, I understand why that would seem like a ton.

In reality, there are two big components to this:

sending the actual emails and

researching hundreds or thousands of good prospects

The research usually takes more time than sending the emails, at least until you establish key relationships in your niche.

Since you’re dealing with hundreds or thousands of data points, it’s crucial that you work efficiently.

This usually means working with tools and knowing how to use them effectively.

For example, you could manually search for resource pages to target for a link. You could probably create a list of 100 in an hour or so.

Or you could simply find a similar type of content, plug it in a tool such as Ahrefs or Majestic, and have a list of hundreds or thousands of targets in seconds.

Work smarter, not harder (when possible).

4. Are you able to determine what is and isn’t important?

By now, you understand pretty well what promoting consists of.

And to be honest, it’s an insane amount of work.

You could easily hire someone (or multiple marketers) just to do promotion for your content.

In most cases, you can’t do that.

Instead, you need to find a way to balance content creation with content promotion while running other parts of your business as well.

Introducing the 80/20 rule: The skill I’m focusing on in this section is your ability to identify which of your actions produce the most results.

There’s a fairly established rule called the 80/20 rule (or Pareto principle).

It states that 80% of your results come from 20% of your effort. And it applies to just about everything.

One of the things it applies to is content promotion:

80% of your traffic will come from 20% of the links

80% of your links and traffic will come from 20% of your promotion tactics

In almost all cases, if a sample size is large enough, these numbers will be fairly accurate. They may differ by 5-10% in each direction, but the effect remains the same.

Using the 80/20 rule to eliminate fluff: The reason why I showed you this rule is because it’s possibly the most effective way to save a lot of time without losing much in the way of results.

In fact, you can often get better results in less time once you understand how the rule works in your case.

By breaking down your efforts and results, you can determine which of your efforts are contributing the most to your results.

Then, you can cut out all the rest. Why spend 80% of your efforts on only 20% of the returns you want?

Instead, use that extra time you freed up to double or triple down on that 20% of activity that actually produces results.

Here’s what it might look like in practice…

Track all your efforts and results, then eliminate waste: You never want to guess what is and isn’t effective.

Instead, start by tracking what you do to promote content, how much time you spend on it, and what you get in return for that effort.

Tracking time is pretty straightforward, but you’ll have to track your other metrics using tools such as Google Analytics (for traffic) and Ahrefs (for links).

Here are some hypothetical results:

The traffic per hour value is calculated by dividing the traffic from that activity by the time spent on the activity.

I used traffic as the main goal for this promotional campaign, but yours could be links, social shares, or whatever else you’re looking for.

Finally, you can calculate the percentage of results value by dividing the traffic per hour value by the total “traffic per hour” amount (e.g., 300/1466 for email outreach). This is a fair comparison since they are all based on a “per hour” basis.

What we see is that almost all of the results come from email outreach and emailing subscribers (about 88%). Those two activities take up 5.5 out of 11.5 hours of effort, or a little under 50% of the total effort.

This also illustrates that it doesn’t matter if there’s a perfect 80/20 ratio. You just want to see which activities are producing the least from your efforts.

In this case, you could cut out over half of your effort and lose only about 12% of the results, a great trade off.

Even if this time was spent just on more email outreach, you could take your total traffic from 2,500 to about 3,500 (a 40% increase).

If you wanted to spend more time emailing your subscribers, you could do it indirectly by spending the extra time trying to get more subscribers. This could be done by creating lead magnets or by employing other tactics to try to improve your conversion rate.

The bottom line is that you need to be efficient.

Find any effort that isn’t producing results (like screwing around on social media), and cut it out. You don’t have time to waste if you want to be a good content promoter.

5. Content takes many forms; being able to create it starts with writing

Although content marketing is a niche of marketing, it’s still fairly broad.

Content can take many different forms:

text posts

infographics

videos

slide shows

tools

charts

e-books

While it’s good to know how to create all types of content, they all, to some degree, involve writing.

Even making videos requires you to produce a script.

As you also know, most content marketing is done in the form of blog posts—typically text- and image-based content.

There are a few skills that go into being a good writer (and content marketer).

Skill #1 – Basic writing ability: There’s a common misconception about what it takes to be a “great writer” (at least when it comes to web content).

No, you don’t need to be able to write an essay like you were taught in school.

No, you don’t need to have an extensive vocabulary with tons of fancy words in it.

In reality, great writing for most situations is very simple. As long as you can write while following basic grammar and have enough of a vocabulary to express your ideas, you’re fine.

Basic writing ability also includes a few more things.

Research, as we talked about before, is one.

In addition, do you know how to use the writing tools at your disposal? Can you work in MS Word or Google Docs and know how to format your content?

Can you then take that post and format it in a major content management system such as WordPress and Drupal?

No, it’s not difficult, but you still need to know how to do these things.

If you don’t, spend a bit of time Googling and learning how to make the most of modern writing tools.

Skill #2 – Being able to write persuasively: When everyone has the same basic writing tools (that we just went over), how do great writers stand out?

Using the same words doesn’t mean you’ll have the same message. The words you choose will have a large effect on how interesting your content is to read.

You want to be able to write persuasively and conversationally:

Writing persuasively begins and ends with how well you understand your reader.

If you know exactly how they think, you can guide them from one thought to another until they reach a conclusion that provokes action.

This takes practice, and the more you write, the better you’ll get.

Additionally, you want to write conversationally.

It’s not complicated. There are only two main aspects:

Use first and second person pronouns – e.g., “you”, “us”, “your”, “we.”

Use the reader’s language – use the same words they do to describe their problems.

You can see that writing persuasively and writing conversationally overlap because to be good at both, you need to understand your readers’ language.

Skill #3 – Being able to come up with the right kind of ideas: There are some fantastic writers out there who make poor content marketers.

While they can write well when given a topic (or guidance on which topics are best), they struggle to see how it all fits together.

It’s not enough to come up with ideas to write about. You have to come up with content ideas that address readers at each step of the buying process.

In addition, you need to take interesting angles on each topic so that people actually would want to read them.

Let’s look at an example.

If you follow multiple marketing blogs, you’ve seen several posts on video marketing in the last few months.

These are typically along the lines of “X tips on using video marketing effectively.”

A post like that doesn’t have an angle to it. There’s no hook.

Instead, I wrote a post titled “4 Clever Ways Videos Can Help You Attract Customers”.

My readers are smart. They don’t want to do video marketing for the sake of it; they want to do it to achieve a result.

So, I took an angle on this topic. I showed how videos can be used to get more customers.

That’s something readers are actually interested in.

Skill #4 – Being able to write efficiently: Finally, it’s worth noting that the best content marketers are able to crank out high quality posts on a regular basis without burning out.

They can only do this by writing fast.

They’ve all developed a process that works for them, and it’s something that you’ll have to do as well.

If you’re a slow writer, read how you can double your writing speed.

One final note about this is that it will take time.

Everyone is a slow writer when they start. At that point, focusing on quality is most important.

Once you have a handle on that, then start focusing on producing content at a faster and more consistent rate.

6. Social skills on the Internet?

Marketers come from all sorts of backgrounds.

A large portion of the new generation of Internet marketers was attracted to the profession because it offered a chance to make money without truly interacting with people.

Or at least that’s what they thought.

If you want to be a legitimate and successful marketer, you need to have at least basic social skills.

You need to know how to communicate with co-workers, influencers, and your readers in a way that doesn’t seem awkward or manipulative.

This comes down to basic human interaction, especially in emails.

A lot of promotional success comes down to building relationships with people, and if you can’t hold a conversation, in any medium, it’s going to be tough to succeed.

Most people have these basic social skills, but if you think yours can be improved, read Ramit Sethi’s The Ultimate Guide to Social Skills, which is by far the most useful guide on the subject I’ve come across.

7. The ability to care about others will take you far

It’s a harsh truth.

No other website owner truly cares about your content.

So, when you email them asking them to take a look at it and give you a link of some sort, it’s tough to get a positive response.

That’s why good marketers never just ask for things.

Instead, they provide value upfront.

They do something nice for an influencer, and most people return the favor. It’s called the rule of reciprocity.

That’s a very simple concept that every marketer should know.

What really sets good marketers apart, however, is empathy.

Empathy just means that you’re good at viewing things from the perspective of others and understanding how they feel.

It’s an important skill in all parts of marketing, but especially promotion.

It’s another one of those skills that help you understand when certain tactics should be used.

For example, consider broken link building.

The idea is that you find broken links on someone’s website and then you let them know about the broken links and suggest yours as a replacement.

It’s a completely valid tactic in some cases…

Empathy allows you to understand what people care about.

The guy managing a resource page in your niche? He probably cares about keeping the page as up-to-date and useful as possible.

Why? Because the whole page is dedicated to links that help the visitor. If those links are dead, it has a big impact on the usefulness of the page.

Here’s an example of what one might look like.

What about the guy running a small blog? He also probably cares about broken links.

What about me? If someone emailed me telling me that I have broken links on Quick Sprout, how much would I care?

To be honest, not very much. I have hundreds of articles on Quick Sprout, so it’s inevitable that I’ll have a few dead links here and there.

I realize that dead links aren’t good for readers, but it’s honestly a small concern compared to all the other work I currently have to do for the site (and my other sites).

So, when people email me about dead links (they do quite often), they are not going to get my attention.

They’ve failed to understand the value I place on the broken links.

The reciprocity principle can work on just about anyone, but first, you need to give the other person something they value.

Can you develop empathy? I’m of the opinion that you can develop empathy just like any other skill.

However, it’s probably the most difficult skill to teach because I can’t just give you a guide or offer a course on it.

Instead, the only way to get better at it is to consciously put yourself in someone else’s shoes as often as you can.

Try to guess what they care about, and if possible, confirm it by having a conversation with them.

My best advice would be to pick five people you know every day, and answer questions like these for all of them:

“What are the things I value most in my life?”

“How much do I care about my professional life?”

“How often do I try to do something nice just to try to be a good person?”

“How loyal am I to my friends?”

You’ll probably have to do a little bit of Internet snooping for each person to answer these questions. Hopefully, you’ll begin to notice that you start thinking from another person’s perspective automatically when you’re trying to contact someone to promote your content.

8. A sloppy marketer is an unproductive one

A single piece of content may often have an entire campaign created around it, consisting of hundreds or thousands of emails.

Mix in a few different tactics, and there is a ton of data you need to keep track of.

This skill is a basic one: organization.

If someone asks you why they should hire you, they won’t be impressed if you tell them you have amazing organization skills. That’s because it’s expected.

If you can’t keep track of what you’ve done and what you have to do, there’s no way you’ll be able to run an efficient promotional campaign.

I’ve gone into it in great detail in the past, but for now, understand that there are three main components to organization as a marketer:

Attitude – You need to want to be as productive as possible for yourself, your boss (if you have one), and your readers. This means you understand the importance of organization and put in the effort required.

Technology – I write a lot about different tools you can use to be a more effective marketer. There’s a reason for this. Tools are a key part of working efficiently and staying organized. Even basic tools such as Google Docs and Trello go a long way when it comes to keeping track of things.

3. Adapting – Staying organized is a commitment. You need to commit to staying up-to-date with relevant tools. You have to commit to keeping track of all your work, even on days when you feel a bit lazy. When something new is added to the promotional campaign, you need to find a way to fit it into your organizational structure.

When you have thousands of emails to send and keep track of, you need to have an organizational system in place.

9. Will your content promotion be effective in the future?

A sign of a good content marketer isn’t how much they know.

That’s because in a field such as marketing, knowledge goes stale quickly.

What worked even a few years ago doesn’t work now.

What’s more important is that you are continuously learning.

One part of that is reading other marketers’ blogs. Since you’re here, I’m guessing you have that covered.

Even just reading one post a day adds up quickly.

I suggest using a tool such as Feedly so that you don’t waste time monitoring when posts come out (or just become an email subscriber of your favorite blogs).

A good portion of marketers do that first part.

What they don’t do is experiment.

Marketing may not be a field of science, but you constantly need to test different tactics and strategies.

You need to be able to quantify what does and what does not work effectively.

For the most part, this involves split-testing.

For example, you might want to determine the effectiveness of sending an initial email to someone without asking for a link in that first email.

To do this, you would send some emails that did ask for a link right away and some that didn’t.

Then, once you had a valid sample size, you could compare the results.

From there, you could continue to test different approaches.

It’s crucial to test on a regular basis because all tactics will become less effective over time. It’s up to you to try to find more effective tactics before they become “ruined” by all the other marketers out there.

If you’re new to testing, it can seem intimidating, but it gets simple once you know what to do. Here are some guides to testing that will walk you through the entire process:

How To Run Your First A/B Test To Find A Winning Variation

A/B Testing For Beginners: 70 Resources to Get You Started

10. Can you lead AND follow?

Content promotion campaigns can take many different forms.

One component that often changes is the role you have to take.

Sometimes, you’ll do all the work yourself. That’s pretty straightforward—you just do things the way you like.

But you might be part of a marketing team and will likely need to follow instructions.

Even more common, you might find yourself having to lead. I say it’s more common because even if you do all your marketing yourself, you can start hiring freelancers to help you with certain parts of promotion.

Or you might want to hire content creators so that you can spend more time on promotion.

Here are a few good guides on managing help effectively:

How to Manage Your Freelancers into 2016 and Beyond

10 Simple Tips for Managing Freelancers

How to Manage Your Freelance Content Providers

11. No time should be wasted waiting, which is why you need to be a jack-of-all-trades

There’s another area that I think will continue to become more important.

And it doesn’t contain just one skill, but a few different ones.

I’m talking about two in particular:

coding

design

These are “accessory skills.” You don’t need them to be a great content marketer.

However, they will help.

There are two main benefits of having some skill in either of these (you don’t need to be an expert).

First, it will save you time.

Instead of having to hire a developer to create a simple script (like that filtering example we looked at earlier), you could do it yourself.

Typically, being able to do something like that can save you days when producing a piece of content.

Add that up over many instances, and a content marketer who can code or design becomes even more valuable.

The second main benefit is that it will help you come up with better content ideas.

When you understand the role of design and coding in content, you start to see opportunities where they could be used to improve content.

Instead of just making a list post, you might think of creating a sortable list post where each item has its own custom icon.

But if you have no knowledge in these two areas, it’s never going to cross your mind unless something tells you to do it.

Helpful skill #1 – Coding: For the non-programmer, coding is very intimidating. It’s actually simpler than it looks (for most basic things).

In particular, for content marketing, you’ll want to learn three different languages:

HTML5

CSS

Javascript

Yes, technically HTML and CSS aren’t programming languages, but to a non-coder, they all appear similar.

The first two are the simplest and affect how your content shows up on a page.

Javascript is an actual programming language that allows the visitor to interact with a web page (and run a script).

You don’t need to become an expert, but you should be able to sort out simple problems.

For example, if a picture isn’t showing up correctly on a page, what do you do?

That’s a simple issue. You really want to avoid having to find someone who can help you fix it because that results in wasted hours.

Instead, you can go into the page source, find the error, and then fix it (in this case, the image width was wrong):

That fix should take less than a minute.

So, how do you learn these?

Take them one by one, and start with the Codecademy track for each of them:

HTML and CSS

Javascript

If you complete each of those, you’ll be ahead of the majority of marketers.

Helpful skill #2 – Design: Design skills can be used for just about every piece of content.

Think of the number of times a custom image could improve your content. Probably at least a few times a post.

One option is to hire a freelance designer to create them, which isn’t a bad option.

However, it’s silly to be waiting for a freelancer when all you need is one simple picture.

You don’t need to be an expert, but you should have basic design skills.

I can show you 90% of what you need to know in a single post. And that post is my guide to creating custom images for your blog post without hiring a designer (like the one below).

 12. The world of marketing will always change: those who adapt will survive

If you look at the great content marketers of today, you’ll notice something.

They were great marketers a few years ago although they might have had a different title.

All industries evolve over time and shift to new areas.

When a shift occurs, usually over a few years, everyone has a decision to make:

Should I adapt?

Some never make it and fall into obscurity.

There are still SEOs who are preaching tactics from the early 2000s that are no longer effective.

They never adapted to the changes in the SEO industry because they were afraid of losing what they had gained.

But the people you see who stay consistently at the top of their fields are always looking to learn about the “next thing.”

They adapt no matter what the circumstances are.

What this means to you as a content marketer: Content marketing, as we define it today, is still relatively young.

It’s only going to grow in the foreseeable future.

However, that doesn’t mean it won’t change.

Content marketing itself will continue to evolve. It’s up to you to always keep learning and improving your skill set.

Many poor content marketers know how to implement only one tactic or strategy successfully.

However, that’s not enough. A single tactic or strategy will never work in all situations. Also, it may not work in the future.

The best content marketers right now know how to use a wide variety of tactics and strategies depending on the situation (client, niche, resources, etc.).

They are also continually testing new ones to stay ahead of everyone else.

For you, this means that you need to keep learning.

When you find something that works, by all means use it. However, don’t think that you “figured it all out.”

Conclusion

Don’t get me wrong, content creation is incredibly important.

However, as far as the overall content marketing effectiveness goes, content promotion is often more important.

Furthermore, there’s a smaller percentage of marketers who know how to effectively promote content, so it really separates them from the rest.

If you want to be the best content promoter you can be, you need to develop all of the skills and techniques that I went over in this article.

Take a minute to honestly assess your skill level in each area. Then, come up with a plan to improve it, but focus on your biggest weaknesses first.

If you do, you will see your value as a content marketer rising, and you will get to the top of the field in time.

http://www.quicksprout.com/the-most-important-skills-for-content-promotion-and-how-to-learn-them/ Read more here - http://review-and-bonuss.blogspot.com/2019/04/the-most-important-skills-for-content.html

[webanalytics]

Deliver Step Change Impact: Marketing & Analytics Obsessions

Some moments in time are perfect to reflect on where you are, what your priorities are, and then consider what you should start-stop-continue. In those moments, you are not thinking of delivering incremental change… You are driven by a desire to deliver a step change (a large or sudden discontinuous change, especially one that makes things better – I’m borrowing the concept from mathematics and technology, from “step function”).

In those moments – common around new years or new annual planning cycles – the difference between delivering an incremental change vs. a step change is the quality of ideas you are considering. In this post, my hope is to both enrich your consideration set and encourage the breadth of your goals.

My professional areas of interest cover Customer Service, User Experience and Finance, though here on Occam’s Razor my focus is on influencing incredible Marketing through the use of innovative Analytics. To help kick-start your 2019 step change, I’ve written two “Top 10” lists, one for Marketing and one for Analytics – consisting of things I recommend you obsess about.

Each chosen obsession is very much in the spirit of my beloved principle of the aggregation of marginal gains. My recommendation is that you deeply reflect on the impact of the 10 x 2 obsessions in your unique circumstance, and then distill the ten you’ll focus on in the next twelve months. Regardless of the then you choose, I’m confident you’ll end up working on challenging things that will push your professional growth forward and bring new joy from the work you do for your employer.

Ready?

First… The Analytics top ten things to focus on to elevate your game this year…

The Step Change Analytics Obsessions List.

A1. Improve the Bounce Rate of your top 10 landing pages by 50%.

(Improving Bounce Rate results in reducing it. :))

You'll be surprised by the steep drop in Cost per Acquisition.

Google Optimize will be one of your BFFs in this quest. You’ll know you’ve moved beyond basic improvements when you start setting Custom Objectives – they require deeper thinking, which is a good sign.

A2. Eliminate 40% of the numbers from your dashboard.

Take the newly-created white space to explain what to do based on performance of 60% of the numbers that remain.

What your boss wants most this year, more than love, is to be told what the data wants her to do. Don't leave her guessing.

(Bonus, with actionable ideas: Smart Dashboard Modules.)

A3. Take your first steps towards unlocking smart algorithms.

Learn what Session Quality is in Google Analytics, then learn how to use it in your campaigns to improve conversions. In the Audiences section, go to the Behavior folder.

Learn what Smart Bidding is in Google Ads, then learn how to use it in your campaigns to improve outcomes.

Machine Learning algorithms will make our data smarter in unparalleled ways; Session Quality and Smart Bidding offer early clues about the scale and type of intellect. In both instances, it is immensely valuable to really understand how a smart algorithm uses billions of data signals to calculate likelihood of a conversion.

Across all your analytics data, algorithms will take you places humans simply can't. This should be the year you invest in an expansion in skills and practice to take advantage of these possibilities.

A4. Take a class in data visualization. It will save your life.

Anyone can make a complicated visual, it takes someone very special (you!) to draw out the essence of the story data is trying to tell.

My recommendations:

Free Courses: Data Visualization and D3.js and Data Analysis and Visualization at Udacity. Affordable: Data Analysis and Presentation Skills at Coursera. Occam’s Razor: Start with this one: Closing Data's Last-Mile Gap: Visualizing For Impact. And, there are five more linked to here.

  Through all these courses remember the most important thing about data visualization: It’s not the ink, it’s the think. Obsess about improving the think, just as much as I’m encouraging you to improve the ink.

A5. Obsess about what happens after campaigns end.

In our analytics practice we tend to celebrate victory too early (at the end of the campaign) or with insufficient breadth (the full scope of impact).

Did you get customers with high lifetime value? How long did the brand lift – say Awareness – last? What was the average order value of the second purchase by people you acquire via Search, compared to those via Retail?

Is there a difference in behavior between people who signed up for email over the last year vs those who did not? What the cost of getting a retail customer to make subsequent purchases over mobile apps lower?

A6. Understand your personal impact, obsess about improving it.

Grab the revenue number for the company. Now work out how much of it is influenced by you directly. Make a note of what it is (likely to be a couple percentage max).

Double that number this year.

What are the first five things on your list?

None of them will be easy, but converting insights into action via influence rarely is. But, you don't have to stretch too far to see how amazing it would be for you (and data too!) if you double your impact.

A7. Run one super-large controlled experiment.

To prove what your Executives believe purely from their gut. Or, to disprove it.

Does Facebook advertising really work better than TV? Can you create premiumness for your brand using digital? Is a 15% coupon now better than 20% off the next purchase? Does swapping out male model posters for cute animals triple sales?

Does sponsoring a fashion show lead to an increase in brand equity? Does free pickup in store result in higher attach rates?

A8. Identify four relevant micro-outcomes to focus on in 2019

(In addition to the macro-outcome of revenue).

Businesses win when you optimize for a portfolio, because at any given time only a tiny fraction of people want to buy. Solving for micro and macro-outcomes is directly connected to the holy grail of solving for short-term AND long-term success.

Employees also become smarter when they have to optimize for more than one thing. :)

A9. Throw away your custom attribution model. Embrace data-driven attribution.

For some things, humans are already less smart than machines. Trying to guess what might be happening across millions of touchpoints on and off site, on and offline, is one of those things.

Skip the first five steps of attribution’s ladder of awesomeness, jump to DDA. From the tens of hours saved per week, figure out how to feed offline data into your data driven attribution model.

With an obsession with data-driven attribution, you are also solving for a portfolio rather than a silo. Super cool, super profitable.

A10. Hire an experienced statistician to be a part of your analytics team.

There is too much goodness in modeling that you are not taking advantage of. From segmentation models to identifying incrementality to predictive modeling to survival analysis to clustering to time series to… I could keep going on and on.

2019's the year you get serious about serious analytics.

A11. Bonus: Reporting kills, analysis thrills.

If that is true, and it is, :), then what % of time are you personally spending between Data Capture – Data Reporting – Data Analysis?

Outsource or eliminate half of your data capture and data reporting responsibilities, and allocate it to data analysis and driving action.

You'll be surprised at the increase in your salary and bonus (oh, and the company will benefit too!).

In context of Analytics are you aiming for something special in 2019 that I've not covered above? Will you please share that with me by adding a comment? Thank you.

Switching gears, here are ten things to obsess about to collectively deliver a step change via your Marketing game this year…

The Step Change Marketing Obsessions List.

M1. Improve the Bounce Rate of your top 10 landing pages by 50%.

(Improving Bounce Rate results in reducing it. :))

Same as the #1 on the Analytics list. :) Far too many Marketers ignore this simple strategy to make lots more money. You work so very hard to earn attention, why then let your ads write checks your website can’t cash?

An additional delightful benefit: I find that getting Marketers to obsess about landing pages forces them to audit the user experience, something worth its weight in gold.

M2. Put up or shut up time for your social media strategy.

99.999% of corporate social media participation yields nothing.

Your CMO wants people to love your brand and organically amplify its goodness. It genuinely is a good thought. Except, a cursory glance at your social contributions show nothing of that sort over the last three years.

So, why are you spending all that money?

I recommend using that money to buying your team iPhones every Friday, I assure you that'll have a positive ROI.

Or. Focus on social media primarily as a paid media strategy. Bring the same discipline to the application of accountability to social media ads that you bring to your Display or Video ads anywhere on the web.

Here are five brand and five performance metrics that'll be your BFFs in 2019, as you social strategy lives up to that now famous mantra: Show me the money!

M3. Keep control of creativity, give up control of the creative.

Machines are much better at optimizing the latter for short or long term.

(For now) You are still better at the former – do lots of it, then hand it over to smart algorithms.

It is hard, especially for creative types who confuse creativity with creative. But, with every passing day you are harming your bottom-line more if you don’t follow the formula above.

Also consider the Machine Learning opportunities for Marketing beyond creative.

Aim to shift 25% of your marketing budgets in 2019 to opportunities that are powered by ML algorithms and rejoice at the boost in profits that results.

M4. TV works, solve for each factor that drives success.

Most TV campaigns are sold and bought based on reach (GRPs FTW!).

In my experience you should optimize for reach AND one overarching story AND creative consistency AND ensure each successfully tested creative has enough frequency to wear-in.

And, if you can't solve for three ANDs… Shift money to max out the Performance Digital opportunity, then with the left over money buy every person in your team – and at your agency – a new car. Your TV budget is big enough , and trust me when I say that giving out a new car will have very high motivational and bottom-line ROI.

M5. Seek to understand the customer journey.

What drives the first purchase? What drives the second? What drives the support calls in between? What does using the product really, really feel like? What drives advocacy?

All advertising that fails does so because the Marketer behind it understands only one sliver of the experience, then solves for that sliver with heart-breaking short-term focus.

When the Marketer understands the answers to the above questions, it influences the creative, it influences targeting, it influences retail store displays, it influences frequency, it influences product design, it influences…. it changes everything. Including profits.

Journeys are better than tinder dates.

6. Solve for intent. It is more possible and more critical with every passing day.

See-Think-Do-Care is a great intent-centric business framework, if I may say so myself, for challenging your current marketing strategy.

What intent is your current marketing content (tv, digital, ads, emails) targeting? What happens once your ads meet that intent? What meaningful content are you publishing, on and offline, to engage audiences before and after the BUY NOW (!) moment? Is your measurement aligned with the intent your marketing is targeting, or are you judging a fish by its ability to climb a tree? How do you know?

Shifting to See-Think-Do-Care is the single biggest force multiplier when it comes to your marketing. Help shift your organizational thinking to the current century in 2019.

M7. Your marketing budget allocation can be improved anywhere from 50% to 50,000%.

Allocating budgets is the hardest decision a Senior Marketer will make. Most will use strategies like Digital had 27% of budget last year, this year we should do between 28 and 30%. History, gut-feel, inter-company-politics, etc. are primary reasons why this silly mindset is pervasive across companies.

A better way? Profitable opportunity size.

I don't think you can argue with the first part: Invest where you make more profit. The second part takes a bit more work. It comes from plotting diminishing margin curves with confidence intervals. In English: How high can the investment goes before every $1 you invest returns less?

You are a Marketer, so it's unlikely that you'll plot these curves. Make it a priority for your Analytics team to do so; without them massive chunks of your budget is being flushed.

(Also, see obsession #10 on the Analytics list.)

M8. A grandmother's Marketing strategy for grandmothers only.

A bit provocative, but I want to challenge how most Marketers just make little tweaks to their strategy. The bigger the company, the more that this pernicious problem exists. Don't let that be you, and allow me to share two views that'll challenge your reality.

Here's the average time spent per day by US adults with media devices…

My humble description of a "grandmother's marketing strategy" is the bar on the right (65+).

It is eminently sensible for our marketing for our fellow 65+ aged Earthlings to be reflective of the implications of that right-most bar.

The problem arises when our entire marketing strategy is an extension of that right-most bar. For our entire marketing strategy to be structured on that 6:55 you see above, when our products and services are not 65+ centric is… A bit silly. Perhaps even reflective of failing our fiduciary duty.

Note the difference in total media consumption (time, place, device, more). Note the products and services your company currently offers. Reflect on this: How misaligned is your current marketing strategy?

I get really excited about something super-cool, but subtle, in the data above: The implication of the difference between active vs. passive consumption!

The difference between leaning-back and letting content wash over us vs. leaning-in and pulling content you desire is huge. It dramatically changes what your marketing should be solving for (beyond the obvious investment alignment by platforms issue).

One more reality-check for your 2019 Marketing strategy: Here's a helpful deep drive into the shifts in consumption of TV across US adults – in just six years (!!)…

This possibly explains why Toyota's entire Marketing strategy seems to be TV-centric (with the incredible frequency of 48 per day per person here in the bay area!). It seems Toyota is only trying to sell cars to 65+ (whose TV watching has actually increased).

In 2019, resolve to align your marketing strategy with your 1. products 2. goals 3. audience, and 4. amount of expressed intent on the platform.

Credits: Originally created by Sara Fischer of Axios, the first graph is via my buddy Thomas Baekdal's newsletter. 100% of you need to sign up for it. The second chart is from the lovely team at The Economist.

M9. Suck less more.

Every campaign you are currently executing can be made to suck less – especially if you think end-to-end experience.

Ex: Expedia's emails are so long they always trigger "[Message clipped] View entire message." Suck less and maybe use my past behavior to send shorter emails so I know you care about me?

Ex: Nordstrom sends me one email a day with exclusive deals – how many clothes do they think I need? Suck less and maybe send me one a month? Or, base it on shopping patterns in store to deliver delight and not just a deal?

Ex: Macy's email I just received (titled "Resolution #1: get an extra 20% off before it ends") has promotions for Women, Men, Shoes, Bed & Bath, Kids, Juniors, Jewelry, Plus Sizes, Handbags, Home, Kitchen, Beauty. All above the fold. Below the fold: Large pictures with promotions for White Bedding, Biggest Underwear, Biggest Mattress (yes again), Best Face Forward, 25% off Adidas, Macy's presents the Edit, Fresh Pastels (the image does not make clear what this is), Free, Fast Pickup. PHEW! This can be unsucked at so many levels, with just a little bit of love and focus.

Ex: Even really good programs can use sucking less. Companies like Google and Microsoft have so many divisions. Each team/department optimizes for itself, emails are pretty good, hence each thinks they are doing really well. But, if you flip the lens to me – the recipient – I get a lot of email from each company. I wish someone at G/M would track Emails Sent/Humans Sent To, and reflect on the sad reality. It would create a culture of Marketing with me at the center instead of a company department – you can imagine the benefits.

I'm using email marketing as an example of activating the power of suck less because I love email marketing. It is an effective and profitable strategy. It has loads of behavioral data available. It needs a comparatively small team to execute well. Yet see how much opportunity there is to suck less at even the largest companies.

Substantially bigger opportunities to suck less exist in all other Marketing you are doing. TV. Print. Radio. Display (omg, sooooo much opportunity!). Video. Website. Mobile app. Everything else.

All you need to do is take a quick peek under the covers.

Your 10x goal for 2019: For every $1 invested in chasing a shiny object (VR ads! Influencer marketing!!!), invest $10 in sucking less in existing large clusters of your Marketing.

Profits that follow will also be that lopsided.

One last bit, culture eats strategy for breakfast. Create a quarterly Most Unsucked Team award, and celebrate this dimension of success. Incentives matter.

M10. Bring your great taste and expectations to work.

You can easily recognize when something is mediocre – even when others put lipstick on the pig and run it around the organization as the greatest success of the month.

You know what exceptional looks and feels like – you are not just a Marketer, you are an intelligent customer.

Yet, my experience is that most Marketers stay in their lane. Often, company cultures encourage that non-beneficial behavior.

In 2019, speak up.

You have great taste. Don't leave it at home when you leave for work.

Speak up.

When you see low quality work being pushed out by your Marketing organization… Create alternative mocks. Push for your version of the brand's tag line (not the generic MBA buzzword puke-fest). Ask for a better balance between Earned-Owned-Paid marketing. Politely challenge your Leader's assertion that creative x is better because he feels like it will be. Recommend experimenting with reckless ideas, instead of directly putting 30% of the budget on them. If you see lipsticked pigs being paraded around as exceptional examples, humbly, privately, flag the corrosive implication on culture to the most senior leader who'll listen to you.

Speak up.

You deserve to be heard.

When you speak, it'll give others around you the courage to speak up as well. Smart people tend to run in packs.

That’s it. :)

A slight repetition: Reflect deeply on the impact of the 10 x 2 obsessions in your unique business environment. Then, distill down to a total of ten you’ll focus on in the next twelve months. Finally, put a start and expected end date for each item. If you get through the list, you would have contributed a step change to your company’s bottom-line, and discovered unexpected personal joy.

As always, it is your turn now.

If you had already identified obsessions for Analytics and/or Marketing for the next twelve months for yourself, what obsessions did you choose? I’m super curious. Are there a couple in my lists above that would be particularly impactful in your company? Some of my recommendations are quite straight-forward, what do you think get’s in the way of focusing on them?

Please share your obsessions, tips, culture-shifting strategies, and critique via comments below.

Thank you.

The post Deliver Step Change Impact: Marketing & Analytics Obsessions appeared first on Occam's Razor by Avinash Kaushik.

from Occam's Razor by Avinash Kaushik http://bit.ly/2VCJlor #Digital #Analytics #Website

[nathandgibsca]

Deliver Step Change Impact: Marketing & Analytics Obsessions

Some moments in time are perfect to reflect on where you are, what your priorities are, and then consider what you should start-stop-continue. In those moments, you are not thinking of delivering incremental change… You are driven by a desire to deliver a step change (a large or sudden discontinuous change, especially one that makes things better – I’m borrowing the concept from mathematics and technology, from “step function”).

In those moments – common around new years or new annual planning cycles – the difference between delivering an incremental change vs. a step change is the quality of ideas you are considering. In this post, my hope is to both enrich your consideration set and encourage the breadth of your goals.

My professional areas of interest cover Customer Service, User Experience and Finance, though here on Occam’s Razor my focus is on influencing incredible Marketing through the use of innovative Analytics. To help kick-start your 2019 step change, I’ve written two “Top 10” lists, one for Marketing and one for Analytics – consisting of things I recommend you obsess about.

Each chosen obsession is very much in the spirit of my beloved principle of the aggregation of marginal gains. My recommendation is that you deeply reflect on the impact of the 10 x 2 obsessions in your unique circumstance, and then distill the ten you’ll focus on in the next twelve months. Regardless of the then you choose, I’m confident you’ll end up working on challenging things that will push your professional growth forward and bring new joy from the work you do for your employer.

Ready?

First… The Analytics top ten things to focus on to elevate your game this year…

The Step Change Analytics Obsessions List.

A1. Improve the Bounce Rate of your top 10 landing pages by 50%.

(Improving Bounce Rate results in reducing it. :))

You'll be surprised by the steep drop in Cost per Acquisition.

Google Optimize will be one of your BFFs in this quest. You’ll know you’ve moved beyond basic improvements when you start setting Custom Objectives – they require deeper thinking, which is a good sign.

A2. Eliminate 40% of the numbers from your dashboard.

Take the newly-created white space to explain what to do based on performance of 60% of the numbers that remain.

What your boss wants most this year, more than love, is to be told what the data wants her to do. Don't leave her guessing.

(Bonus, with actionable ideas: Smart Dashboard Modules.)

A3. Take your first steps towards unlocking smart algorithms.

Learn what Session Quality is in Google Analytics, then learn how to use it in your campaigns to improve conversions. In the Audiences section, go to the Behavior folder.

Learn what Smart Bidding is in Google Ads, then learn how to use it in your campaigns to improve outcomes.

Machine Learning algorithms will make our data smarter in unparalleled ways; Session Quality and Smart Bidding offer early clues about the scale and type of intellect. In both instances, it is immensely valuable to really understand how a smart algorithm uses billions of data signals to calculate likelihood of a conversion.

Across all your analytics data, algorithms will take you places humans simply can't. This should be the year you invest in an expansion in skills and practice to take advantage of these possibilities.

A4. Take a class in data visualization. It will save your life.

Anyone can make a complicated visual, it takes someone very special (you!) to draw out the essence of the story data is trying to tell.

My recommendations:

Free Courses: Data Visualization and D3.js and Data Analysis and Visualization at Udacity. Affordable: Data Analysis and Presentation Skills at Coursera. Occam’s Razor: Start with this one: Closing Data's Last-Mile Gap: Visualizing For Impact. And, there are five more linked to here.

  Through all these courses remember the most important thing about data visualization: It’s not the ink, it’s the think. Obsess about improving the think, just as much as I’m encouraging you to improve the ink.

A5. Obsess about what happens after campaigns end.

In our analytics practice we tend to celebrate victory too early (at the end of the campaign) or with insufficient breadth (the full scope of impact).

Did you get customers with high lifetime value? How long did the brand lift – say Awareness – last? What was the average order value of the second purchase by people you acquire via Search, compared to those via Retail?

Is there a difference in behavior between people who signed up for email over the last year vs those who did not? What the cost of getting a retail customer to make subsequent purchases over mobile apps lower?

A6. Understand your personal impact, obsess about improving it.

Grab the revenue number for the company. Now work out how much of it is influenced by you directly. Make a note of what it is (likely to be a couple percentage max).

Double that number this year.

What are the first five things on your list?

None of them will be easy, but converting insights into action via influence rarely is. But, you don't have to stretch too far to see how amazing it would be for you (and data too!) if you double your impact.

A7. Run one super-large controlled experiment.

To prove what your Executives believe purely from their gut. Or, to disprove it.

Does Facebook advertising really work better than TV? Can you create premiumness for your brand using digital? Is a 15% coupon now better than 20% off the next purchase? Does swapping out male model posters for cute animals triple sales?

Does sponsoring a fashion show lead to an increase in brand equity? Does free pickup in store result in higher attach rates?

A8. Identify four relevant micro-outcomes to focus on in 2019

(In addition to the macro-outcome of revenue).

Businesses win when you optimize for a portfolio, because at any given time only a tiny fraction of people want to buy. Solving for micro and macro-outcomes is directly connected to the holy grail of solving for short-term AND long-term success.

Employees also become smarter when they have to optimize for more than one thing. :)

A9. Throw away your custom attribution model. Embrace data-driven attribution.

For some things, humans are already less smart than machines. Trying to guess what might be happening across millions of touchpoints on and off site, on and offline, is one of those things.

Skip the first five steps of attribution’s ladder of awesomeness, jump to DDA. From the tens of hours saved per week, figure out how to feed offline data into your data driven attribution model.

With an obsession with data-driven attribution, you are also solving for a portfolio rather than a silo. Super cool, super profitable.

A10. Hire an experienced statistician to be a part of your analytics team.

There is too much goodness in modeling that you are not taking advantage of. From segmentation models to identifying incrementality to predictive modeling to survival analysis to clustering to time series to… I could keep going on and on.

2019's the year you get serious about serious analytics.

A11. Bonus: Reporting kills, analysis thrills.

If that is true, and it is, :), then what % of time are you personally spending between Data Capture – Data Reporting – Data Analysis?

Outsource or eliminate half of your data capture and data reporting responsibilities, and allocate it to data analysis and driving action.

You'll be surprised at the increase in your salary and bonus (oh, and the company will benefit too!).

In context of Analytics are you aiming for something special in 2019 that I've not covered above? Will you please share that with me by adding a comment? Thank you.

Switching gears, here are ten things to obsess about to collectively deliver a step change via your Marketing game this year…

The Step Change Marketing Obsessions List.

M1. Improve the Bounce Rate of your top 10 landing pages by 50%.

(Improving Bounce Rate results in reducing it. :))

Same as the #1 on the Analytics list. :) Far too many Marketers ignore this simple strategy to make lots more money. You work so very hard to earn attention, why then let your ads write checks your website can’t cash?

An additional delightful benefit: I find that getting Marketers to obsess about landing pages forces them to audit the user experience, something worth its weight in gold.

M2. Put up or shut up time for your social media strategy.

99.999% of corporate social media participation yields nothing.

Your CMO wants people to love your brand and organically amplify its goodness. It genuinely is a good thought. Except, a cursory glance at your social contributions show nothing of that sort over the last three years.

So, why are you spending all that money?

I recommend using that money to buying your team iPhones every Friday, I assure you that'll have a positive ROI.

Or. Focus on social media primarily as a paid media strategy. Bring the same discipline to the application of accountability to social media ads that you bring to your Display or Video ads anywhere on the web.

Here are five brand and five performance metrics that'll be your BFFs in 2019, as you social strategy lives up to that now famous mantra: Show me the money!

M3. Keep control of creativity, give up control of the creative.

Machines are much better at optimizing the latter for short or long term.

(For now) You are still better at the former – do lots of it, then hand it over to smart algorithms.

It is hard, especially for creative types who confuse creativity with creative. But, with every passing day you are harming your bottom-line more if you don’t follow the formula above.

Also consider the Machine Learning opportunities for Marketing beyond creative.

Aim to shift 25% of your marketing budgets in 2019 to opportunities that are powered by ML algorithms and rejoice at the boost in profits that results.

M4. TV works, solve for each factor that drives success.

Most TV campaigns are sold and bought based on reach (GRPs FTW!).

In my experience you should optimize for reach AND one overarching story AND creative consistency AND ensure each successfully tested creative has enough frequency to wear-in.

And, if you can't solve for three ANDs… Shift money to max out the Performance Digital opportunity, then with the left over money buy every person in your team – and at your agency – a new car. Your TV budget is big enough , and trust me when I say that giving out a new car will have very high motivational and bottom-line ROI.

M5. Seek to understand the customer journey.

What drives the first purchase? What drives the second? What drives the support calls in between? What does using the product really, really feel like? What drives advocacy?

All advertising that fails does so because the Marketer behind it understands only one sliver of the experience, then solves for that sliver with heart-breaking short-term focus.

When the Marketer understands the answers to the above questions, it influences the creative, it influences targeting, it influences retail store displays, it influences frequency, it influences product design, it influences…. it changes everything. Including profits.

Journeys are better than tinder dates.

6. Solve for intent. It is more possible and more critical with every passing day.

See-Think-Do-Care is a great intent-centric business framework, if I may say so myself, for challenging your current marketing strategy.

What intent is your current marketing content (tv, digital, ads, emails) targeting? What happens once your ads meet that intent? What meaningful content are you publishing, on and offline, to engage audiences before and after the BUY NOW (!) moment? Is your measurement aligned with the intent your marketing is targeting, or are you judging a fish by its ability to climb a tree? How do you know?

Shifting to See-Think-Do-Care is the single biggest force multiplier when it comes to your marketing. Help shift your organizational thinking to the current century in 2019.

M7. Your marketing budget allocation can be improved anywhere from 50% to 50,000%.

Allocating budgets is the hardest decision a Senior Marketer will make. Most will use strategies like Digital had 27% of budget last year, this year we should do between 28 and 30%. History, gut-feel, inter-company-politics, etc. are primary reasons why this silly mindset is pervasive across companies.

A better way? Profitable opportunity size.

I don't think you can argue with the first part: Invest where you make more profit. The second part takes a bit more work. It comes from plotting diminishing margin curves with confidence intervals. In English: How high can the investment goes before every $1 you invest returns less?

You are a Marketer, so it's unlikely that you'll plot these curves. Make it a priority for your Analytics team to do so; without them massive chunks of your budget is being flushed.

(Also, see obsession #10 on the Analytics list.)

M8. A grandmother's Marketing strategy for grandmothers only.

A bit provocative, but I want to challenge how most Marketers just make little tweaks to their strategy. The bigger the company, the more that this pernicious problem exists. Don't let that be you, and allow me to share two views that'll challenge your reality.

Here's the average time spent per day by US adults with media devices…

My humble description of a "grandmother's marketing strategy" is the bar on the right (65+).

It is eminently sensible for our marketing for our fellow 65+ aged Earthlings to be reflective of the implications of that right-most bar.

The problem arises when our entire marketing strategy is an extension of that right-most bar. For our entire marketing strategy to be structured on that 6:55 you see above, when our products and services are not 65+ centric is… A bit silly. Perhaps even reflective of failing our fiduciary duty.

Note the difference in total media consumption (time, place, device, more). Note the products and services your company currently offers. Reflect on this: How misaligned is your current marketing strategy?

I get really excited about something super-cool, but subtle, in the data above: The implication of the difference between active vs. passive consumption!

The difference between leaning-back and letting content wash over us vs. leaning-in and pulling content you desire is huge. It dramatically changes what your marketing should be solving for (beyond the obvious investment alignment by platforms issue).

One more reality-check for your 2019 Marketing strategy: Here's a helpful deep drive into the shifts in consumption of TV across US adults – in just six years (!!)…

This possibly explains why Toyota's entire Marketing strategy seems to be TV-centric (with the incredible frequency of 48 per day per person here in the bay area!). It seems Toyota is only trying to sell cars to 65+ (whose TV watching has actually increased).

In 2019, resolve to align your marketing strategy with your 1. products 2. goals 3. audience, and 4. amount of expressed intent on the platform.

Credits: Originally created by Sara Fischer of Axios, the first graph is via my buddy Thomas Baekdal's newsletter. 100% of you need to sign up for it. The second chart is from the lovely team at The Economist.

M9. Suck less more.

Every campaign you are currently executing can be made to suck less – especially if you think end-to-end experience.

Ex: Expedia's emails are so long they always trigger "[Message clipped] View entire message." Suck less and maybe use my past behavior to send shorter emails so I know you care about me?

Ex: Nordstrom sends me one email a day with exclusive deals – how many clothes do they think I need? Suck less and maybe send me one a month? Or, base it on shopping patterns in store to deliver delight and not just a deal?

Ex: Macy's email I just received (titled "Resolution #1: get an extra 20% off before it ends") has promotions for Women, Men, Shoes, Bed & Bath, Kids, Juniors, Jewelry, Plus Sizes, Handbags, Home, Kitchen, Beauty. All above the fold. Below the fold: Large pictures with promotions for White Bedding, Biggest Underwear, Biggest Mattress (yes again), Best Face Forward, 25% off Adidas, Macy's presents the Edit, Fresh Pastels (the image does not make clear what this is), Free, Fast Pickup. PHEW! This can be unsucked at so many levels, with just a little bit of love and focus.

Ex: Even really good programs can use sucking less. Companies like Google and Microsoft have so many divisions. Each team/department optimizes for itself, emails are pretty good, hence each thinks they are doing really well. But, if you flip the lens to me – the recipient – I get a lot of email from each company. I wish someone at G/M would track Emails Sent/Humans Sent To, and reflect on the sad reality. It would create a culture of Marketing with me at the center instead of a company department – you can imagine the benefits.

I'm using email marketing as an example of activating the power of suck less because I love email marketing. It is an effective and profitable strategy. It has loads of behavioral data available. It needs a comparatively small team to execute well. Yet see how much opportunity there is to suck less at even the largest companies.

Substantially bigger opportunities to suck less exist in all other Marketing you are doing. TV. Print. Radio. Display (omg, sooooo much opportunity!). Video. Website. Mobile app. Everything else.

All you need to do is take a quick peek under the covers.

Your 10x goal for 2019: For every $1 invested in chasing a shiny object (VR ads! Influencer marketing!!!), invest $10 in sucking less in existing large clusters of your Marketing.

Profits that follow will also be that lopsided.

One last bit, culture eats strategy for breakfast. Create a quarterly Most Unsucked Team award, and celebrate this dimension of success. Incentives matter.

M10. Bring your great taste and expectations to work.

You can easily recognize when something is mediocre – even when others put lipstick on the pig and run it around the organization as the greatest success of the month.

You know what exceptional looks and feels like – you are not just a Marketer, you are an intelligent customer.

Yet, my experience is that most Marketers stay in their lane. Often, company cultures encourage that non-beneficial behavior.

In 2019, speak up.

You have great taste. Don't leave it at home when you leave for work.

Speak up.

When you see low quality work being pushed out by your Marketing organization… Create alternative mocks. Push for your version of the brand's tag line (not the generic MBA buzzword puke-fest). Ask for a better balance between Earned-Owned-Paid marketing. Politely challenge your Leader's assertion that creative x is better because he feels like it will be. Recommend experimenting with reckless ideas, instead of directly putting 30% of the budget on them. If you see lipsticked pigs being paraded around as exceptional examples, humbly, privately, flag the corrosive implication on culture to the most senior leader who'll listen to you.

Speak up.

You deserve to be heard.

When you speak, it'll give others around you the courage to speak up as well. Smart people tend to run in packs.

That’s it. :)

A slight repetition: Reflect deeply on the impact of the 10 x 2 obsessions in your unique business environment. Then, distill down to a total of ten you’ll focus on in the next twelve months. Finally, put a start and expected end date for each item. If you get through the list, you would have contributed a step change to your company’s bottom-line, and discovered unexpected personal joy.

As always, it is your turn now.

If you had already identified obsessions for Analytics and/or Marketing for the next twelve months for yourself, what obsessions did you choose? I’m super curious. Are there a couple in my lists above that would be particularly impactful in your company? Some of my recommendations are quite straight-forward, what do you think get’s in the way of focusing on them?

Please share your obsessions, tips, culture-shifting strategies, and critique via comments below.

Thank you.

The post Deliver Step Change Impact: Marketing & Analytics Obsessions appeared first on Occam's Razor by Avinash Kaushik.

from SEO Tips https://www.kaushik.net/avinash/top-ten-profitable-marketing-analytics-obsessions/

[smartwebhostingblog]

Living In the Smartwatch Future: A Long-Term Review of the Apple Watch Series 3

New Post has been published on http://team77.com/living-in-the-smartwatch-future-a-long-term-review-of-the-apple-watch-series-3/

Living In the Smartwatch Future: A Long-Term Review of the Apple Watch Series 3

Apple will soon debut an updated Apple Watch with a thinner body and larger screen, if rumors are correct. By far, Apple’s smartwatch has been the category’s biggest seller, though perhaps not as big a hit as Wall Street had originally hoped when the watch premiered in 2015.

Every year when Apple unveils an updated watch, reporters, and analysts who have tried it for a week or two publish their reviews. Those reviews are valuable, but they fail to answer the critical question: Are smartwatches useful in over the long term in daily life?

The Samsung Gear Sport, Apple Watch Series 3, and Fitbit Versa.

For the past year, I’ve worn an Apple Watch Series 3, while occasionally also using Fitbit’s Versa and Ionic, and the Samsung Gear Sport. And while I’ve found several benefits, there remain some limitations with all of them.

The bottom line: Smartwatches are increasingly useful and should become even more so over the next few years.

Less is more

One way I tested the Apple Watch was fairly simple. For a week, I alternated between wearing my watch and not wearing it. In a paper notebook, I tried to jot down each time I looked at my phone screen or peeked at my watch. That drove me a little crazy, so I also noted each day the amount of time the iPhone recorded as “usage” in its battery settings section. On days when I wore my watch, I used my phone an average of 4 hours and 57 minutes, versus 5 hours and 21 minutes when I went without. It’s a modest difference, but one that could grow over time as watches become more useful.

Apple originally pitched its smartwatch as freeing users from having to check their iPhone screens as often. With growing concerns about phone addiction, social isolation, and excessive social networking, that benefit is more valid today than ever.

One reason I used my phone less was fairly obvious. When a notification appears on my watch, I usually do nothing immediately except read it. But when my phone buzzes with a notification, I pick it up and check not only the app that triggered the buzz, but whatever other random apps have the dreaded red circle badge indicating that there are unread messages or notices. And like everyone else, I’m also prone to get sucked into checking my Facebook feed, email, and other apps once I already have the phone in hand.

A healthy life

The Apple Watch and its rivals track a variety of biometric data, including heart rates, sleep cycles, and exercise activity. Some people say such tracking helped to save their lives. For me, collecting biometric data lets me see whether I’m leading a healthier life. I use an app called HeartWatch to see how exercise and medication affect my health between doctor’s appointments. Exercise tracking apps like Strava and Runkeeper work great on smartwatches, which means I don’t have to awkwardly pull out my phone while on a bike ride.

There are also apps like Round that remind me to take medications. I find that I’m more likely to take my pills after getting a notification on the watch than on my phone, which I don’t usually carry around the house with me in the early morning or after dinner.

One caveat: With battery life of about two days, the Apple Watch Series 3 is imperfect for sleep tracking. Fitbit’s watches, which have a battery life of five or more days on a single charge, do a better job and have a great built in app for sleep analysis. Apple Watch, in contrast, doesn’t include a sleep app. The free Sleep++, from developer Cross Forward Consulting, is basic and you have to go to the trouble of clicking it to tell it when you go to sleep and wake up. AutoSleep, a rival app from Tantsissa, is better but costs $3.

Game over

Another early touted benefit of smartwatches was the so-called gamification of fitness. By tracking data about exercise activity, the devices and apps can let users know how they are doing in ways that resemble video games. You set a record for calories burned in that last swim, the Apple Watch sometimes tells me. You have a streak of five days exercising for at least 30 minutes, keep it going one more day, it will prompt another time. The current software on the watch even awards digital “achievement badges” for personal bests or for winning weird mini-contests it sometimes offers, like burning a certain number of calories in a single month or reaching the daily stand up goal for many days in a row.

The triggers and tracking and badges seemed cute and motivating at first. But after a while, the buzz wore off and I barely notice them now. Keeping a streak alive seem less important than spending a little more time with my kids or meeting an important deadline at work.

Fashion forward

Watches have long been one of the only pieces of jewelry most men would wear and can add pizzaz to a woman’s ensemble, as well. Apple has taken the lead in helping make smartwatches into a fashion statement. The key is the easy mechanism that lets you change the bands on your Apple Watch in a few seconds with the press of a couple of buttons. Other smartwatches–and most regular watches–force you to use more fiddly, spring-loaded levers, or even break out a mini-screw driver (though Fitbit’s newest high-end fitness tracking band, the Charge 3, appears to have a very Apple-like band mechanism).

Apple has also frequently refreshed its band offerings with new colors, new materials, and new designs. Samsung and Fitbit are doing well in the band variety department lately, too. And there’s also a pretty thriving third-party market for bands. I definitely appreciate being able to dress up my watch with a fancy orange leather Hermes band my wife got me for a present one year, or have no fear of jumping in the pool with a rubber-like fluoroelastomer sport band. One knock on Apple is that it doesn’t allow third-party watch faces. Samsung and Fitbit users can take advantage of a multitude of different faces from other developers. Apple users can use any photo as a watch face, though, providing one option for personalization.

Contracting and expanding

I’ve mentioned several apps that I love using on my Apple (aapl) watch and the huge ecosystem of apps is a big strength. Apple has far more watch apps available than Fitbit (fit) and Samsung. But all is not well with the watch app ecosystem. Some highly desirable apps, like, say Spotify, aren’t available. Apple has made programming information available for outside developers, but Spotify, which has an app for Samsung’s watch, hasn’t yet released anything (perhaps due to competitive friction with Apple Music). And some Apple Watch apps from major companies like Slack and Instagram have been discontinued.

Part of that ebb and flow is the natural process of developers figuring out what kinds of apps people actually do and don’t want to use on their wrist versus on the phone. And with bigger watch screens and faster processors expected over the next few years, not to mention the spread of cellular-capable watches that don’t need a nearby phone to reach the Internet, I’d bet on all of the smartwatch ecosystems experiencing healthy growth.

[theinvinciblenoob]

This summer’s wedding season required me to buy a new suit. I vowed to be adventurous and buy a color I normally never would have considered. Alas, I opted for a little more movie-theater usher and a little less Jidenna. Had I known about it at the time, I probably would have used Eison Triple Thread, a company that specializes in creating made-to-order suits.

Working with someone to create a suit can be a hard enough task. You have to consider the occasion the suit is for, body type, taste and other relevant factors. And what other suit company or department store doesn’t already do that? To differentiate itself from the crowd, Eison Triple Thread launched FITS, a web application that creates tailored looks based on clients’ lifestyles and musical preferences.

Eison founder and CEO Julian Eison was the fly kid on the playground and says his parents instilled in him a sense of presentation and to be his best when he was out and about.

“In terms of style and color I was super deliberate about what I wore,” he says. “I was the kid who collected Jordans and wanted to be fashionable because I just cared. I think through that process, and as I grew, I just started to embrace it.”

After six years in private equity, where he says he was able to see tech’s flow from the buy side and the sell side, Eison decided to combine his love of fashion and interest in tech. In 2014, he launched Eison Triple Thread from the garage of his San Francisco home to try his hand at creating an alternative to suit-buying at conventional big-box department stores.

“When we first launched the business, it was about visualization,” Eison says. “How can you visualize your body and think about something going on your body that fits you well?”

But Eison Triple Thread isn’t the only suit company that wants to outfit its customers in sleek styles in a made-to-order fashion. The likes of Indochino, Bonobos and Stitch Fix, all of which came before Eison Triple Thread, ultimately have the same goal. So what’s a suit company do to strike a difference between its competitors? Why, integrate artificial intelligence and Spotify data, naturally.

“Music is at the core of a lot of everyday life; it knows no boundaries or color, and it reveals something about us that we may not know that we kind of project onto people,” Eison says. “So we’re trying to get to the core, the unadulterated piece, and that’s music, and it drives a lot of our decisions, selections, identities and moods.”

During the onboarding process, users first log in to the FITS system with their Spotify credentials and take a lifestyle quiz. Questions include in which industry you work, how you dress for work, what your work commute is, how you spend your free time and which word best describes you. Eison says they can start generating data from this basic information.

“We’ve turned that into a lifestyle quiz that aims to reveal as much about a person in terms of their fashion, their interests, their preferences and how they typically like things to fit. That goes into our analysis and allows us to home in on this fit and this style.”

[gallery size="medium" ids="1681262,1681261,1681263,1681264,1681265,1681260"]

While you’re busy thinking about yourself to the best of your ability, FITS is trolling Spotify through its API to gather data about your musical tastes: genre, when you tend to listen to music and for how long. The process from beginning to end takes only about 15 minutes — unless, like me, you have a hard time selecting just one word from a list of four to describe yourself. Reflective, intense, upbeat, energetic: I am all of these things.

Once you complete the quiz, the web app returns a list of “looks,” as Eison calls them, based on data gleaned from your best answers to these questions. The looks come from a collection of images that Eison and product director Dario Smith curate regularly from the internet based on styles they deem worthy. Eison tells me they currently have 3,000 images in their database and curate additional ones seasonally to kick back to customers on a regular basis.

They pull the metadata of photos, including color pairing, assumed cloth texture and other similar data, which the algorithm uses, Eison says. In the next release, he said the company will be able to identify skin tone for those who upload the required photos. In addition, the company uses available photo metadata to understand geography of fashion. When available, Eison says, they are able to gain insight into local fashion and trends to further tune the algorithm.

“If there are X amount of styles, we want to make sure we have representation,” Eison says. “We can aggregate all these images and then serve those periodically based on how important or relevant they are.”

For my part, I answered the questions while Spotify worked in the background to make sense of my musical predilections: showtunes (your Hamiltons, your Ragtimes, your Cabarets), Jidenna, Calle 13, selections from Moana (yeah, that’s right), Nathaniel Rateliff & the Night Sweats and a smattering of old R&B.

The result was a list of 25 photos of men of varying ages, races and sizes in a wide range of suits pulled from the Eison database (see five of them below). I was excited about most of them, although there were a few too many double-breasted ones for my liking. That’s on me, I suppose, but I don’t think that’s a look I can pull off. Or maybe that’s the point of a system like this: To present something to someone that he or she might not think they’d ever look good in or visualize themselves even wearing.

[gallery ids="1681254,1681255,1681256,1681257,1681258"]

Once you select the look you want, there might be further details to tend to, such as number and style of jacket buttons, button-hole color, the color and fabric of the jacket lining, waistband style on the pants and anything else you can possibly think of. One thing I could see in the future is the ability to place these looks on a picture of myself.

Once you make all of these very permanent decisions, you then have to be measured. Or measure yourself if you opted to do this at home. I was in the Eison studio, so Smith did the honors, measuring me in places I never thought needed to be measured. For instance, they noted posture, as well as the way my arms rest on the side of my body. Suddenly I realized why the clothes I’ve worn my entire adult life never fit me very well.

About two weeks later, you have a suit that you picked out not from a rack but one suggested for you based on your lifestyle and musical tastes. And it will fit only you. My suit fits. But because it’s tailored with my measurements, I’m not so surprised by that. The treat here is the unique application of Spotify and machine learning. Having the FITS system tell me to avoid buying a light gray suit is the permission I needed to step outside of my fashion comfort zone and don a look I most likely never would have otherwise. 

Not bad for a music-streaming platform and a little AI-style effort.

via TechCrunch

[deepfinds-blog]

This summer’s wedding season required me to buy a new suit. I vowed to be adventurous and buy a color I normally never would have considered. Alas, I opted for a little more movie-theater usher and a little less Jidenna. Had I known about it at the time, I probably would have used Eison Triple Thread, a company that specializes in creating made-to-order suits.

Working with someone to create a suit can be a hard enough task. You have to consider the occasion the suit is for, body type, taste and other relevant factors. And what other suit company or department store doesn’t already do that? To differentiate itself from the crowd, Eison Triple Thread launched FITS, a web application that creates tailored looks based on clients’ lifestyles and musical preferences.

Eison founder and CEO Julian Eison was the fly kid on the playground and says his parents instilled in him a sense of presentation and to be his best when he was out and about.

“In terms of style and color I was super deliberate about what I wore,” he says. “I was the kid who collected Jordans and wanted to be fashionable because I just cared. I think through that process, and as I grew, I just started to embrace it.”

After six years in private equity, where he says he was able to see tech’s flow from the buy side and the sell side, Eison decided to combine his love of fashion and interest in tech. In 2014, he launched Eison Triple Thread from the garage of his San Francisco home to try his hand at creating an alternative to suit-buying at conventional big-box department stores.

“When we first launched the business, it was about visualization,” Eison says. “How can you visualize your body and think about something going on your body that fits you well?”

But Eison Triple Thread isn’t the only suit company that wants to outfit its customers in sleek styles in a made-to-order fashion. The likes of Indochino, Bonobos and Stitch Fix, all of which came before Eison Triple Thread, ultimately have the same goal. So what’s a suit company do to strike a difference between its competitors? Why, integrate artificial intelligence and Spotify data, naturally.

“Music is at the core of a lot of everyday life; it knows no boundaries or color, and it reveals something about us that we may not know that we kind of project onto people,” Eison says. “So we’re trying to get to the core, the unadulterated piece, and that’s music, and it drives a lot of our decisions, selections, identities and moods.”

During the onboarding process, users first log in to the FITS system with their Spotify credentials and take a lifestyle quiz. Questions include in which industry you work, how you dress for work, what your work commute is, how you spend your free time and which word best describes you. Eison says they can start generating data from this basic information.

“We’ve turned that into a lifestyle quiz that aims to reveal as much about a person in terms of their fashion, their interests, their preferences and how they typically like things to fit. That goes into our analysis and allows us to home in on this fit and this style.”

While you’re busy thinking about yourself to the best of your ability, FITS is trolling Spotify through its API to gather data about your musical tastes: genre, when you tend to listen to music and for how long. The process from beginning to end takes only about 15 minutes — unless, like me, you have a hard time selecting just one word from a list of four to describe yourself. Reflective, intense, upbeat, energetic: I am all of these things.

Once you complete the quiz, the web app returns a list of “looks,” as Eison calls them, based on data gleaned from your best answers to these questions. The looks come from a collection of images that Eison and product director Dario Smith curate regularly from the internet based on styles they deem worthy. Eison tells me they currently have 3,000 images in their database and curate additional ones seasonally to kick back to customers on a regular basis.

They pull the metadata of photos, including color pairing, assumed cloth texture and other similar data, which the algorithm uses, Eison says. In the next release, he said the company will be able to identify skin tone for those who upload the required photos. In addition, the company uses available photo metadata to understand geography of fashion. When available, Eison says, they are able to gain insight into local fashion and trends to further tune the algorithm.

“If there are X amount of styles, we want to make sure we have representation,” Eison says. “We can aggregate all these images and then serve those periodically based on how important or relevant they are.”

For my part, I answered the questions while Spotify worked in the background to make sense of my musical predilections: showtunes (your Hamiltons, your Ragtimes, your Cabarets), Jidenna, Calle 13, selections from Moana (yeah, that’s right), Nathaniel Rateliff & the Night Sweats and a smattering of old R&B.

The result was a list of 25 photos of men of varying ages, races and sizes in a wide range of suits pulled from the Eison database (see five of them below). I was excited about most of them, although there were a few too many double-breasted ones for my liking. That’s on me, I suppose, but I don’t think that’s a look I can pull off. Or maybe that’s the point of a system like this: To present something to someone that he or she might not think they’d ever look good in or visualize themselves even wearing.

Once you select the look you want, there might be further details to tend to, such as number and style of jacket buttons, button-hole color, the color and fabric of the jacket lining, waistband style on the pants and anything else you can possibly think of. One thing I could see in the future is the ability to place these looks on a picture of myself.

Once you make all of these very permanent decisions, you then have to be measured. Or measure yourself if you opted to do this at home. I was in the Eison studio, so Smith did the honors, measuring me in places I never thought needed to be measured. For instance, they noted posture, as well as the way my arms rest on the side of my body. Suddenly I realized why the clothes I’ve worn my entire adult life never fit me very well.

About two weeks later, you have a suit that you picked out not from a rack but one suggested for you based on your lifestyle and musical tastes. And it will fit only you. My suit fits. But because it’s tailored with my measurements, I’m not so surprised by that. The treat here is the unique application of Spotify and machine learning. Having the FITS system tell me to avoid buying a light gray suit is the permission I needed to step outside of my fashion comfort zone and don a look I most likely never would have otherwise. 

Not bad for a music-streaming platform and a little AI-style effort.

Fashionably AI This summer’s wedding season required me to buy a new suit. I vowed to be adventurous and buy a color I normally never would have considered.