#but not making the subtitles more complicated than they need to be to accurately convey the audio feels pretty straightforward to me

[hellooo-one-and-all]

not particularly liking it when the subtitles on d20 get fancy with describing sounds makes me feel like such a buzzkill but also. subtitles should be accessible to the people who get the most use out of subtitles actually and some of these words and phrases are getting so fucking complicated

[thelaithlyworm]

Fic writer review, thank you to @animanightmate  for the tag ♥

how many works do you have on AO3?

TWO HUNDRED AND NINETY-THREE!!! (I shall have to do something special for the 300-versary.)

what’s your total AO3 word count?

595,085   Okay. So that’s, uh, a alot.

how many fandoms have you written for and what are they?

Uh, a little over 80? (Those fic exchanges and podfic prompts can really expand a lady’s list, yeah?) I was really big in The Musketeers for a while. The next biggest are Star Trek: Picard, and Nirvana In Fire, both of which a smaller fandoms, packed full of nice people. And I have a fair few of podfics in Good Omens.

what are your top 5 fics by kudos?

“Sleep of the Just”

“Flying Monkeys”

“Things Darcy Lewis Learned About S.H.I.E.L.D”

“Yellow Ducky Pyjamas”

“Paperwork Ninja”

all of which were written after the first Avengers movie and I was... enthused. MCU fandom is large enough that it drowns out all other stats.

do you respond to comments, why or why not?

Generally, yes. I like the feeling of community, it’s polite, (and I don’t nearly get so many that I have to make choices about ‘writing time’ vs. ‘responding to comments’ time).

what’s the fic you’ve written with the angstiest ending?

Now, technically that would be J’attendrai, which is original fic, written for an exchange, set in WWII France and, uh, I swear the giftee said they liked The Angst.

On the other hand, the end of The Lion and the Serpent, while more bittersweet than straight angst, spends 140,000 words dragging characters we care about through certain unavoidable moments of pain and some of those issues aren’t ever going to go away or be healed or brought to justice, so...

do you write crossovers? if so what is the craziest one you’ve written?

Sometimes. None of them are crazy, they are all perfectly reasonable given the context, and so I cannot answer the second part of this question.

have you ever received hate on a fic?

Not that I recall.

do you write smut? if so what kind?

Sometimes.

*scratches head*

I tend not to go into detail unless there’s some element of plot or character being worked through. Which means... if the characters involved have an uncomplicatedly happy time then it’s likely to be a Fade to Black. If I write the whole thing out, there’s generally a note of sadness or anxiety mixed in with the fun times.

have you ever had a fic stolen?

Not to my knowedge.

have you ever had a fic translated?

Yep. Every now and then a very courteous Russian asks for permission to translate a shorter work. (It’s very flattering.)

have you ever co-written a fic before?

Not a fic, though I have co-written other things.

what’s your all time favorite ship?

I don’t really do OTPs.

what’s a WIP that you want to finish but don’t think you ever will?

I decline to answer on the grounds I might incriminate myself.

what are your writing strengths?

Short, vivid scenes that convey a lot of sene]se of place and emotional nuance with a few sentences. Also, I think I’m pretty funny.

what are your writing weaknesses?

Action scenes! ARGH!! Plotting long forms.

what are your thoughts on writing dialogue in other languages in a fic?

Clarity is important. Something like, “Bonjour!” is likely to be understood by the average audience I write for, but long complicated sentences in other languages aren’t. So... how can I indicate what was just said in the surrounding text? Does it need to be in <other language> or can I paraphrase or use a translation convention? Subtitle? Foot notes? (Foot notes are clunky, and best avoided.)

Conversely, the odds of at least one native speaker (given the eclecticness of fandom) reading it are quite high - and nobody enjoys reading something clunky or ludicrous in their native tongue, which means more work for me trying to get it grammatically accurate.

In other words, I’m not going to use other languages verbatim unless they’re important to the work. I do sometimes try to write English sentences to mirror the grammar and phrasing, though, to get the feel.

what was the first fandom you wrote for?

The Hobbit, with a side of lore from The Lord of the Rings and The Silmarillion. I wrote about Belladonna Took before she was a popular self-insert character!

what’s your favorite fic you’ve written?

I Love All My Children Equally.

Thank you for the tag! ❤ I’m tagging @procrastinatorproject, @regionalpancake, @spinifex, @jazzfic and @evilasiangenius though do feel free to ignore this if you don’t want to do it, or answer it anyway, even if I haven’t tagged

[bngrc]

I spent my afternoon editing a song translation with the help of a native Chinese speaker. I’ve translated several songs from English into Chinese over the past year, and the editing process is always more tedious and complicated than I expect it to be.

People who are willing to offer help with translation generally know very little about songwriting. They know about translating written prose, or spoken dialogue.

When doing conventional translation, the main concern is accuracy. 

The translator tries to look for words and expressions that carry the same 1) meaning 2) connotation 3) degree of formality. Compromises will be made, of course. No translation can ever be completely accurate. But accuracy is the priority.

When translating song lyrics, the main concern is prosody. That is to say, the lyrics have to sound good. 

A song translator must keep in mind that they are writing a song first, and a translation second. If a lyric needs to be wailed in anguish, the song translator needs to pick words that contain the right vowel sounds for wailing, even if it means taking some liberties with translation accuracy. 

Subtitles must be translated on a sentence-by-sentence basis. The song translator can’t always think that way. They work on more of a verse-by-verse basis. 

Of course the song must convey the same general intention, but the song cannot be micromanaged. The song translator must work within a syllable limit, so they might throw out less important line to make space for a more nuanced interpretation of a more important lyric. 

So asking for help with a translation becomes an absurdly complicated process.

Because the person offering assistance might have a superior mastery of both languages, but they won’t understand the song translator’s priorities if they’ve never written a song before.

And the song translator will often need to spend a great deal of time not only explaining, but also justifying their priorities.

[cgiuniverse]

Content  Component

Here are the components of content which we will be discussed:

1.       TEXT

Definition:

In academic terms, a text is anything that conveys a set of meanings to the person who examines it. Texts are not limited to written materials, such as books, magazines, and newspapers. Those items are indeed texts—but so are movies, paintings, television shows, songs, political cartoons, online materials, advertisements, maps, works of art, and even rooms full of people. If we can look at something, explore it, find layers of meaning in it, and draw information and conclusions from it, we’re looking at a text.

 Strengths:

1. It develops writing creativity and spread the purpose of writing.

2. It can be used as subtitle of video so viewers can understand the message of video while the explanation in foreign languages.

3. Adds more information when we forget to mentioning some information on the videos and pictures.

4. Text helps deaf people when they are watching video.

5. Text or words have energy and power with the ability to help, to heal, to hinder, to hurt, to harm, to humiliate and to humble.

 Weaknesses:

1. If the sentences or words are too long, people tends lazy to read.

2. Easy to cause misunderstanding if there are typos and punctuation.

3. Sometimes the content of texts are not good, it can be destructive words which hurt others.

4. Some applications and social media platforms limit short messages can be post.

5. An explanation that is too complicated will misunderstand the reader.

  2.    PICTURE: designs or representations made in various ways (such as painting, drawing, or photography) drawing also becomes a very clear or explicit description to suggest a mental image or provide an accurate idea of something

 strengths:

1. Associated Thumbnail Image

2. Encourage Social Media Interest and Sharing

3. Support The Information Points

4.  Achieve an Emotional Connection

5. Convey Professionalism

 Weakness:

1. Licensing

You have to be careful when using stock photos to make sure you’re not using pictures in a way that overstep the boundaries of the license

2.Lack Authenticity

3. Anyone Can Use Similar Picture.

3   AUDIO content is any type of material or knowledge published that is absorbed by listening.

Strengths:

1.             In contrast to other electronic media, radio sets, tape recorders and cassette recorders are not costly in:

2.            With the support of battery packs, even without electrical radio tape / cassette recorders can be used

3.            These recorders will play back cassettes / tapes at the learner's convenience. That is to say, such materials can be used to replicate, drill, practice and demonstrate certain specific points of teaching.

4.            Radio sets, tape / cassette recorders are comparatively convenient and quite compact and can be conveniently used in different locations.Production cost of educational audio programmes is quite reasonable.

5.            Tapes / cassettes are generated in compliance with the educational needs and requirements of the individual learner groups.

Weaknesses:

(1) Audio programs are sound based only and do not have visuals. These structures can therefore be boring.

(2) Audio cassettes / tapes are typically produced locally, and even institutionally, so they often lose professional quality.

(3) In case of audio there is no scope for interaction and feedback. Hence these are one-sided/one-way communication and miss the personal touch.

(3) No space for contact and feedback exists for the audio. These are often one-sided / one-way communication and the personal touch is lacking.

 4. Video

Video : Visual multimedia source combining a series of images to create a moving image. The video transmits a signal to a computer and determines the order the image captures should be shown in. Videos usually have audio components that suit the images displayed on the screen.

strengths:  

1. The video can extract such a big information with limited time.

2. It can give best illustration or explanation to our audience about one complex information to make easy learning (e.g).

3. allow us to record behavior in its situational context, allow for reflection, informants, coding, and use of the behavior or situation for illustration.

4. Video recordings are being used more and more in educational research.

5.  to improve teaching, it is essential to understand how video-aided reflection influences teacher change.

 Weaknesses

1. High cost  

2. Need teamwork in making the videos which are takes many times.

3. Need a special equipment in presentment.  

4. Consist of advertisements inside videos, make an audience unsatisfied

5. Animation is the creation of art in motion. Animation is the act of drawing movement to have a meaning and a message. The aim of animation is to make an illustration of montionless object to become more alive.

Example of animation:

Stop motion animation is creating an effect of moving objects from motionless objects by taking one frame at a time and combining all the frames to make a movement.

Strength of animation:

- It catches the attention of the viewers

- It creates a movement for motionless objects

- It can contain a message more than a picture can have

- It brings a topic to life

- It doesn't take a big file size

 Weakness of animation:

- Takes a lot of time and effort to take all the frames to make one animation

- Requires skills to operate the animation software

- Limited to edit because of the small size

- Can cost a lot of budget

- Can be distracting if it is presented too many in one page.

   Sources:

https://www.teach-ict.com/gcse_new/software/animation/miniweb/pg10.htm.

https://www.bloopanimation.com/types-of-animation/

(.https://scholar.google.com/scholar?hl=en&as_sdt=0,5&q=understanding+of+video+strength+and+weaknesses#d=gs_qabs&u=%23p%3DfRbZVAsZFggJ)

(https://scholar.google.com/scholar?hl=en&as_sdt=0,5&q=understanding+of+video+strength+and+weaknesses#d=gs_qabs&u=%23p%3D0ZwFH3_mTEQJ).

(https://scholar.google.com/scholar?start=20&q=understanding+of+video+strength+and+weaknesses&hl=en&as_sdt=0,5#d=gs_qabs&u=%23p%3DScFvhyJM0n8J)

(https://id.techinasia.com/talk/kelebihan-dan-kekurangan-menggunakan-video-marketing).

(http://su28he12rm19an90.blogspot.com/2015/09/kelebihan-dan-kekurangan-media-video.html?m=1)

(https://masbos.com/kelebihan-dan-kelemahan-televisi/).

http://www.advertisecolumbus.com/blog/pros-and-cons-of-stock-photos-for-business

https://www.socialmediatoday.com/content/10-benefits-using-images-blogs

https://openoregon.pressbooks.pub/wrd/chapter/what-is-a-text/

https://www.google.com/amp/s/m.huffpost.com/us/entry/6324786/amp

http://www.preservearticles.com/education/what-are-the-major-strengths-and-weaknesses-of-using-audio-programmes-in-education/16508

https://searchcustomerexperience.techtarget.com/definition/audio-content

[tainghekhongdaycomvn]

PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday

PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday

Posted by Lea-Pica

If you find your presentations are often met with a lukewarm reception, it's a sure sign it's time for you to invest in your data storytelling. By following a few smart rules, a structured approach to data visualization could make all the difference in how stakeholders receive and act upon your insights. In this edition of Whiteboard Friday, we're thrilled to welcome data viz expert Lea Pica to share her strategic methodology for creating highly effective charts.

Click on the whiteboard image above to open a high-resolution version in a new tab!

Video Transcription

Hello, Moz fans. Welcome to another edition of Whiteboard Friday. I'm here to talk to you this week about a very hot topic in the digital marketing space. So my name is Lea Pica, and I am a data storytelling trainer, coach, speaker, blogger, and podcaster at LeaPica.com.

I want to tell you a little story. So as 12 years I spent as a digital analyst and SEM, I used to present insights a lot, but nothing ever happened as a result of it. People fell asleep or never responded. No action was being taken. So I decided to figure out what was happening, and I learned all these great tricks for doing it.

What I learned in my journey is that effective data visualization communicates a story quickly, clearly, accurately, and ethically, and it had really four main goals — to inform decisions, to inspire action, to galvanize people, and most importantly to communicate the value of the work that you do.

Now, there are lots of things you can do, but I was struggling to find one specific process that was going to help me get from what I was trying to communicate to getting people to act on it. So I developed my own methodology. It's called the PICA Protocol, and it's a visualization prescription for impactful data storytelling. What I like about this protocol is that it's practical, approachable. It's not complicated. It's prescriptive, and it's repeatable. I believe it's going to get you where you need to go every time.

So let's say one of your managers, clients, stakeholders is asking you for something like, "What are our most successful keyword groups?" Something delightfully vague like that. Now, before you jump into your data visualization platform and start dropping charts like it's hot, I want you to take a step back and start with the first step in the process, which is P for purpose.

P for Purpose

So I found that every great data visualization started with a very focused question or questions.

Why do you exist? Get philosophical with it.

What need of my audience are you meeting?

What decisions are you going to inform?

These questions help you get really focused about what you're going to present and avoid the sort of needle in a haystack approach to seeing what might stick.

So the answers to these questions are going to help you make an important decision, to choose an appropriate chart type for the message that you're trying to convey. Some of the ways you want to do that — I hear you guys are like into keywords a little bit — you want to listen for the keywords of what people are asking you for. So in this case, we have "most successful." Okay, that indicates a comparison. Different types or campaigns or groups, those are categories. So it sounds like what we're going for is a categorical comparison. There are other kinds of keywords you can look for, like changing over time, how this affects that. Answers or opinions. All of those are going to help you determine your most appropriate visual.

Now, in this case, we have a categorical comparison, so I always go back to basics. It's an oldie but goodie, but we're going to do the tried-and-true bar chart. It's universally understood and doesn't have a learning curve. What I would not recommend are pie charts. No, no, no. Unless you only have two segments in your visual and one is unmistakably larger than the other, pie charts are not your best choice for communicating categorical comparison, composition, or ranking.

I for Insight

So we have our choice. We're now going to move on to the next step in the methodology, which is I for insight. So an insight is something that gives a person a capacity to understand something quickly, accurately, and intuitively. Think of those criteria.

So here, does my display surface the story and answer these questions intuitively? That's our criteria. The components of that are:

Layout and orientation. So how is the chart configured? Very often we'll use vertical bar charts for categorical comparison, but that will end up having diagonal labels if they're really long, and unless your audience walks around like this all the time, it's going to be confusing because that would be weird. So you want to make sure it's oriented well.

Labeling. In the case of bars, I always prefer to label each bar directly rather than relying on just an axis, because then their eyes aren't jumping from bar to axis to bar to axis and they're paying more attention to you. That's also for line charts. Very often I'll label a line with a maximum, a minimum, and maybe the most important data point.

Interpretation of the data and where we're placing it, the location.

So our interpretation, is it objective or is it subjective? So subjective words are like better or worse or stupid or awesome. Those are opinions. But objective words are higher, lower, most efficient, least efficient. So you really want your observations to be objective.

Have you presented it ethically? Or have you manipulated the view in a way that isn't telling a really ethical picture, like adjusting a bar axis above zero, which is a no-no? But you can do that with a line graph in certain cases. So look for those nuances. You want to basically ask yourself, "Would I be able to uphold this visual in a court of law or sleep at night?"

Location of that insight. So very often we'll put our insights, our interpretation down here or in really tiny letters up here. Then up here we'll put big letters saying this is sales, my keyword category. No. What we want to do is we want to put our interpretation up here. This top area is the most important real estate on your visual. That's where their eyes are going to look first. So think of this like a BuzzFeed headline for your visual. What do you want them to take away? You can always put what the chart is here in a little subtitle.

Make recommendations. Because that's what a really powerful visual is going to do.

I always suggest having two recommendations at least, because this way you're empowering your audience with a choice. This way you can actually be subjective. That is okay in this case, because that's your unique subject matter expertise.

Are your recommendations accountable to specific people? Are they feasible?

What's the cost of not acting on your recommendations? Put some urgency behind it. So I like to put my recommendations in a little box or callout on the side here so it's really clear after I've presented my facts.

C for Context

The next step in the methodology is C for context. What this is saying is, "Do I have all the data points I need to paint a complete picture, or is there more to this story?" So some additional lenses you might find useful are past period comparison, targets or benchmarks are useful, segmentation, things like geography, mobile device. Or what are the typical questions or arguments that your audience has when you present data? They can be super value contextual points.

In this case, I might decide that while they care about the number of sales, because that's most successful to them, I care about the keywords "conversion rates." So I'm going to add a second bar chart here like this, and I'm going to see there's a different story that's popping out here now.

Now, this is where your data storytelling really comes into play. This particular strategy is called a table lens or a side-by-side bar chart. It's what I recommend if you want to combine two categorical metrics together.

A for Aesthetics

Now, the last step in the methodology is A for aesthetics. Aesthetics are how things look. So it's not about making it look pretty. No, it's asking, "Does my viz comply with brain best practices of how we absorb information?"

1. Decrease visual noise

So the first step in doing that is we want to decrease visual noise, because that creates a lot of tension. So decreasing noise will increase the chance of a happy brain.

Now, I'm a crunchy granola hippie, so I love to detox every day. I've developed a data visualization detox that entails removing things like grid lines, borders, axis lines, line markers, and backgrounds. Get all of that junk out of there, really clean up. You can align everything to the left to make sure that the brain is following things properly down. Don't center everything.

2. Use uniform colors (plus one standout color for emphasis)

Now, you'll notice that most of my bars here have a uniform color — simple black. I like to color everything one color, because then I'll use a separate, standout color, like this blue, to strategically emphasize my key message. You might notice that I did that throughout this step for the words that I want you to pick out. That's why I colored these particular bars, because this feels like the story to me, because that is the storytelling part of this message.

Notice that I also colored the category in my observation to create a connective tissue between these two items. So using color intentionally means things like using green for good and red for bad, not arbitrarily, and then maybe blue for what's important.

3. Source your data

Then finally, you always want to source your data. That increases the trust. So you want to put your platform and your date range. Really simple.

So this is the anatomy of an awesome data viz. I've adapted it from a great book called "Good Charts" by my friend, Scott Berinato. What I have found that by using this protocol, you're going to end up with these wonderful, raving fans who are going to love your work and understand your value. I included a little kitty fan because I can. It's my Whiteboard Friday.

So that is the protocol. I actually have included a free gift for you today. If you click the link at the end of this post, you'll be able to sign up for a Chart Detox Checklist, a full printable PICA Protocol prescription and a Chart Choosing Guide.

Get the PICA Protocol prescription

I would actually love to hear from you. What are the kinds of struggles that you have in presenting your insights to stakeholders, where you just feel like they're not getting the value of what you're doing? I'd love to hear any questions you have about the methodology as well.

So thank you for watching this edition of Whiteboard Friday. I hope you enjoyed it. We'll see you next week, and please remember to viz responsibly, my friends. Namaste.

Video transcription by Speechpad.com

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Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - 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Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl Bạn có thể xem thêm địa chỉ mua tai nghe không dây tại đây https://ift.tt/2mb4VST

[golehyas]

PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday

Posted by Lea-Pica

If you find your presentations are often met with a lukewarm reception, it's a sure sign it's time for you to invest in your data storytelling. By following a few smart rules, a structured approach to data visualization could make all the difference in how stakeholders receive and act upon your insights. In this edition of Whiteboard Friday, we're thrilled to welcome data viz expert Lea Pica to share her strategic methodology for creating highly effective charts.

Click on the whiteboard image above to open a high-resolution version in a new tab!

Video Transcription

Hello, Moz fans. Welcome to another edition of Whiteboard Friday. I'm here to talk to you this week about a very hot topic in the digital marketing space. So my name is Lea Pica, and I am a data storytelling trainer, coach, speaker, blogger, and podcaster at LeaPica.com.

I want to tell you a little story. So as 12 years I spent as a digital analyst and SEM, I used to present insights a lot, but nothing ever happened as a result of it. People fell asleep or never responded. No action was being taken. So I decided to figure out what was happening, and I learned all these great tricks for doing it.

What I learned in my journey is that effective data visualization communicates a story quickly, clearly, accurately, and ethically, and it had really four main goals - to inform decisions, to inspire action, to galvanize people, and most importantly to communicate the value of the work that you do.

Now, there are lots of things you can do, but I was struggling to find one specific process that was going to help me get from what I was trying to communicate to getting people to act on it. So I developed my own methodology. It's called the PICA Protocol, and it's a visualization prescription for impactful data storytelling. What I like about this protocol is that it's practical, approachable. It's not complicated. It's prescriptive, and it's repeatable. I believe it's going to get you where you need to go every time.

So let's say one of your managers, clients, stakeholders is asking you for something like, "What are our most successful keyword groups?" Something delightfully vague like that. Now, before you jump into your data visualization platform and start dropping charts like it's hot, I want you to take a step back and start with the first step in the process, which is P for purpose.

P for Purpose

So I found that every great data visualization started with a very focused question or questions.

Why do you exist? Get philosophical with it.

What need of my audience are you meeting?

What decisions are you going to inform?

These questions help you get really focused about what you're going to present and avoid the sort of needle in a haystack approach to seeing what might stick.

So the answers to these questions are going to help you make an important decision, to choose an appropriate chart type for the message that you're trying to convey. Some of the ways you want to do that - I hear you guys are like into keywords a little bit - you want to listen for the keywords of what people are asking you for. So in this case, we have "most successful." Okay, that indicates a comparison. Different types or campaigns or groups, those are categories. So it sounds like what we're going for is a categorical comparison. There are other kinds of keywords you can look for, like changing over time, how this affects that. Answers or opinions. All of those are going to help you determine your most appropriate visual.

Now, in this case, we have a categorical comparison, so I always go back to basics. It's an oldie but goodie, but we're going to do the tried-and-true bar chart. It's universally understood and doesn't have a learning curve. What I would not recommend are pie charts. No, no, no. Unless you only have two segments in your visual and one is unmistakably larger than the other, pie charts are not your best choice for communicating categorical comparison, composition, or ranking.

I for Insight

So we have our choice. We're now going to move on to the next step in the methodology, which is I for insight. So an insight is something that gives a person a capacity to understand something quickly, accurately, and intuitively. Think of those criteria.

So here, does my display surface the story and answer these questions intuitively? That's our criteria. The components of that are:

Layout and orientation. So how is the chart configured? Very often we'll use vertical bar charts for categorical comparison, but that will end up having diagonal labels if they're really long, and unless your audience walks around like this all the time, it's going to be confusing because that would be weird. So you want to make sure it's oriented well.

Labeling. In the case of bars, I always prefer to label each bar directly rather than relying on just an axis, because then their eyes aren't jumping from bar to axis to bar to axis and they're paying more attention to you. That's also for line charts. Very often I'll label a line with a maximum, a minimum, and maybe the most important data point.

Interpretation of the data and where we're placing it, the location.

So our interpretation, is it objective or is it subjective? So subjective words are like better or worse or stupid or awesome. Those are opinions. But objective words are higher, lower, most efficient, least efficient. So you really want your observations to be objective.

Have you presented it ethically? Or have you manipulated the view in a way that isn't telling a really ethical picture, like adjusting a bar axis above zero, which is a no-no? But you can do that with a line graph in certain cases. So look for those nuances. You want to basically ask yourself, "Would I be able to uphold this visual in a court of law or sleep at night?"

Location of that insight. So very often we'll put our insights, our interpretation down here or in really tiny letters up here. Then up here we'll put big letters saying this is sales, my keyword category. No. What we want to do is we want to put our interpretation up here. This top area is the most important real estate on your visual. That's where their eyes are going to look first. So think of this like a BuzzFeed headline for your visual. What do you want them to take away? You can always put what the chart is here in a little subtitle.

Make recommendations. Because that's what a really powerful visual is going to do.

I always suggest having two recommendations at least, because this way you're empowering your audience with a choice. This way you can actually be subjective. That is okay in this case, because that's your unique subject matter expertise.

Are your recommendations accountable to specific people? Are they feasible?

What's the cost of not acting on your recommendations? Put some urgency behind it. So I like to put my recommendations in a little box or callout on the side here so it's really clear after I've presented my facts.

C for Context

The next step in the methodology is C for context. What this is saying is, "Do I have all the data points I need to paint a complete picture, or is there more to this story?" So some additional lenses you might find useful are past period comparison, targets or benchmarks are useful, segmentation, things like geography, mobile device. Or what are the typical questions or arguments that your audience has when you present data? They can be super value contextual points.

In this case, I might decide that while they care about the number of sales, because that's most successful to them, I care about the keywords "conversion rates." So I'm going to add a second bar chart here like this, and I'm going to see there's a different story that's popping out here now.

Now, this is where your data storytelling really comes into play. This particular strategy is called a table lens or a side-by-side bar chart. It's what I recommend if you want to combine two categorical metrics together.

A for Aesthetics

Now, the last step in the methodology is A for aesthetics. Aesthetics are how things look. So it's not about making it look pretty. No, it's asking, "Does my viz comply with brain best practices of how we absorb information?"

1. Decrease visual noise

So the first step in doing that is we want to decrease visual noise, because that creates a lot of tension. So decreasing noise will increase the chance of a happy brain.

Now, I'm a crunchy granola hippie, so I love to detox every day. I've developed a data visualization detox that entails removing things like grid lines, borders, axis lines, line markers, and backgrounds. Get all of that junk out of there, really clean up. You can align everything to the left to make sure that the brain is following things properly down. Don't center everything.

2. Use uniform colors (plus one standout color for emphasis)

Now, you'll notice that most of my bars here have a uniform color - simple black. I like to color everything one color, because then I'll use a separate, standout color, like this blue, to strategically emphasize my key message. You might notice that I did that throughout this step for the words that I want you to pick out. That's why I colored these particular bars, because this feels like the story to me, because that is the storytelling part of this message.

Notice that I also colored the category in my observation to create a connective tissue between these two items. So using color intentionally means things like using green for good and red for bad, not arbitrarily, and then maybe blue for what's important.

3. Source your data

Then finally, you always want to source your data. That increases the trust. So you want to put your platform and your date range. Really simple.

So this is the anatomy of an awesome data viz. I've adapted it from a great book called "Good Charts" by my friend, Scott Berinato. What I have found that by using this protocol, you're going to end up with these wonderful, raving fans who are going to love your work and understand your value. I included a little kitty fan because I can. It's my Whiteboard Friday.

So that is the protocol. I actually have included a free gift for you today. If you click the link at the end of this post, you'll be able to sign up for a Chart Detox Checklist, a full printable PICA Protocol prescription and a Chart Choosing Guide.

Get the PICA Protocol prescription

I would actually love to hear from you. What are the kinds of struggles that you have in presenting your insights to stakeholders, where you just feel like they're not getting the value of what you're doing? I'd love to hear any questions you have about the methodology as well.

So thank you for watching this edition of Whiteboard Friday. I hope you enjoyed it. We'll see you next week, and please remember to viz responsibly, my friends. Namaste.

Video transcription by Speechpad.com

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don't have time to hunt down but want to read!

[bloodyslytherxn-blog]

PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday

Posted by Lea-Pica

If you find your presentations are often met with a lukewarm reception, it's a sure sign it's time for you to invest in your data storytelling. By following a few smart rules, a structured approach to data visualization could make all the difference in how stakeholders receive and act upon your insights. In this edition of Whiteboard Friday, we're thrilled to welcome data viz expert Lea Pica to share her strategic methodology for creating highly effective charts.

Click on the whiteboard image above to open a high-resolution version in a new tab!

Video Transcription

Hello, Moz fans. Welcome to another edition of Whiteboard Friday. I'm here to talk to you this week about a very hot topic in the digital marketing space. So my name is Lea Pica, and I am a data storytelling trainer, coach, speaker, blogger, and podcaster at LeaPica.com.

I want to tell you a little story. So as 12 years I spent as a digital analyst and SEM, I used to present insights a lot, but nothing ever happened as a result of it. People fell asleep or never responded. No action was being taken. So I decided to figure out what was happening, and I learned all these great tricks for doing it.

What I learned in my journey is that effective data visualization communicates a story quickly, clearly, accurately, and ethically, and it had really four main goals - to inform decisions, to inspire action, to galvanize people, and most importantly to communicate the value of the work that you do.

Now, there are lots of things you can do, but I was struggling to find one specific process that was going to help me get from what I was trying to communicate to getting people to act on it. So I developed my own methodology. It's called the PICA Protocol, and it's a visualization prescription for impactful data storytelling. What I like about this protocol is that it's practical, approachable. It's not complicated. It's prescriptive, and it's repeatable. I believe it's going to get you where you need to go every time.

So let's say one of your managers, clients, stakeholders is asking you for something like, "What are our most successful keyword groups?" Something delightfully vague like that. Now, before you jump into your data visualization platform and start dropping charts like it's hot, I want you to take a step back and start with the first step in the process, which is P for purpose.

P for Purpose

So I found that every great data visualization started with a very focused question or questions.

Why do you exist? Get philosophical with it.

What need of my audience are you meeting?

What decisions are you going to inform?

These questions help you get really focused about what you're going to present and avoid the sort of needle in a haystack approach to seeing what might stick.

So the answers to these questions are going to help you make an important decision, to choose an appropriate chart type for the message that you're trying to convey. Some of the ways you want to do that - I hear you guys are like into keywords a little bit - you want to listen for the keywords of what people are asking you for. So in this case, we have "most successful." Okay, that indicates a comparison. Different types or campaigns or groups, those are categories. So it sounds like what we're going for is a categorical comparison. There are other kinds of keywords you can look for, like changing over time, how this affects that. Answers or opinions. All of those are going to help you determine your most appropriate visual.

Now, in this case, we have a categorical comparison, so I always go back to basics. It's an oldie but goodie, but we're going to do the tried-and-true bar chart. It's universally understood and doesn't have a learning curve. What I would not recommend are pie charts. No, no, no. Unless you only have two segments in your visual and one is unmistakably larger than the other, pie charts are not your best choice for communicating categorical comparison, composition, or ranking.

I for Insight

So we have our choice. We're now going to move on to the next step in the methodology, which is I for insight. So an insight is something that gives a person a capacity to understand something quickly, accurately, and intuitively. Think of those criteria.

So here, does my display surface the story and answer these questions intuitively? That's our criteria. The components of that are:

Layout and orientation. So how is the chart configured? Very often we'll use vertical bar charts for categorical comparison, but that will end up having diagonal labels if they're really long, and unless your audience walks around like this all the time, it's going to be confusing because that would be weird. So you want to make sure it's oriented well.

Labeling. In the case of bars, I always prefer to label each bar directly rather than relying on just an axis, because then their eyes aren't jumping from bar to axis to bar to axis and they're paying more attention to you. That's also for line charts. Very often I'll label a line with a maximum, a minimum, and maybe the most important data point.

Interpretation of the data and where we're placing it, the location.

So our interpretation, is it objective or is it subjective? So subjective words are like better or worse or stupid or awesome. Those are opinions. But objective words are higher, lower, most efficient, least efficient. So you really want your observations to be objective.

Have you presented it ethically? Or have you manipulated the view in a way that isn't telling a really ethical picture, like adjusting a bar axis above zero, which is a no-no? But you can do that with a line graph in certain cases. So look for those nuances. You want to basically ask yourself, "Would I be able to uphold this visual in a court of law or sleep at night?"

Location of that insight. So very often we'll put our insights, our interpretation down here or in really tiny letters up here. Then up here we'll put big letters saying this is sales, my keyword category. No. What we want to do is we want to put our interpretation up here. This top area is the most important real estate on your visual. That's where their eyes are going to look first. So think of this like a BuzzFeed headline for your visual. What do you want them to take away? You can always put what the chart is here in a little subtitle.

Make recommendations. Because that's what a really powerful visual is going to do.

I always suggest having two recommendations at least, because this way you're empowering your audience with a choice. This way you can actually be subjective. That is okay in this case, because that's your unique subject matter expertise.

Are your recommendations accountable to specific people? Are they feasible?

What's the cost of not acting on your recommendations? Put some urgency behind it. So I like to put my recommendations in a little box or callout on the side here so it's really clear after I've presented my facts.

C for Context

The next step in the methodology is C for context. What this is saying is, "Do I have all the data points I need to paint a complete picture, or is there more to this story?" So some additional lenses you might find useful are past period comparison, targets or benchmarks are useful, segmentation, things like geography, mobile device. Or what are the typical questions or arguments that your audience has when you present data? They can be super value contextual points.

In this case, I might decide that while they care about the number of sales, because that's most successful to them, I care about the keywords "conversion rates." So I'm going to add a second bar chart here like this, and I'm going to see there's a different story that's popping out here now.

Now, this is where your data storytelling really comes into play. This particular strategy is called a table lens or a side-by-side bar chart. It's what I recommend if you want to combine two categorical metrics together.

A for Aesthetics

Now, the last step in the methodology is A for aesthetics. Aesthetics are how things look. So it's not about making it look pretty. No, it's asking, "Does my viz comply with brain best practices of how we absorb information?"

1. Decrease visual noise

So the first step in doing that is we want to decrease visual noise, because that creates a lot of tension. So decreasing noise will increase the chance of a happy brain.

Now, I'm a crunchy granola hippie, so I love to detox every day. I've developed a data visualization detox that entails removing things like grid lines, borders, axis lines, line markers, and backgrounds. Get all of that junk out of there, really clean up. You can align everything to the left to make sure that the brain is following things properly down. Don't center everything.

2. Use uniform colors (plus one standout color for emphasis)

Now, you'll notice that most of my bars here have a uniform color - simple black. I like to color everything one color, because then I'll use a separate, standout color, like this blue, to strategically emphasize my key message. You might notice that I did that throughout this step for the words that I want you to pick out. That's why I colored these particular bars, because this feels like the story to me, because that is the storytelling part of this message.

Notice that I also colored the category in my observation to create a connective tissue between these two items. So using color intentionally means things like using green for good and red for bad, not arbitrarily, and then maybe blue for what's important.

3. Source your data

Then finally, you always want to source your data. That increases the trust. So you want to put your platform and your date range. Really simple.

So this is the anatomy of an awesome data viz. I've adapted it from a great book called "Good Charts" by my friend, Scott Berinato. What I have found that by using this protocol, you're going to end up with these wonderful, raving fans who are going to love your work and understand your value. I included a little kitty fan because I can. It's my Whiteboard Friday.

So that is the protocol. I actually have included a free gift for you today. If you click the link at the end of this post, you'll be able to sign up for a Chart Detox Checklist, a full printable PICA Protocol prescription and a Chart Choosing Guide.

Get the PICA Protocol prescription

I would actually love to hear from you. What are the kinds of struggles that you have in presenting your insights to stakeholders, where you just feel like they're not getting the value of what you're doing? I'd love to hear any questions you have about the methodology as well.

So thank you for watching this edition of Whiteboard Friday. I hope you enjoyed it. We'll see you next week, and please remember to viz responsibly, my friends. Namaste.

Video transcription by Speechpad.com

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don't have time to hunt down but want to read!

[kunst-in-verantwortung-blog1]

PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday

Posted by Lea-Pica

If you find your presentations are often met with a lukewarm reception, it's a sure sign it's time for you to invest in your data storytelling. By following a few smart rules, a structured approach to data visualization could make all the difference in how stakeholders receive and act upon your insights. In this edition of Whiteboard Friday, we're thrilled to welcome data viz expert Lea Pica to share her strategic methodology for creating highly effective charts.

Click on the whiteboard image above to open a high-resolution version in a new tab!

Video Transcription

Hello, Moz fans. Welcome to another edition of Whiteboard Friday. I'm here to talk to you this week about a very hot topic in the digital marketing space. So my name is Lea Pica, and I am a data storytelling trainer, coach, speaker, blogger, and podcaster at LeaPica.com.

I want to tell you a little story. So as 12 years I spent as a digital analyst and SEM, I used to present insights a lot, but nothing ever happened as a result of it. People fell asleep or never responded. No action was being taken. So I decided to figure out what was happening, and I learned all these great tricks for doing it.

What I learned in my journey is that effective data visualization communicates a story quickly, clearly, accurately, and ethically, and it had really four main goals - to inform decisions, to inspire action, to galvanize people, and most importantly to communicate the value of the work that you do.

Now, there are lots of things you can do, but I was struggling to find one specific process that was going to help me get from what I was trying to communicate to getting people to act on it. So I developed my own methodology. It's called the PICA Protocol, and it's a visualization prescription for impactful data storytelling. What I like about this protocol is that it's practical, approachable. It's not complicated. It's prescriptive, and it's repeatable. I believe it's going to get you where you need to go every time.

So let's say one of your managers, clients, stakeholders is asking you for something like, "What are our most successful keyword groups?" Something delightfully vague like that. Now, before you jump into your data visualization platform and start dropping charts like it's hot, I want you to take a step back and start with the first step in the process, which is P for purpose.

P for Purpose

So I found that every great data visualization started with a very focused question or questions.

Why do you exist? Get philosophical with it.

What need of my audience are you meeting?

What decisions are you going to inform?

These questions help you get really focused about what you're going to present and avoid the sort of needle in a haystack approach to seeing what might stick.

So the answers to these questions are going to help you make an important decision, to choose an appropriate chart type for the message that you're trying to convey. Some of the ways you want to do that - I hear you guys are like into keywords a little bit - you want to listen for the keywords of what people are asking you for. So in this case, we have "most successful." Okay, that indicates a comparison. Different types or campaigns or groups, those are categories. So it sounds like what we're going for is a categorical comparison. There are other kinds of keywords you can look for, like changing over time, how this affects that. Answers or opinions. All of those are going to help you determine your most appropriate visual.

Now, in this case, we have a categorical comparison, so I always go back to basics. It's an oldie but goodie, but we're going to do the tried-and-true bar chart. It's universally understood and doesn't have a learning curve. What I would not recommend are pie charts. No, no, no. Unless you only have two segments in your visual and one is unmistakably larger than the other, pie charts are not your best choice for communicating categorical comparison, composition, or ranking.

I for Insight

So we have our choice. We're now going to move on to the next step in the methodology, which is I for insight. So an insight is something that gives a person a capacity to understand something quickly, accurately, and intuitively. Think of those criteria.

So here, does my display surface the story and answer these questions intuitively? That's our criteria. The components of that are:

Layout and orientation. So how is the chart configured? Very often we'll use vertical bar charts for categorical comparison, but that will end up having diagonal labels if they're really long, and unless your audience walks around like this all the time, it's going to be confusing because that would be weird. So you want to make sure it's oriented well.

Labeling. In the case of bars, I always prefer to label each bar directly rather than relying on just an axis, because then their eyes aren't jumping from bar to axis to bar to axis and they're paying more attention to you. That's also for line charts. Very often I'll label a line with a maximum, a minimum, and maybe the most important data point.

Interpretation of the data and where we're placing it, the location.

So our interpretation, is it objective or is it subjective? So subjective words are like better or worse or stupid or awesome. Those are opinions. But objective words are higher, lower, most efficient, least efficient. So you really want your observations to be objective.

Have you presented it ethically? Or have you manipulated the view in a way that isn't telling a really ethical picture, like adjusting a bar axis above zero, which is a no-no? But you can do that with a line graph in certain cases. So look for those nuances. You want to basically ask yourself, "Would I be able to uphold this visual in a court of law or sleep at night?"

Location of that insight. So very often we'll put our insights, our interpretation down here or in really tiny letters up here. Then up here we'll put big letters saying this is sales, my keyword category. No. What we want to do is we want to put our interpretation up here. This top area is the most important real estate on your visual. That's where their eyes are going to look first. So think of this like a BuzzFeed headline for your visual. What do you want them to take away? You can always put what the chart is here in a little subtitle.

Make recommendations. Because that's what a really powerful visual is going to do.

I always suggest having two recommendations at least, because this way you're empowering your audience with a choice. This way you can actually be subjective. That is okay in this case, because that's your unique subject matter expertise.

Are your recommendations accountable to specific people? Are they feasible?

What's the cost of not acting on your recommendations? Put some urgency behind it. So I like to put my recommendations in a little box or callout on the side here so it's really clear after I've presented my facts.

C for Context

The next step in the methodology is C for context. What this is saying is, "Do I have all the data points I need to paint a complete picture, or is there more to this story?" So some additional lenses you might find useful are past period comparison, targets or benchmarks are useful, segmentation, things like geography, mobile device. Or what are the typical questions or arguments that your audience has when you present data? They can be super value contextual points.

In this case, I might decide that while they care about the number of sales, because that's most successful to them, I care about the keywords "conversion rates." So I'm going to add a second bar chart here like this, and I'm going to see there's a different story that's popping out here now.

Now, this is where your data storytelling really comes into play. This particular strategy is called a table lens or a side-by-side bar chart. It's what I recommend if you want to combine two categorical metrics together.

A for Aesthetics

Now, the last step in the methodology is A for aesthetics. Aesthetics are how things look. So it's not about making it look pretty. No, it's asking, "Does my viz comply with brain best practices of how we absorb information?"

1. Decrease visual noise

So the first step in doing that is we want to decrease visual noise, because that creates a lot of tension. So decreasing noise will increase the chance of a happy brain.

Now, I'm a crunchy granola hippie, so I love to detox every day. I've developed a data visualization detox that entails removing things like grid lines, borders, axis lines, line markers, and backgrounds. Get all of that junk out of there, really clean up. You can align everything to the left to make sure that the brain is following things properly down. Don't center everything.

2. Use uniform colors (plus one standout color for emphasis)

Now, you'll notice that most of my bars here have a uniform color - simple black. I like to color everything one color, because then I'll use a separate, standout color, like this blue, to strategically emphasize my key message. You might notice that I did that throughout this step for the words that I want you to pick out. That's why I colored these particular bars, because this feels like the story to me, because that is the storytelling part of this message.

Notice that I also colored the category in my observation to create a connective tissue between these two items. So using color intentionally means things like using green for good and red for bad, not arbitrarily, and then maybe blue for what's important.

3. Source your data

Then finally, you always want to source your data. That increases the trust. So you want to put your platform and your date range. Really simple.

So this is the anatomy of an awesome data viz. I've adapted it from a great book called "Good Charts" by my friend, Scott Berinato. What I have found that by using this protocol, you're going to end up with these wonderful, raving fans who are going to love your work and understand your value. I included a little kitty fan because I can. It's my Whiteboard Friday.

So that is the protocol. I actually have included a free gift for you today. If you click the link at the end of this post, you'll be able to sign up for a Chart Detox Checklist, a full printable PICA Protocol prescription and a Chart Choosing Guide.

Get the PICA Protocol prescription

I would actually love to hear from you. What are the kinds of struggles that you have in presenting your insights to stakeholders, where you just feel like they're not getting the value of what you're doing? I'd love to hear any questions you have about the methodology as well.

So thank you for watching this edition of Whiteboard Friday. I hope you enjoyed it. We'll see you next week, and please remember to viz responsibly, my friends. Namaste.

Video transcription by Speechpad.com

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don't have time to hunt down but want to read!

[nankaih-blog]

PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday

Posted by Lea-Pica

If you find your presentations are often met with a lukewarm reception, it's a sure sign it's time for you to invest in your data storytelling. By following a few smart rules, a structured approach to data visualization could make all the difference in how stakeholders receive and act upon your insights. In this edition of Whiteboard Friday, we're thrilled to welcome data viz expert Lea Pica to share her strategic methodology for creating highly effective charts.

Click on the whiteboard image above to open a high-resolution version in a new tab!

Video Transcription

Hello, Moz fans. Welcome to another edition of Whiteboard Friday. I'm here to talk to you this week about a very hot topic in the digital marketing space. So my name is Lea Pica, and I am a data storytelling trainer, coach, speaker, blogger, and podcaster at LeaPica.com.

I want to tell you a little story. So as 12 years I spent as a digital analyst and SEM, I used to present insights a lot, but nothing ever happened as a result of it. People fell asleep or never responded. No action was being taken. So I decided to figure out what was happening, and I learned all these great tricks for doing it.

What I learned in my journey is that effective data visualization communicates a story quickly, clearly, accurately, and ethically, and it had really four main goals - to inform decisions, to inspire action, to galvanize people, and most importantly to communicate the value of the work that you do.

Now, there are lots of things you can do, but I was struggling to find one specific process that was going to help me get from what I was trying to communicate to getting people to act on it. So I developed my own methodology. It's called the PICA Protocol, and it's a visualization prescription for impactful data storytelling. What I like about this protocol is that it's practical, approachable. It's not complicated. It's prescriptive, and it's repeatable. I believe it's going to get you where you need to go every time.

So let's say one of your managers, clients, stakeholders is asking you for something like, "What are our most successful keyword groups?" Something delightfully vague like that. Now, before you jump into your data visualization platform and start dropping charts like it's hot, I want you to take a step back and start with the first step in the process, which is P for purpose.

P for Purpose

So I found that every great data visualization started with a very focused question or questions.

Why do you exist? Get philosophical with it.

What need of my audience are you meeting?

What decisions are you going to inform?

These questions help you get really focused about what you're going to present and avoid the sort of needle in a haystack approach to seeing what might stick.

So the answers to these questions are going to help you make an important decision, to choose an appropriate chart type for the message that you're trying to convey. Some of the ways you want to do that - I hear you guys are like into keywords a little bit - you want to listen for the keywords of what people are asking you for. So in this case, we have "most successful." Okay, that indicates a comparison. Different types or campaigns or groups, those are categories. So it sounds like what we're going for is a categorical comparison. There are other kinds of keywords you can look for, like changing over time, how this affects that. Answers or opinions. All of those are going to help you determine your most appropriate visual.

Now, in this case, we have a categorical comparison, so I always go back to basics. It's an oldie but goodie, but we're going to do the tried-and-true bar chart. It's universally understood and doesn't have a learning curve. What I would not recommend are pie charts. No, no, no. Unless you only have two segments in your visual and one is unmistakably larger than the other, pie charts are not your best choice for communicating categorical comparison, composition, or ranking.

I for Insight

So we have our choice. We're now going to move on to the next step in the methodology, which is I for insight. So an insight is something that gives a person a capacity to understand something quickly, accurately, and intuitively. Think of those criteria.

So here, does my display surface the story and answer these questions intuitively? That's our criteria. The components of that are:

Layout and orientation. So how is the chart configured? Very often we'll use vertical bar charts for categorical comparison, but that will end up having diagonal labels if they're really long, and unless your audience walks around like this all the time, it's going to be confusing because that would be weird. So you want to make sure it's oriented well.

Labeling. In the case of bars, I always prefer to label each bar directly rather than relying on just an axis, because then their eyes aren't jumping from bar to axis to bar to axis and they're paying more attention to you. That's also for line charts. Very often I'll label a line with a maximum, a minimum, and maybe the most important data point.

Interpretation of the data and where we're placing it, the location.

So our interpretation, is it objective or is it subjective? So subjective words are like better or worse or stupid or awesome. Those are opinions. But objective words are higher, lower, most efficient, least efficient. So you really want your observations to be objective.

Have you presented it ethically? Or have you manipulated the view in a way that isn't telling a really ethical picture, like adjusting a bar axis above zero, which is a no-no? But you can do that with a line graph in certain cases. So look for those nuances. You want to basically ask yourself, "Would I be able to uphold this visual in a court of law or sleep at night?"

Location of that insight. So very often we'll put our insights, our interpretation down here or in really tiny letters up here. Then up here we'll put big letters saying this is sales, my keyword category. No. What we want to do is we want to put our interpretation up here. This top area is the most important real estate on your visual. That's where their eyes are going to look first. So think of this like a BuzzFeed headline for your visual. What do you want them to take away? You can always put what the chart is here in a little subtitle.

Make recommendations. Because that's what a really powerful visual is going to do.

I always suggest having two recommendations at least, because this way you're empowering your audience with a choice. This way you can actually be subjective. That is okay in this case, because that's your unique subject matter expertise.

Are your recommendations accountable to specific people? Are they feasible?

What's the cost of not acting on your recommendations? Put some urgency behind it. So I like to put my recommendations in a little box or callout on the side here so it's really clear after I've presented my facts.

C for Context

The next step in the methodology is C for context. What this is saying is, "Do I have all the data points I need to paint a complete picture, or is there more to this story?" So some additional lenses you might find useful are past period comparison, targets or benchmarks are useful, segmentation, things like geography, mobile device. Or what are the typical questions or arguments that your audience has when you present data? They can be super value contextual points.

In this case, I might decide that while they care about the number of sales, because that's most successful to them, I care about the keywords "conversion rates." So I'm going to add a second bar chart here like this, and I'm going to see there's a different story that's popping out here now.

Now, this is where your data storytelling really comes into play. This particular strategy is called a table lens or a side-by-side bar chart. It's what I recommend if you want to combine two categorical metrics together.

A for Aesthetics

Now, the last step in the methodology is A for aesthetics. Aesthetics are how things look. So it's not about making it look pretty. No, it's asking, "Does my viz comply with brain best practices of how we absorb information?"

1. Decrease visual noise

So the first step in doing that is we want to decrease visual noise, because that creates a lot of tension. So decreasing noise will increase the chance of a happy brain.

Now, I'm a crunchy granola hippie, so I love to detox every day. I've developed a data visualization detox that entails removing things like grid lines, borders, axis lines, line markers, and backgrounds. Get all of that junk out of there, really clean up. You can align everything to the left to make sure that the brain is following things properly down. Don't center everything.

2. Use uniform colors (plus one standout color for emphasis)

Now, you'll notice that most of my bars here have a uniform color - simple black. I like to color everything one color, because then I'll use a separate, standout color, like this blue, to strategically emphasize my key message. You might notice that I did that throughout this step for the words that I want you to pick out. That's why I colored these particular bars, because this feels like the story to me, because that is the storytelling part of this message.

Notice that I also colored the category in my observation to create a connective tissue between these two items. So using color intentionally means things like using green for good and red for bad, not arbitrarily, and then maybe blue for what's important.

3. Source your data

Then finally, you always want to source your data. That increases the trust. So you want to put your platform and your date range. Really simple.

So this is the anatomy of an awesome data viz. I've adapted it from a great book called "Good Charts" by my friend, Scott Berinato. What I have found that by using this protocol, you're going to end up with these wonderful, raving fans who are going to love your work and understand your value. I included a little kitty fan because I can. It's my Whiteboard Friday.

So that is the protocol. I actually have included a free gift for you today. If you click the link at the end of this post, you'll be able to sign up for a Chart Detox Checklist, a full printable PICA Protocol prescription and a Chart Choosing Guide.

Get the PICA Protocol prescription

I would actually love to hear from you. What are the kinds of struggles that you have in presenting your insights to stakeholders, where you just feel like they're not getting the value of what you're doing? I'd love to hear any questions you have about the methodology as well.

So thank you for watching this edition of Whiteboard Friday. I hope you enjoyed it. We'll see you next week, and please remember to viz responsibly, my friends. Namaste.

Video transcription by Speechpad.com

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don't have time to hunt down but want to read!

[solongdarling-blog]

PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday

Posted by Lea-Pica

If you find your presentations are often met with a lukewarm reception, it's a sure sign it's time for you to invest in your data storytelling. By following a few smart rules, a structured approach to data visualization could make all the difference in how stakeholders receive and act upon your insights. In this edition of Whiteboard Friday, we're thrilled to welcome data viz expert Lea Pica to share her strategic methodology for creating highly effective charts.

Click on the whiteboard image above to open a high-resolution version in a new tab!

Video Transcription

Hello, Moz fans. Welcome to another edition of Whiteboard Friday. I'm here to talk to you this week about a very hot topic in the digital marketing space. So my name is Lea Pica, and I am a data storytelling trainer, coach, speaker, blogger, and podcaster at LeaPica.com.

I want to tell you a little story. So as 12 years I spent as a digital analyst and SEM, I used to present insights a lot, but nothing ever happened as a result of it. People fell asleep or never responded. No action was being taken. So I decided to figure out what was happening, and I learned all these great tricks for doing it.

What I learned in my journey is that effective data visualization communicates a story quickly, clearly, accurately, and ethically, and it had really four main goals - to inform decisions, to inspire action, to galvanize people, and most importantly to communicate the value of the work that you do.

Now, there are lots of things you can do, but I was struggling to find one specific process that was going to help me get from what I was trying to communicate to getting people to act on it. So I developed my own methodology. It's called the PICA Protocol, and it's a visualization prescription for impactful data storytelling. What I like about this protocol is that it's practical, approachable. It's not complicated. It's prescriptive, and it's repeatable. I believe it's going to get you where you need to go every time.

So let's say one of your managers, clients, stakeholders is asking you for something like, "What are our most successful keyword groups?" Something delightfully vague like that. Now, before you jump into your data visualization platform and start dropping charts like it's hot, I want you to take a step back and start with the first step in the process, which is P for purpose.

P for Purpose

So I found that every great data visualization started with a very focused question or questions.

Why do you exist? Get philosophical with it.

What need of my audience are you meeting?

What decisions are you going to inform?

These questions help you get really focused about what you're going to present and avoid the sort of needle in a haystack approach to seeing what might stick.

So the answers to these questions are going to help you make an important decision, to choose an appropriate chart type for the message that you're trying to convey. Some of the ways you want to do that - I hear you guys are like into keywords a little bit - you want to listen for the keywords of what people are asking you for. So in this case, we have "most successful." Okay, that indicates a comparison. Different types or campaigns or groups, those are categories. So it sounds like what we're going for is a categorical comparison. There are other kinds of keywords you can look for, like changing over time, how this affects that. Answers or opinions. All of those are going to help you determine your most appropriate visual.

Now, in this case, we have a categorical comparison, so I always go back to basics. It's an oldie but goodie, but we're going to do the tried-and-true bar chart. It's universally understood and doesn't have a learning curve. What I would not recommend are pie charts. No, no, no. Unless you only have two segments in your visual and one is unmistakably larger than the other, pie charts are not your best choice for communicating categorical comparison, composition, or ranking.

I for Insight

So we have our choice. We're now going to move on to the next step in the methodology, which is I for insight. So an insight is something that gives a person a capacity to understand something quickly, accurately, and intuitively. Think of those criteria.

So here, does my display surface the story and answer these questions intuitively? That's our criteria. The components of that are:

Layout and orientation. So how is the chart configured? Very often we'll use vertical bar charts for categorical comparison, but that will end up having diagonal labels if they're really long, and unless your audience walks around like this all the time, it's going to be confusing because that would be weird. So you want to make sure it's oriented well.

Labeling. In the case of bars, I always prefer to label each bar directly rather than relying on just an axis, because then their eyes aren't jumping from bar to axis to bar to axis and they're paying more attention to you. That's also for line charts. Very often I'll label a line with a maximum, a minimum, and maybe the most important data point.

Interpretation of the data and where we're placing it, the location.

So our interpretation, is it objective or is it subjective? So subjective words are like better or worse or stupid or awesome. Those are opinions. But objective words are higher, lower, most efficient, least efficient. So you really want your observations to be objective.

Have you presented it ethically? Or have you manipulated the view in a way that isn't telling a really ethical picture, like adjusting a bar axis above zero, which is a no-no? But you can do that with a line graph in certain cases. So look for those nuances. You want to basically ask yourself, "Would I be able to uphold this visual in a court of law or sleep at night?"

Location of that insight. So very often we'll put our insights, our interpretation down here or in really tiny letters up here. Then up here we'll put big letters saying this is sales, my keyword category. No. What we want to do is we want to put our interpretation up here. This top area is the most important real estate on your visual. That's where their eyes are going to look first. So think of this like a BuzzFeed headline for your visual. What do you want them to take away? You can always put what the chart is here in a little subtitle.

Make recommendations. Because that's what a really powerful visual is going to do.

I always suggest having two recommendations at least, because this way you're empowering your audience with a choice. This way you can actually be subjective. That is okay in this case, because that's your unique subject matter expertise.

Are your recommendations accountable to specific people? Are they feasible?

What's the cost of not acting on your recommendations? Put some urgency behind it. So I like to put my recommendations in a little box or callout on the side here so it's really clear after I've presented my facts.

C for Context

The next step in the methodology is C for context. What this is saying is, "Do I have all the data points I need to paint a complete picture, or is there more to this story?" So some additional lenses you might find useful are past period comparison, targets or benchmarks are useful, segmentation, things like geography, mobile device. Or what are the typical questions or arguments that your audience has when you present data? They can be super value contextual points.

In this case, I might decide that while they care about the number of sales, because that's most successful to them, I care about the keywords "conversion rates." So I'm going to add a second bar chart here like this, and I'm going to see there's a different story that's popping out here now.

Now, this is where your data storytelling really comes into play. This particular strategy is called a table lens or a side-by-side bar chart. It's what I recommend if you want to combine two categorical metrics together.

A for Aesthetics

Now, the last step in the methodology is A for aesthetics. Aesthetics are how things look. So it's not about making it look pretty. No, it's asking, "Does my viz comply with brain best practices of how we absorb information?"

1. Decrease visual noise

So the first step in doing that is we want to decrease visual noise, because that creates a lot of tension. So decreasing noise will increase the chance of a happy brain.

Now, I'm a crunchy granola hippie, so I love to detox every day. I've developed a data visualization detox that entails removing things like grid lines, borders, axis lines, line markers, and backgrounds. Get all of that junk out of there, really clean up. You can align everything to the left to make sure that the brain is following things properly down. Don't center everything.

2. Use uniform colors (plus one standout color for emphasis)

Now, you'll notice that most of my bars here have a uniform color - simple black. I like to color everything one color, because then I'll use a separate, standout color, like this blue, to strategically emphasize my key message. You might notice that I did that throughout this step for the words that I want you to pick out. That's why I colored these particular bars, because this feels like the story to me, because that is the storytelling part of this message.

Notice that I also colored the category in my observation to create a connective tissue between these two items. So using color intentionally means things like using green for good and red for bad, not arbitrarily, and then maybe blue for what's important.

3. Source your data

Then finally, you always want to source your data. That increases the trust. So you want to put your platform and your date range. Really simple.

So this is the anatomy of an awesome data viz. I've adapted it from a great book called "Good Charts" by my friend, Scott Berinato. What I have found that by using this protocol, you're going to end up with these wonderful, raving fans who are going to love your work and understand your value. I included a little kitty fan because I can. It's my Whiteboard Friday.

So that is the protocol. I actually have included a free gift for you today. If you click the link at the end of this post, you'll be able to sign up for a Chart Detox Checklist, a full printable PICA Protocol prescription and a Chart Choosing Guide.

Get the PICA Protocol prescription

I would actually love to hear from you. What are the kinds of struggles that you have in presenting your insights to stakeholders, where you just feel like they're not getting the value of what you're doing? I'd love to hear any questions you have about the methodology as well.

So thank you for watching this edition of Whiteboard Friday. I hope you enjoyed it. We'll see you next week, and please remember to viz responsibly, my friends. Namaste.

Video transcription by Speechpad.com

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don't have time to hunt down but want to read!

[fromthegrotto-blog1]

PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday

Posted by Lea-Pica

If you find your presentations are often met with a lukewarm reception, it's a sure sign it's time for you to invest in your data storytelling. By following a few smart rules, a structured approach to data visualization could make all the difference in how stakeholders receive and act upon your insights. In this edition of Whiteboard Friday, we're thrilled to welcome data viz expert Lea Pica to share her strategic methodology for creating highly effective charts.

Click on the whiteboard image above to open a high-resolution version in a new tab!

Video Transcription

Hello, Moz fans. Welcome to another edition of Whiteboard Friday. I'm here to talk to you this week about a very hot topic in the digital marketing space. So my name is Lea Pica, and I am a data storytelling trainer, coach, speaker, blogger, and podcaster at LeaPica.com.

I want to tell you a little story. So as 12 years I spent as a digital analyst and SEM, I used to present insights a lot, but nothing ever happened as a result of it. People fell asleep or never responded. No action was being taken. So I decided to figure out what was happening, and I learned all these great tricks for doing it.

What I learned in my journey is that effective data visualization communicates a story quickly, clearly, accurately, and ethically, and it had really four main goals - to inform decisions, to inspire action, to galvanize people, and most importantly to communicate the value of the work that you do.

Now, there are lots of things you can do, but I was struggling to find one specific process that was going to help me get from what I was trying to communicate to getting people to act on it. So I developed my own methodology. It's called the PICA Protocol, and it's a visualization prescription for impactful data storytelling. What I like about this protocol is that it's practical, approachable. It's not complicated. It's prescriptive, and it's repeatable. I believe it's going to get you where you need to go every time.

So let's say one of your managers, clients, stakeholders is asking you for something like, "What are our most successful keyword groups?" Something delightfully vague like that. Now, before you jump into your data visualization platform and start dropping charts like it's hot, I want you to take a step back and start with the first step in the process, which is P for purpose.

P for Purpose

So I found that every great data visualization started with a very focused question or questions.

Why do you exist? Get philosophical with it.

What need of my audience are you meeting?

What decisions are you going to inform?

These questions help you get really focused about what you're going to present and avoid the sort of needle in a haystack approach to seeing what might stick.

So the answers to these questions are going to help you make an important decision, to choose an appropriate chart type for the message that you're trying to convey. Some of the ways you want to do that - I hear you guys are like into keywords a little bit - you want to listen for the keywords of what people are asking you for. So in this case, we have "most successful." Okay, that indicates a comparison. Different types or campaigns or groups, those are categories. So it sounds like what we're going for is a categorical comparison. There are other kinds of keywords you can look for, like changing over time, how this affects that. Answers or opinions. All of those are going to help you determine your most appropriate visual.

Now, in this case, we have a categorical comparison, so I always go back to basics. It's an oldie but goodie, but we're going to do the tried-and-true bar chart. It's universally understood and doesn't have a learning curve. What I would not recommend are pie charts. No, no, no. Unless you only have two segments in your visual and one is unmistakably larger than the other, pie charts are not your best choice for communicating categorical comparison, composition, or ranking.

I for Insight

So we have our choice. We're now going to move on to the next step in the methodology, which is I for insight. So an insight is something that gives a person a capacity to understand something quickly, accurately, and intuitively. Think of those criteria.

So here, does my display surface the story and answer these questions intuitively? That's our criteria. The components of that are:

Layout and orientation. So how is the chart configured? Very often we'll use vertical bar charts for categorical comparison, but that will end up having diagonal labels if they're really long, and unless your audience walks around like this all the time, it's going to be confusing because that would be weird. So you want to make sure it's oriented well.

Labeling. In the case of bars, I always prefer to label each bar directly rather than relying on just an axis, because then their eyes aren't jumping from bar to axis to bar to axis and they're paying more attention to you. That's also for line charts. Very often I'll label a line with a maximum, a minimum, and maybe the most important data point.

Interpretation of the data and where we're placing it, the location.

So our interpretation, is it objective or is it subjective? So subjective words are like better or worse or stupid or awesome. Those are opinions. But objective words are higher, lower, most efficient, least efficient. So you really want your observations to be objective.

Have you presented it ethically? Or have you manipulated the view in a way that isn't telling a really ethical picture, like adjusting a bar axis above zero, which is a no-no? But you can do that with a line graph in certain cases. So look for those nuances. You want to basically ask yourself, "Would I be able to uphold this visual in a court of law or sleep at night?"

Location of that insight. So very often we'll put our insights, our interpretation down here or in really tiny letters up here. Then up here we'll put big letters saying this is sales, my keyword category. No. What we want to do is we want to put our interpretation up here. This top area is the most important real estate on your visual. That's where their eyes are going to look first. So think of this like a BuzzFeed headline for your visual. What do you want them to take away? You can always put what the chart is here in a little subtitle.

Make recommendations. Because that's what a really powerful visual is going to do.

I always suggest having two recommendations at least, because this way you're empowering your audience with a choice. This way you can actually be subjective. That is okay in this case, because that's your unique subject matter expertise.

Are your recommendations accountable to specific people? Are they feasible?

What's the cost of not acting on your recommendations? Put some urgency behind it. So I like to put my recommendations in a little box or callout on the side here so it's really clear after I've presented my facts.

C for Context

The next step in the methodology is C for context. What this is saying is, "Do I have all the data points I need to paint a complete picture, or is there more to this story?" So some additional lenses you might find useful are past period comparison, targets or benchmarks are useful, segmentation, things like geography, mobile device. Or what are the typical questions or arguments that your audience has when you present data? They can be super value contextual points.

In this case, I might decide that while they care about the number of sales, because that's most successful to them, I care about the keywords "conversion rates." So I'm going to add a second bar chart here like this, and I'm going to see there's a different story that's popping out here now.

Now, this is where your data storytelling really comes into play. This particular strategy is called a table lens or a side-by-side bar chart. It's what I recommend if you want to combine two categorical metrics together.

A for Aesthetics

Now, the last step in the methodology is A for aesthetics. Aesthetics are how things look. So it's not about making it look pretty. No, it's asking, "Does my viz comply with brain best practices of how we absorb information?"

1. Decrease visual noise

So the first step in doing that is we want to decrease visual noise, because that creates a lot of tension. So decreasing noise will increase the chance of a happy brain.

Now, I'm a crunchy granola hippie, so I love to detox every day. I've developed a data visualization detox that entails removing things like grid lines, borders, axis lines, line markers, and backgrounds. Get all of that junk out of there, really clean up. You can align everything to the left to make sure that the brain is following things properly down. Don't center everything.

2. Use uniform colors (plus one standout color for emphasis)

Now, you'll notice that most of my bars here have a uniform color - simple black. I like to color everything one color, because then I'll use a separate, standout color, like this blue, to strategically emphasize my key message. You might notice that I did that throughout this step for the words that I want you to pick out. That's why I colored these particular bars, because this feels like the story to me, because that is the storytelling part of this message.

Notice that I also colored the category in my observation to create a connective tissue between these two items. So using color intentionally means things like using green for good and red for bad, not arbitrarily, and then maybe blue for what's important.

3. Source your data

Then finally, you always want to source your data. That increases the trust. So you want to put your platform and your date range. Really simple.

So this is the anatomy of an awesome data viz. I've adapted it from a great book called "Good Charts" by my friend, Scott Berinato. What I have found that by using this protocol, you're going to end up with these wonderful, raving fans who are going to love your work and understand your value. I included a little kitty fan because I can. It's my Whiteboard Friday.

So that is the protocol. I actually have included a free gift for you today. If you click the link at the end of this post, you'll be able to sign up for a Chart Detox Checklist, a full printable PICA Protocol prescription and a Chart Choosing Guide.

Get the PICA Protocol prescription

I would actually love to hear from you. What are the kinds of struggles that you have in presenting your insights to stakeholders, where you just feel like they're not getting the value of what you're doing? I'd love to hear any questions you have about the methodology as well.

So thank you for watching this edition of Whiteboard Friday. I hope you enjoyed it. We'll see you next week, and please remember to viz responsibly, my friends. Namaste.

Video transcription by Speechpad.com

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don't have time to hunt down but want to read!

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PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday

Posted by Lea-Pica

If you find your presentations are often met with a lukewarm reception, it's a sure sign it's time for you to invest in your data storytelling. By following a few smart rules, a structured approach to data visualization could make all the difference in how stakeholders receive and act upon your insights. In this edition of Whiteboard Friday, we're thrilled to welcome data viz expert Lea Pica to share her strategic methodology for creating highly effective charts.

Click on the whiteboard image above to open a high-resolution version in a new tab!

Video Transcription

Hello, Moz fans. Welcome to another edition of Whiteboard Friday. I'm here to talk to you this week about a very hot topic in the digital marketing space. So my name is Lea Pica, and I am a data storytelling trainer, coach, speaker, blogger, and podcaster at LeaPica.com.

I want to tell you a little story. So as 12 years I spent as a digital analyst and SEM, I used to present insights a lot, but nothing ever happened as a result of it. People fell asleep or never responded. No action was being taken. So I decided to figure out what was happening, and I learned all these great tricks for doing it.

What I learned in my journey is that effective data visualization communicates a story quickly, clearly, accurately, and ethically, and it had really four main goals - to inform decisions, to inspire action, to galvanize people, and most importantly to communicate the value of the work that you do.

Now, there are lots of things you can do, but I was struggling to find one specific process that was going to help me get from what I was trying to communicate to getting people to act on it. So I developed my own methodology. It's called the PICA Protocol, and it's a visualization prescription for impactful data storytelling. What I like about this protocol is that it's practical, approachable. It's not complicated. It's prescriptive, and it's repeatable. I believe it's going to get you where you need to go every time.

So let's say one of your managers, clients, stakeholders is asking you for something like, "What are our most successful keyword groups?" Something delightfully vague like that. Now, before you jump into your data visualization platform and start dropping charts like it's hot, I want you to take a step back and start with the first step in the process, which is P for purpose.

P for Purpose

So I found that every great data visualization started with a very focused question or questions.

Why do you exist? Get philosophical with it.

What need of my audience are you meeting?

What decisions are you going to inform?

These questions help you get really focused about what you're going to present and avoid the sort of needle in a haystack approach to seeing what might stick.

So the answers to these questions are going to help you make an important decision, to choose an appropriate chart type for the message that you're trying to convey. Some of the ways you want to do that - I hear you guys are like into keywords a little bit - you want to listen for the keywords of what people are asking you for. So in this case, we have "most successful." Okay, that indicates a comparison. Different types or campaigns or groups, those are categories. So it sounds like what we're going for is a categorical comparison. There are other kinds of keywords you can look for, like changing over time, how this affects that. Answers or opinions. All of those are going to help you determine your most appropriate visual.

Now, in this case, we have a categorical comparison, so I always go back to basics. It's an oldie but goodie, but we're going to do the tried-and-true bar chart. It's universally understood and doesn't have a learning curve. What I would not recommend are pie charts. No, no, no. Unless you only have two segments in your visual and one is unmistakably larger than the other, pie charts are not your best choice for communicating categorical comparison, composition, or ranking.

I for Insight

So we have our choice. We're now going to move on to the next step in the methodology, which is I for insight. So an insight is something that gives a person a capacity to understand something quickly, accurately, and intuitively. Think of those criteria.

So here, does my display surface the story and answer these questions intuitively? That's our criteria. The components of that are:

Layout and orientation. So how is the chart configured? Very often we'll use vertical bar charts for categorical comparison, but that will end up having diagonal labels if they're really long, and unless your audience walks around like this all the time, it's going to be confusing because that would be weird. So you want to make sure it's oriented well.

Labeling. In the case of bars, I always prefer to label each bar directly rather than relying on just an axis, because then their eyes aren't jumping from bar to axis to bar to axis and they're paying more attention to you. That's also for line charts. Very often I'll label a line with a maximum, a minimum, and maybe the most important data point.

Interpretation of the data and where we're placing it, the location.

So our interpretation, is it objective or is it subjective? So subjective words are like better or worse or stupid or awesome. Those are opinions. But objective words are higher, lower, most efficient, least efficient. So you really want your observations to be objective.

Have you presented it ethically? Or have you manipulated the view in a way that isn't telling a really ethical picture, like adjusting a bar axis above zero, which is a no-no? But you can do that with a line graph in certain cases. So look for those nuances. You want to basically ask yourself, "Would I be able to uphold this visual in a court of law or sleep at night?"

Location of that insight. So very often we'll put our insights, our interpretation down here or in really tiny letters up here. Then up here we'll put big letters saying this is sales, my keyword category. No. What we want to do is we want to put our interpretation up here. This top area is the most important real estate on your visual. That's where their eyes are going to look first. So think of this like a BuzzFeed headline for your visual. What do you want them to take away? You can always put what the chart is here in a little subtitle.

Make recommendations. Because that's what a really powerful visual is going to do.

I always suggest having two recommendations at least, because this way you're empowering your audience with a choice. This way you can actually be subjective. That is okay in this case, because that's your unique subject matter expertise.

Are your recommendations accountable to specific people? Are they feasible?

What's the cost of not acting on your recommendations? Put some urgency behind it. So I like to put my recommendations in a little box or callout on the side here so it's really clear after I've presented my facts.

C for Context

The next step in the methodology is C for context. What this is saying is, "Do I have all the data points I need to paint a complete picture, or is there more to this story?" So some additional lenses you might find useful are past period comparison, targets or benchmarks are useful, segmentation, things like geography, mobile device. Or what are the typical questions or arguments that your audience has when you present data? They can be super value contextual points.

In this case, I might decide that while they care about the number of sales, because that's most successful to them, I care about the keywords "conversion rates." So I'm going to add a second bar chart here like this, and I'm going to see there's a different story that's popping out here now.

Now, this is where your data storytelling really comes into play. This particular strategy is called a table lens or a side-by-side bar chart. It's what I recommend if you want to combine two categorical metrics together.

A for Aesthetics

Now, the last step in the methodology is A for aesthetics. Aesthetics are how things look. So it's not about making it look pretty. No, it's asking, "Does my viz comply with brain best practices of how we absorb information?"

1. Decrease visual noise

So the first step in doing that is we want to decrease visual noise, because that creates a lot of tension. So decreasing noise will increase the chance of a happy brain.

Now, I'm a crunchy granola hippie, so I love to detox every day. I've developed a data visualization detox that entails removing things like grid lines, borders, axis lines, line markers, and backgrounds. Get all of that junk out of there, really clean up. You can align everything to the left to make sure that the brain is following things properly down. Don't center everything.

2. Use uniform colors (plus one standout color for emphasis)

Now, you'll notice that most of my bars here have a uniform color - simple black. I like to color everything one color, because then I'll use a separate, standout color, like this blue, to strategically emphasize my key message. You might notice that I did that throughout this step for the words that I want you to pick out. That's why I colored these particular bars, because this feels like the story to me, because that is the storytelling part of this message.

Notice that I also colored the category in my observation to create a connective tissue between these two items. So using color intentionally means things like using green for good and red for bad, not arbitrarily, and then maybe blue for what's important.

3. Source your data

Then finally, you always want to source your data. That increases the trust. So you want to put your platform and your date range. Really simple.

So this is the anatomy of an awesome data viz. I've adapted it from a great book called "Good Charts" by my friend, Scott Berinato. What I have found that by using this protocol, you're going to end up with these wonderful, raving fans who are going to love your work and understand your value. I included a little kitty fan because I can. It's my Whiteboard Friday.

So that is the protocol. I actually have included a free gift for you today. If you click the link at the end of this post, you'll be able to sign up for a Chart Detox Checklist, a full printable PICA Protocol prescription and a Chart Choosing Guide.

Get the PICA Protocol prescription

I would actually love to hear from you. What are the kinds of struggles that you have in presenting your insights to stakeholders, where you just feel like they're not getting the value of what you're doing? I'd love to hear any questions you have about the methodology as well.

So thank you for watching this edition of Whiteboard Friday. I hope you enjoyed it. We'll see you next week, and please remember to viz responsibly, my friends. Namaste.

Video transcription by Speechpad.com

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don't have time to hunt down but want to read!

[eve-evi-blog]

PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday

Posted by Lea-Pica

If you find your presentations are often met with a lukewarm reception, it's a sure sign it's time for you to invest in your data storytelling. By following a few smart rules, a structured approach to data visualization could make all the difference in how stakeholders receive and act upon your insights. In this edition of Whiteboard Friday, we're thrilled to welcome data viz expert Lea Pica to share her strategic methodology for creating highly effective charts.

Click on the whiteboard image above to open a high-resolution version in a new tab!

Video Transcription

Hello, Moz fans. Welcome to another edition of Whiteboard Friday. I'm here to talk to you this week about a very hot topic in the digital marketing space. So my name is Lea Pica, and I am a data storytelling trainer, coach, speaker, blogger, and podcaster at LeaPica.com.

I want to tell you a little story. So as 12 years I spent as a digital analyst and SEM, I used to present insights a lot, but nothing ever happened as a result of it. People fell asleep or never responded. No action was being taken. So I decided to figure out what was happening, and I learned all these great tricks for doing it.

What I learned in my journey is that effective data visualization communicates a story quickly, clearly, accurately, and ethically, and it had really four main goals - to inform decisions, to inspire action, to galvanize people, and most importantly to communicate the value of the work that you do.

Now, there are lots of things you can do, but I was struggling to find one specific process that was going to help me get from what I was trying to communicate to getting people to act on it. So I developed my own methodology. It's called the PICA Protocol, and it's a visualization prescription for impactful data storytelling. What I like about this protocol is that it's practical, approachable. It's not complicated. It's prescriptive, and it's repeatable. I believe it's going to get you where you need to go every time.

So let's say one of your managers, clients, stakeholders is asking you for something like, "What are our most successful keyword groups?" Something delightfully vague like that. Now, before you jump into your data visualization platform and start dropping charts like it's hot, I want you to take a step back and start with the first step in the process, which is P for purpose.

P for Purpose

So I found that every great data visualization started with a very focused question or questions.

Why do you exist? Get philosophical with it.

What need of my audience are you meeting?

What decisions are you going to inform?

These questions help you get really focused about what you're going to present and avoid the sort of needle in a haystack approach to seeing what might stick.

So the answers to these questions are going to help you make an important decision, to choose an appropriate chart type for the message that you're trying to convey. Some of the ways you want to do that - I hear you guys are like into keywords a little bit - you want to listen for the keywords of what people are asking you for. So in this case, we have "most successful." Okay, that indicates a comparison. Different types or campaigns or groups, those are categories. So it sounds like what we're going for is a categorical comparison. There are other kinds of keywords you can look for, like changing over time, how this affects that. Answers or opinions. All of those are going to help you determine your most appropriate visual.

Now, in this case, we have a categorical comparison, so I always go back to basics. It's an oldie but goodie, but we're going to do the tried-and-true bar chart. It's universally understood and doesn't have a learning curve. What I would not recommend are pie charts. No, no, no. Unless you only have two segments in your visual and one is unmistakably larger than the other, pie charts are not your best choice for communicating categorical comparison, composition, or ranking.

I for Insight

So we have our choice. We're now going to move on to the next step in the methodology, which is I for insight. So an insight is something that gives a person a capacity to understand something quickly, accurately, and intuitively. Think of those criteria.

So here, does my display surface the story and answer these questions intuitively? That's our criteria. The components of that are:

Layout and orientation. So how is the chart configured? Very often we'll use vertical bar charts for categorical comparison, but that will end up having diagonal labels if they're really long, and unless your audience walks around like this all the time, it's going to be confusing because that would be weird. So you want to make sure it's oriented well.

Labeling. In the case of bars, I always prefer to label each bar directly rather than relying on just an axis, because then their eyes aren't jumping from bar to axis to bar to axis and they're paying more attention to you. That's also for line charts. Very often I'll label a line with a maximum, a minimum, and maybe the most important data point.

Interpretation of the data and where we're placing it, the location.

So our interpretation, is it objective or is it subjective? So subjective words are like better or worse or stupid or awesome. Those are opinions. But objective words are higher, lower, most efficient, least efficient. So you really want your observations to be objective.

Have you presented it ethically? Or have you manipulated the view in a way that isn't telling a really ethical picture, like adjusting a bar axis above zero, which is a no-no? But you can do that with a line graph in certain cases. So look for those nuances. You want to basically ask yourself, "Would I be able to uphold this visual in a court of law or sleep at night?"

Location of that insight. So very often we'll put our insights, our interpretation down here or in really tiny letters up here. Then up here we'll put big letters saying this is sales, my keyword category. No. What we want to do is we want to put our interpretation up here. This top area is the most important real estate on your visual. That's where their eyes are going to look first. So think of this like a BuzzFeed headline for your visual. What do you want them to take away? You can always put what the chart is here in a little subtitle.

Make recommendations. Because that's what a really powerful visual is going to do.

I always suggest having two recommendations at least, because this way you're empowering your audience with a choice. This way you can actually be subjective. That is okay in this case, because that's your unique subject matter expertise.

Are your recommendations accountable to specific people? Are they feasible?

What's the cost of not acting on your recommendations? Put some urgency behind it. So I like to put my recommendations in a little box or callout on the side here so it's really clear after I've presented my facts.

C for Context

The next step in the methodology is C for context. What this is saying is, "Do I have all the data points I need to paint a complete picture, or is there more to this story?" So some additional lenses you might find useful are past period comparison, targets or benchmarks are useful, segmentation, things like geography, mobile device. Or what are the typical questions or arguments that your audience has when you present data? They can be super value contextual points.

In this case, I might decide that while they care about the number of sales, because that's most successful to them, I care about the keywords "conversion rates." So I'm going to add a second bar chart here like this, and I'm going to see there's a different story that's popping out here now.

Now, this is where your data storytelling really comes into play. This particular strategy is called a table lens or a side-by-side bar chart. It's what I recommend if you want to combine two categorical metrics together.

A for Aesthetics

Now, the last step in the methodology is A for aesthetics. Aesthetics are how things look. So it's not about making it look pretty. No, it's asking, "Does my viz comply with brain best practices of how we absorb information?"

1. Decrease visual noise

So the first step in doing that is we want to decrease visual noise, because that creates a lot of tension. So decreasing noise will increase the chance of a happy brain.

Now, I'm a crunchy granola hippie, so I love to detox every day. I've developed a data visualization detox that entails removing things like grid lines, borders, axis lines, line markers, and backgrounds. Get all of that junk out of there, really clean up. You can align everything to the left to make sure that the brain is following things properly down. Don't center everything.

2. Use uniform colors (plus one standout color for emphasis)

Now, you'll notice that most of my bars here have a uniform color - simple black. I like to color everything one color, because then I'll use a separate, standout color, like this blue, to strategically emphasize my key message. You might notice that I did that throughout this step for the words that I want you to pick out. That's why I colored these particular bars, because this feels like the story to me, because that is the storytelling part of this message.

Notice that I also colored the category in my observation to create a connective tissue between these two items. So using color intentionally means things like using green for good and red for bad, not arbitrarily, and then maybe blue for what's important.

3. Source your data

Then finally, you always want to source your data. That increases the trust. So you want to put your platform and your date range. Really simple.

So this is the anatomy of an awesome data viz. I've adapted it from a great book called "Good Charts" by my friend, Scott Berinato. What I have found that by using this protocol, you're going to end up with these wonderful, raving fans who are going to love your work and understand your value. I included a little kitty fan because I can. It's my Whiteboard Friday.

So that is the protocol. I actually have included a free gift for you today. If you click the link at the end of this post, you'll be able to sign up for a Chart Detox Checklist, a full printable PICA Protocol prescription and a Chart Choosing Guide.

Get the PICA Protocol prescription

I would actually love to hear from you. What are the kinds of struggles that you have in presenting your insights to stakeholders, where you just feel like they're not getting the value of what you're doing? I'd love to hear any questions you have about the methodology as well.

So thank you for watching this edition of Whiteboard Friday. I hope you enjoyed it. We'll see you next week, and please remember to viz responsibly, my friends. Namaste.

Video transcription by Speechpad.com

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don't have time to hunt down but want to read!

[tvrdojezgreno-blog]

PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday

Posted by Lea-Pica

If you find your presentations are often met with a lukewarm reception, it's a sure sign it's time for you to invest in your data storytelling. By following a few smart rules, a structured approach to data visualization could make all the difference in how stakeholders receive and act upon your insights. In this edition of Whiteboard Friday, we're thrilled to welcome data viz expert Lea Pica to share her strategic methodology for creating highly effective charts.

Click on the whiteboard image above to open a high-resolution version in a new tab!

Video Transcription

Hello, Moz fans. Welcome to another edition of Whiteboard Friday. I'm here to talk to you this week about a very hot topic in the digital marketing space. So my name is Lea Pica, and I am a data storytelling trainer, coach, speaker, blogger, and podcaster at LeaPica.com.

I want to tell you a little story. So as 12 years I spent as a digital analyst and SEM, I used to present insights a lot, but nothing ever happened as a result of it. People fell asleep or never responded. No action was being taken. So I decided to figure out what was happening, and I learned all these great tricks for doing it.

What I learned in my journey is that effective data visualization communicates a story quickly, clearly, accurately, and ethically, and it had really four main goals - to inform decisions, to inspire action, to galvanize people, and most importantly to communicate the value of the work that you do.

Now, there are lots of things you can do, but I was struggling to find one specific process that was going to help me get from what I was trying to communicate to getting people to act on it. So I developed my own methodology. It's called the PICA Protocol, and it's a visualization prescription for impactful data storytelling. What I like about this protocol is that it's practical, approachable. It's not complicated. It's prescriptive, and it's repeatable. I believe it's going to get you where you need to go every time.

So let's say one of your managers, clients, stakeholders is asking you for something like, "What are our most successful keyword groups?" Something delightfully vague like that. Now, before you jump into your data visualization platform and start dropping charts like it's hot, I want you to take a step back and start with the first step in the process, which is P for purpose.

P for Purpose

So I found that every great data visualization started with a very focused question or questions.

Why do you exist? Get philosophical with it.

What need of my audience are you meeting?

What decisions are you going to inform?

These questions help you get really focused about what you're going to present and avoid the sort of needle in a haystack approach to seeing what might stick.

So the answers to these questions are going to help you make an important decision, to choose an appropriate chart type for the message that you're trying to convey. Some of the ways you want to do that - I hear you guys are like into keywords a little bit - you want to listen for the keywords of what people are asking you for. So in this case, we have "most successful." Okay, that indicates a comparison. Different types or campaigns or groups, those are categories. So it sounds like what we're going for is a categorical comparison. There are other kinds of keywords you can look for, like changing over time, how this affects that. Answers or opinions. All of those are going to help you determine your most appropriate visual.

Now, in this case, we have a categorical comparison, so I always go back to basics. It's an oldie but goodie, but we're going to do the tried-and-true bar chart. It's universally understood and doesn't have a learning curve. What I would not recommend are pie charts. No, no, no. Unless you only have two segments in your visual and one is unmistakably larger than the other, pie charts are not your best choice for communicating categorical comparison, composition, or ranking.

I for Insight

So we have our choice. We're now going to move on to the next step in the methodology, which is I for insight. So an insight is something that gives a person a capacity to understand something quickly, accurately, and intuitively. Think of those criteria.

So here, does my display surface the story and answer these questions intuitively? That's our criteria. The components of that are:

Layout and orientation. So how is the chart configured? Very often we'll use vertical bar charts for categorical comparison, but that will end up having diagonal labels if they're really long, and unless your audience walks around like this all the time, it's going to be confusing because that would be weird. So you want to make sure it's oriented well.

Labeling. In the case of bars, I always prefer to label each bar directly rather than relying on just an axis, because then their eyes aren't jumping from bar to axis to bar to axis and they're paying more attention to you. That's also for line charts. Very often I'll label a line with a maximum, a minimum, and maybe the most important data point.

Interpretation of the data and where we're placing it, the location.

So our interpretation, is it objective or is it subjective? So subjective words are like better or worse or stupid or awesome. Those are opinions. But objective words are higher, lower, most efficient, least efficient. So you really want your observations to be objective.

Have you presented it ethically? Or have you manipulated the view in a way that isn't telling a really ethical picture, like adjusting a bar axis above zero, which is a no-no? But you can do that with a line graph in certain cases. So look for those nuances. You want to basically ask yourself, "Would I be able to uphold this visual in a court of law or sleep at night?"

Location of that insight. So very often we'll put our insights, our interpretation down here or in really tiny letters up here. Then up here we'll put big letters saying this is sales, my keyword category. No. What we want to do is we want to put our interpretation up here. This top area is the most important real estate on your visual. That's where their eyes are going to look first. So think of this like a BuzzFeed headline for your visual. What do you want them to take away? You can always put what the chart is here in a little subtitle.

Make recommendations. Because that's what a really powerful visual is going to do.

I always suggest having two recommendations at least, because this way you're empowering your audience with a choice. This way you can actually be subjective. That is okay in this case, because that's your unique subject matter expertise.

Are your recommendations accountable to specific people? Are they feasible?

What's the cost of not acting on your recommendations? Put some urgency behind it. So I like to put my recommendations in a little box or callout on the side here so it's really clear after I've presented my facts.

C for Context

The next step in the methodology is C for context. What this is saying is, "Do I have all the data points I need to paint a complete picture, or is there more to this story?" So some additional lenses you might find useful are past period comparison, targets or benchmarks are useful, segmentation, things like geography, mobile device. Or what are the typical questions or arguments that your audience has when you present data? They can be super value contextual points.

In this case, I might decide that while they care about the number of sales, because that's most successful to them, I care about the keywords "conversion rates." So I'm going to add a second bar chart here like this, and I'm going to see there's a different story that's popping out here now.

Now, this is where your data storytelling really comes into play. This particular strategy is called a table lens or a side-by-side bar chart. It's what I recommend if you want to combine two categorical metrics together.

A for Aesthetics

Now, the last step in the methodology is A for aesthetics. Aesthetics are how things look. So it's not about making it look pretty. No, it's asking, "Does my viz comply with brain best practices of how we absorb information?"

1. Decrease visual noise

So the first step in doing that is we want to decrease visual noise, because that creates a lot of tension. So decreasing noise will increase the chance of a happy brain.

Now, I'm a crunchy granola hippie, so I love to detox every day. I've developed a data visualization detox that entails removing things like grid lines, borders, axis lines, line markers, and backgrounds. Get all of that junk out of there, really clean up. You can align everything to the left to make sure that the brain is following things properly down. Don't center everything.

2. Use uniform colors (plus one standout color for emphasis)

Now, you'll notice that most of my bars here have a uniform color - simple black. I like to color everything one color, because then I'll use a separate, standout color, like this blue, to strategically emphasize my key message. You might notice that I did that throughout this step for the words that I want you to pick out. That's why I colored these particular bars, because this feels like the story to me, because that is the storytelling part of this message.

Notice that I also colored the category in my observation to create a connective tissue between these two items. So using color intentionally means things like using green for good and red for bad, not arbitrarily, and then maybe blue for what's important.

3. Source your data

Then finally, you always want to source your data. That increases the trust. So you want to put your platform and your date range. Really simple.

So this is the anatomy of an awesome data viz. I've adapted it from a great book called "Good Charts" by my friend, Scott Berinato. What I have found that by using this protocol, you're going to end up with these wonderful, raving fans who are going to love your work and understand your value. I included a little kitty fan because I can. It's my Whiteboard Friday.

So that is the protocol. I actually have included a free gift for you today. If you click the link at the end of this post, you'll be able to sign up for a Chart Detox Checklist, a full printable PICA Protocol prescription and a Chart Choosing Guide.

Get the PICA Protocol prescription

I would actually love to hear from you. What are the kinds of struggles that you have in presenting your insights to stakeholders, where you just feel like they're not getting the value of what you're doing? I'd love to hear any questions you have about the methodology as well.

So thank you for watching this edition of Whiteboard Friday. I hope you enjoyed it. We'll see you next week, and please remember to viz responsibly, my friends. Namaste.

Video transcription by Speechpad.com

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don't have time to hunt down but want to read!

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PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday

Posted by Lea-Pica

If you find your presentations are often met with a lukewarm reception, it's a sure sign it's time for you to invest in your data storytelling. By following a few smart rules, a structured approach to data visualization could make all the difference in how stakeholders receive and act upon your insights. In this edition of Whiteboard Friday, we're thrilled to welcome data viz expert Lea Pica to share her strategic methodology for creating highly effective charts.

Click on the whiteboard image above to open a high-resolution version in a new tab!

Video Transcription

Hello, Moz fans. Welcome to another edition of Whiteboard Friday. I'm here to talk to you this week about a very hot topic in the digital marketing space. So my name is Lea Pica, and I am a data storytelling trainer, coach, speaker, blogger, and podcaster at LeaPica.com.

I want to tell you a little story. So as 12 years I spent as a digital analyst and SEM, I used to present insights a lot, but nothing ever happened as a result of it. People fell asleep or never responded. No action was being taken. So I decided to figure out what was happening, and I learned all these great tricks for doing it.

What I learned in my journey is that effective data visualization communicates a story quickly, clearly, accurately, and ethically, and it had really four main goals - to inform decisions, to inspire action, to galvanize people, and most importantly to communicate the value of the work that you do.

Now, there are lots of things you can do, but I was struggling to find one specific process that was going to help me get from what I was trying to communicate to getting people to act on it. So I developed my own methodology. It's called the PICA Protocol, and it's a visualization prescription for impactful data storytelling. What I like about this protocol is that it's practical, approachable. It's not complicated. It's prescriptive, and it's repeatable. I believe it's going to get you where you need to go every time.

So let's say one of your managers, clients, stakeholders is asking you for something like, "What are our most successful keyword groups?" Something delightfully vague like that. Now, before you jump into your data visualization platform and start dropping charts like it's hot, I want you to take a step back and start with the first step in the process, which is P for purpose.

P for Purpose

So I found that every great data visualization started with a very focused question or questions.

Why do you exist? Get philosophical with it.

What need of my audience are you meeting?

What decisions are you going to inform?

These questions help you get really focused about what you're going to present and avoid the sort of needle in a haystack approach to seeing what might stick.

So the answers to these questions are going to help you make an important decision, to choose an appropriate chart type for the message that you're trying to convey. Some of the ways you want to do that - I hear you guys are like into keywords a little bit - you want to listen for the keywords of what people are asking you for. So in this case, we have "most successful." Okay, that indicates a comparison. Different types or campaigns or groups, those are categories. So it sounds like what we're going for is a categorical comparison. There are other kinds of keywords you can look for, like changing over time, how this affects that. Answers or opinions. All of those are going to help you determine your most appropriate visual.

Now, in this case, we have a categorical comparison, so I always go back to basics. It's an oldie but goodie, but we're going to do the tried-and-true bar chart. It's universally understood and doesn't have a learning curve. What I would not recommend are pie charts. No, no, no. Unless you only have two segments in your visual and one is unmistakably larger than the other, pie charts are not your best choice for communicating categorical comparison, composition, or ranking.

I for Insight

So we have our choice. We're now going to move on to the next step in the methodology, which is I for insight. So an insight is something that gives a person a capacity to understand something quickly, accurately, and intuitively. Think of those criteria.

So here, does my display surface the story and answer these questions intuitively? That's our criteria. The components of that are:

Layout and orientation. So how is the chart configured? Very often we'll use vertical bar charts for categorical comparison, but that will end up having diagonal labels if they're really long, and unless your audience walks around like this all the time, it's going to be confusing because that would be weird. So you want to make sure it's oriented well.

Labeling. In the case of bars, I always prefer to label each bar directly rather than relying on just an axis, because then their eyes aren't jumping from bar to axis to bar to axis and they're paying more attention to you. That's also for line charts. Very often I'll label a line with a maximum, a minimum, and maybe the most important data point.

Interpretation of the data and where we're placing it, the location.

So our interpretation, is it objective or is it subjective? So subjective words are like better or worse or stupid or awesome. Those are opinions. But objective words are higher, lower, most efficient, least efficient. So you really want your observations to be objective.

Have you presented it ethically? Or have you manipulated the view in a way that isn't telling a really ethical picture, like adjusting a bar axis above zero, which is a no-no? But you can do that with a line graph in certain cases. So look for those nuances. You want to basically ask yourself, "Would I be able to uphold this visual in a court of law or sleep at night?"

Location of that insight. So very often we'll put our insights, our interpretation down here or in really tiny letters up here. Then up here we'll put big letters saying this is sales, my keyword category. No. What we want to do is we want to put our interpretation up here. This top area is the most important real estate on your visual. That's where their eyes are going to look first. So think of this like a BuzzFeed headline for your visual. What do you want them to take away? You can always put what the chart is here in a little subtitle.

Make recommendations. Because that's what a really powerful visual is going to do.

I always suggest having two recommendations at least, because this way you're empowering your audience with a choice. This way you can actually be subjective. That is okay in this case, because that's your unique subject matter expertise.

Are your recommendations accountable to specific people? Are they feasible?

What's the cost of not acting on your recommendations? Put some urgency behind it. So I like to put my recommendations in a little box or callout on the side here so it's really clear after I've presented my facts.

C for Context

The next step in the methodology is C for context. What this is saying is, "Do I have all the data points I need to paint a complete picture, or is there more to this story?" So some additional lenses you might find useful are past period comparison, targets or benchmarks are useful, segmentation, things like geography, mobile device. Or what are the typical questions or arguments that your audience has when you present data? They can be super value contextual points.

In this case, I might decide that while they care about the number of sales, because that's most successful to them, I care about the keywords "conversion rates." So I'm going to add a second bar chart here like this, and I'm going to see there's a different story that's popping out here now.

Now, this is where your data storytelling really comes into play. This particular strategy is called a table lens or a side-by-side bar chart. It's what I recommend if you want to combine two categorical metrics together.

A for Aesthetics

Now, the last step in the methodology is A for aesthetics. Aesthetics are how things look. So it's not about making it look pretty. No, it's asking, "Does my viz comply with brain best practices of how we absorb information?"

1. Decrease visual noise

So the first step in doing that is we want to decrease visual noise, because that creates a lot of tension. So decreasing noise will increase the chance of a happy brain.

Now, I'm a crunchy granola hippie, so I love to detox every day. I've developed a data visualization detox that entails removing things like grid lines, borders, axis lines, line markers, and backgrounds. Get all of that junk out of there, really clean up. You can align everything to the left to make sure that the brain is following things properly down. Don't center everything.

2. Use uniform colors (plus one standout color for emphasis)

Now, you'll notice that most of my bars here have a uniform color - simple black. I like to color everything one color, because then I'll use a separate, standout color, like this blue, to strategically emphasize my key message. You might notice that I did that throughout this step for the words that I want you to pick out. That's why I colored these particular bars, because this feels like the story to me, because that is the storytelling part of this message.

Notice that I also colored the category in my observation to create a connective tissue between these two items. So using color intentionally means things like using green for good and red for bad, not arbitrarily, and then maybe blue for what's important.

3. Source your data

Then finally, you always want to source your data. That increases the trust. So you want to put your platform and your date range. Really simple.

So this is the anatomy of an awesome data viz. I've adapted it from a great book called "Good Charts" by my friend, Scott Berinato. What I have found that by using this protocol, you're going to end up with these wonderful, raving fans who are going to love your work and understand your value. I included a little kitty fan because I can. It's my Whiteboard Friday.

So that is the protocol. I actually have included a free gift for you today. If you click the link at the end of this post, you'll be able to sign up for a Chart Detox Checklist, a full printable PICA Protocol prescription and a Chart Choosing Guide.

Get the PICA Protocol prescription

I would actually love to hear from you. What are the kinds of struggles that you have in presenting your insights to stakeholders, where you just feel like they're not getting the value of what you're doing? I'd love to hear any questions you have about the methodology as well.

So thank you for watching this edition of Whiteboard Friday. I hope you enjoyed it. We'll see you next week, and please remember to viz responsibly, my friends. Namaste.

Video transcription by Speechpad.com

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don't have time to hunt down but want to read!

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PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday

PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday

Posted by Lea-Pica

If you find your presentations are often met with a lukewarm reception, it's a sure sign it's time for you to invest in your data storytelling. By following a few smart rules, a structured approach to data visualization could make all the difference in how stakeholders receive and act upon your insights. In this edition of Whiteboard Friday, we're thrilled to welcome data viz expert Lea Pica to share her strategic methodology for creating highly effective charts.

Click on the whiteboard image above to open a high-resolution version in a new tab!

Video Transcription

Hello, Moz fans. Welcome to another edition of Whiteboard Friday. I'm here to talk to you this week about a very hot topic in the digital marketing space. So my name is Lea Pica, and I am a data storytelling trainer, coach, speaker, blogger, and podcaster at LeaPica.com.

I want to tell you a little story. So as 12 years I spent as a digital analyst and SEM, I used to present insights a lot, but nothing ever happened as a result of it. People fell asleep or never responded. No action was being taken. So I decided to figure out what was happening, and I learned all these great tricks for doing it.

What I learned in my journey is that effective data visualization communicates a story quickly, clearly, accurately, and ethically, and it had really four main goals — to inform decisions, to inspire action, to galvanize people, and most importantly to communicate the value of the work that you do.

Now, there are lots of things you can do, but I was struggling to find one specific process that was going to help me get from what I was trying to communicate to getting people to act on it. So I developed my own methodology. It's called the PICA Protocol, and it's a visualization prescription for impactful data storytelling. What I like about this protocol is that it's practical, approachable. It's not complicated. It's prescriptive, and it's repeatable. I believe it's going to get you where you need to go every time.

So let's say one of your managers, clients, stakeholders is asking you for something like, "What are our most successful keyword groups?" Something delightfully vague like that. Now, before you jump into your data visualization platform and start dropping charts like it's hot, I want you to take a step back and start with the first step in the process, which is P for purpose.

P for Purpose

So I found that every great data visualization started with a very focused question or questions.

Why do you exist? Get philosophical with it.

What need of my audience are you meeting?

What decisions are you going to inform?

These questions help you get really focused about what you're going to present and avoid the sort of needle in a haystack approach to seeing what might stick.

So the answers to these questions are going to help you make an important decision, to choose an appropriate chart type for the message that you're trying to convey. Some of the ways you want to do that — I hear you guys are like into keywords a little bit — you want to listen for the keywords of what people are asking you for. So in this case, we have "most successful." Okay, that indicates a comparison. Different types or campaigns or groups, those are categories. So it sounds like what we're going for is a categorical comparison. There are other kinds of keywords you can look for, like changing over time, how this affects that. Answers or opinions. All of those are going to help you determine your most appropriate visual.

Now, in this case, we have a categorical comparison, so I always go back to basics. It's an oldie but goodie, but we're going to do the tried-and-true bar chart. It's universally understood and doesn't have a learning curve. What I would not recommend are pie charts. No, no, no. Unless you only have two segments in your visual and one is unmistakably larger than the other, pie charts are not your best choice for communicating categorical comparison, composition, or ranking.

I for Insight

So we have our choice. We're now going to move on to the next step in the methodology, which is I for insight. So an insight is something that gives a person a capacity to understand something quickly, accurately, and intuitively. Think of those criteria.

So here, does my display surface the story and answer these questions intuitively? That's our criteria. The components of that are:

Layout and orientation. So how is the chart configured? Very often we'll use vertical bar charts for categorical comparison, but that will end up having diagonal labels if they're really long, and unless your audience walks around like this all the time, it's going to be confusing because that would be weird. So you want to make sure it's oriented well.

Labeling. In the case of bars, I always prefer to label each bar directly rather than relying on just an axis, because then their eyes aren't jumping from bar to axis to bar to axis and they're paying more attention to you. That's also for line charts. Very often I'll label a line with a maximum, a minimum, and maybe the most important data point.

Interpretation of the data and where we're placing it, the location.

So our interpretation, is it objective or is it subjective? So subjective words are like better or worse or stupid or awesome. Those are opinions. But objective words are higher, lower, most efficient, least efficient. So you really want your observations to be objective.

Have you presented it ethically? Or have you manipulated the view in a way that isn't telling a really ethical picture, like adjusting a bar axis above zero, which is a no-no? But you can do that with a line graph in certain cases. So look for those nuances. You want to basically ask yourself, "Would I be able to uphold this visual in a court of law or sleep at night?"

Location of that insight. So very often we'll put our insights, our interpretation down here or in really tiny letters up here. Then up here we'll put big letters saying this is sales, my keyword category. No. What we want to do is we want to put our interpretation up here. This top area is the most important real estate on your visual. That's where their eyes are going to look first. So think of this like a BuzzFeed headline for your visual. What do you want them to take away? You can always put what the chart is here in a little subtitle.

Make recommendations. Because that's what a really powerful visual is going to do.

I always suggest having two recommendations at least, because this way you're empowering your audience with a choice. This way you can actually be subjective. That is okay in this case, because that's your unique subject matter expertise.

Are your recommendations accountable to specific people? Are they feasible?

What's the cost of not acting on your recommendations? Put some urgency behind it. So I like to put my recommendations in a little box or callout on the side here so it's really clear after I've presented my facts.

C for Context

The next step in the methodology is C for context. What this is saying is, "Do I have all the data points I need to paint a complete picture, or is there more to this story?" So some additional lenses you might find useful are past period comparison, targets or benchmarks are useful, segmentation, things like geography, mobile device. Or what are the typical questions or arguments that your audience has when you present data? They can be super value contextual points.

In this case, I might decide that while they care about the number of sales, because that's most successful to them, I care about the keywords "conversion rates." So I'm going to add a second bar chart here like this, and I'm going to see there's a different story that's popping out here now.

Now, this is where your data storytelling really comes into play. This particular strategy is called a table lens or a side-by-side bar chart. It's what I recommend if you want to combine two categorical metrics together.

A for Aesthetics

Now, the last step in the methodology is A for aesthetics. Aesthetics are how things look. So it's not about making it look pretty. No, it's asking, "Does my viz comply with brain best practices of how we absorb information?"

1. Decrease visual noise

So the first step in doing that is we want to decrease visual noise, because that creates a lot of tension. So decreasing noise will increase the chance of a happy brain.

Now, I'm a crunchy granola hippie, so I love to detox every day. I've developed a data visualization detox that entails removing things like grid lines, borders, axis lines, line markers, and backgrounds. Get all of that junk out of there, really clean up. You can align everything to the left to make sure that the brain is following things properly down. Don't center everything.

2. Use uniform colors (plus one standout color for emphasis)

Now, you'll notice that most of my bars here have a uniform color — simple black. I like to color everything one color, because then I'll use a separate, standout color, like this blue, to strategically emphasize my key message. You might notice that I did that throughout this step for the words that I want you to pick out. That's why I colored these particular bars, because this feels like the story to me, because that is the storytelling part of this message.

Notice that I also colored the category in my observation to create a connective tissue between these two items. So using color intentionally means things like using green for good and red for bad, not arbitrarily, and then maybe blue for what's important.

3. Source your data

Then finally, you always want to source your data. That increases the trust. So you want to put your platform and your date range. Really simple.

So this is the anatomy of an awesome data viz. I've adapted it from a great book called "Good Charts" by my friend, Scott Berinato. What I have found that by using this protocol, you're going to end up with these wonderful, raving fans who are going to love your work and understand your value. I included a little kitty fan because I can. It's my Whiteboard Friday.

So that is the protocol. I actually have included a free gift for you today. If you click the link at the end of this post, you'll be able to sign up for a Chart Detox Checklist, a full printable PICA Protocol prescription and a Chart Choosing Guide.

Get the PICA Protocol prescription

I would actually love to hear from you. What are the kinds of struggles that you have in presenting your insights to stakeholders, where you just feel like they're not getting the value of what you're doing? I'd love to hear any questions you have about the methodology as well.

So thank you for watching this edition of Whiteboard Friday. I hope you enjoyed it. We'll see you next week, and please remember to viz responsibly, my friends. Namaste.

Video transcription by Speechpad.com

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don't have time to hunt down but want to read!

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Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - Whiteboard Friday https://ift.tt/2kG7ARl xem thêm tại: https://ift.tt/2mb4VST để biết thêm về địa chỉ bán tai nghe không dây giá rẻ PICA Protocol: A Visualization Prescription for Impactful Data Storytelling - 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