#don’t even get me started on that one GIANT spreadsheet with MULTIPLE PAGES that has nearly EVERY Dick and Tim comic

[bonemeal12]

He’s a freak in the spreadsheets

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The Native website positioning Stats & Sensible Ways of Google’s Prime-Ranked Grocery Shops

New Post has been published on http://tiptopreview.com/the-local-seo-stats-practical-tactics-of-googles-top-ranked-grocery-stores/

The Native website positioning Stats & Sensible Ways of Google’s Prime-Ranked Grocery Shops

Grocery shops belong on the heart of the 2021 native website positioning trade dialog.

Apart from medical amenities, no enterprise stands out extra clearly on the map as important to each day life within the US, and few verticals have needed to adapt extra quickly in mid-flight than our neighborhood meals shops within the COVID-19 period. From unbiased grocers to main grocery store chains, there are heroes in each aisle retaining the nation fed. Any knowledge that helps the robust continuance of those companies is properly value sharing.

On this article, I’ll present outcomes from 900 knowledge factors I pulled whereas analyzing the highest local-pack-ranked grocery retailer in every of the 50 US capital cities. I’ll additionally summarize the sensible techniques I’ve discovered from listening to grocers and their entrepreneurs, highlighting how they’re adapting and succeeding in unprecedented occasions.

It’s my hope that each in-house and company grocery entrepreneurs will uncover vital takeaways in my evaluation to make sure a profitable 2021 for every very important retailer.

Methodology

I manually queried Google for “grocery store”, modified with the town title of every of the 50 US capital cities. I used to be not bodily situated in any of the cities the place I searched, which ought to exclude the affect of user-to-business proximity. In a spreadsheet, I manually recorded 18 traits for every of the successful grocery shops, after which drew my statistics from this knowledge.

The GMB traits of top-ranked grocery shops

Evaluate these statististics to evaluate how a grocery retailer you’re marketing measures up.

Location inside metropolis limits

100% of the grocery shops rating #1 had a bodily location inside the metropolis limits of the required search phrase metropolis. No store, nonetheless robust, was getting the primary spot within the native pack if it wasn’t inside the metropolis.

Takeaway: Having a location inside metropolis limits correlates with a superb likelihood of rating for searches that comprise that metropolis’s title.

Key phrases in enterprise title

Solely 6% of the top-ranked companies had enterprise titles that matched any a part of my search phrases. This was good to see, given Google’s identified (and unlucky) rewarding of manufacturers that stuff key phrases into their enterprise titles in violation of Google’s guidelines. I noticed just one enterprise that had extraneous key phrases in its title.

Takeaway: You don’t must spam Google with key phrases in your small business title to rank as a high grocery retailer.

Model variety

Nobody model is successful the highest spot throughout the nation. Outcomes have been extraordinarily numerous, and made up of a vibrant mixture of unbiased grocers and huge chains. Some manufacturers have been successful out in multiple state, nonetheless. Safeway received 5 native packs, Complete Meals received 4, and Hy-Vee and Hannaford every received three. Past this, manufacturers have been very assorted.

Takeaway: Any model, giant or small, can compete for premium native visibility. Nobody model has a monopoly on rankings.

Web page Authority of GMB touchdown web page

Page Authority (PA) is a 100-point rating developed by Moz that predicts how properly a particular web site web page will rank inside search engine outcomes. PA is believed to exert a powerful affect on native pack rankings.

Analyzing the PA of the web site touchdown web page linked to from every grocery retailer’s Google My Enterprise itemizing, I discovered that the common PA was 40. The highest PA was 58 and the lowest was 26. 5 of the top-ranked supermarkets had no web site hyperlink in any respect, amazingly, and this should be a supply of thriller and frustration for lower-ranked grocery shops in these cities with GMB listings that do hyperlink to their web sites.

Takeaway: A mean PA of 40 is just not prohibitively excessive. Utilizing Moz Pro to measure aggressive PA and actively in search of related native hyperlinks for every location of a grocery model will help you beat out sleepier rivals. When low PA or perhaps a lacking web site hyperlink are nonetheless being rewarded with a excessive rating for a competitor of the model you’re marketing, it’s time to conduct a local business audit to find which different native search rating elements is likely to be at play.

Major GMB class

82% of top-ranked grocery shops use “grocery store” as their major class. The rest of manufacturers had chosen just a few different classes, like “supermarket” or “organic food store”. The first class chosen for the GMB itemizing is believed to have essentially the most influence on which phrases the enterprise ranks for in Google’s native packs.

Takeaway: “Grocery store” has a a lot greater estimated month-to-month search quantity than some other key phrase phrase I investigated, corresponding to “supermarket” or “food store”. Grocers wishing to rank for this high time period are greatest off selecting “grocery store” as their major GMB class.

Score

The common score of top-ranked grocery shops is Four.2 stars. The highest rated market had Four.7 stars, and the lowest had three.6. Star ratings are believed to influence local rank.

Takeaway: No top-ranked grocery retailer had an ideal 5-star score. Don’t be overly involved in regards to the occasional adverse evaluation, however do intention for buyer satisfaction that yields scores within the Four-star vary, cumulatively.

Evaluate rely

Grocery shops obtain a large variety of opinions, and evaluation counts are believed to affect rank. Total, the 50 grocery shops I analyzed had acquired a complete of 62,415 opinions, indicating simply how frequent utilization of Google as a dominant client evaluation platform has grow to be.

The common evaluation rely per retailer location is 1,248. The rely for the most-reviewed grocery retailer in my knowledge set is three,632. The fewest opinions a top-ranked retailer acquired is 227. Keep in mind that the opinions every retailer location wants to realize most visibility will likely be predicated on their distinctive geographic market and stage of competitors.

Takeaway: The truth that the overwhelming majority of opinions I noticed are unmanaged (don’t have any model responses) leads me to imagine that skilled evaluation acquisition campaigns aren’t doubtless the drive driving the excessive variety of complete opinions within the grocery trade. Fairly, I’d counsel that Individuals are self-motivated to evaluation the locations they store for meals. However, if a model you’re marketing is being outranked by a competitor with extra client sentiment, launching a proper evaluation acquisition program is a great guess for impacting rank and enhancing customer support for a retailer location.

Evaluate recency

The recency of your opinions indicators to Google and customers whether or not your small business is a spot of bustling exercise or a bit on the quiet aspect. It’s lengthy been theorized that evaluation recency might need some influence on rank as a person conduct sign. In my knowledge set, 52% of top-ranked shops had been reviewed inside the final day. 46% had acquired a evaluation inside the final week. Solely 2% had seen greater than every week go by with out receiving a brand new evaluation.

Takeaway: A number of client surveys have discovered that clients are typically most serious about your most up-to-date opinions when making a choice about the place to buy. If a grocery retailer location you’re marketing hasn’t been reviewed in weeks or months (or years!), it’s undoubtedly a sign to start actively asking clients for suggestions.

At all times do not forget that your clients are your grocery retailer’s greatest gross sales drive. They freely persuade each other to buy along with your firm by dint of what they are saying about your model in opinions. A gradual stream of latest, constructive sentiment is priceless gross sales copy on your market.

Proprietor responses to opinions in 2020

Making use of Google’s proprietor response operate on the opinions a grocery retailer receives is completely fundamental to offering good customer service. Nevertheless, in my knowledge set, 60% of top-ranked grocery shops had not responded to a single evaluation in 2020, and of the 40% that had responded to some opinions, not one model had responded to all of their opinions.

Takeaway: Whereas ignoring opinions seems to have had no adverse influence on grocery shops’ capability to realize high native pack rankings, I can’t emphasize sufficient what a waste of alternative is occurring on this vertical.

Each evaluation is a buyer beginning a dialog with a model, whether or not their objective is to thank the enterprise or to complain in hopes of receiving assist. Ignoring nearly all of conversations clients are beginning should be extraordinarily deleterious to client satisfaction and popularity. 2020 was a 12 months like no different, and grocers have had their arms full adapting and surviving, however going ahead, supermarkets that allocate assets to responding to each evaluation could have an unbelievable buyer expertise edge over less-engaged rivals.

Place subjects

Google excerpts frequent subjects from the physique of every retailer’s opinions and places them on the high of the evaluation show. 40% of top-ranked grocery shops have “produce” as their most-mentioned place matter, and it was additionally current for a lot of, many different shops even when it wasn’t their #1 matter. 6% have “organic” and one other 6% have “to go” because the most-talked about component, however past this, place subjects are drastically assorted. This space of Google’s interface is sprinkled with phrases like “clean”, “cashier”, “deals”, “sales”, and lots of different phrases.

Takeaway: I’m not but satisfied of the usefulness or final endurance of this side of Google’s evaluation shows. Nevertheless, it supplies very shorthand sentiment evaluation for grocers and entrepreneurs wanting an at-a-glance thought of what clients are saying in opinions for a model and its rivals. You want to drill down into the textual content of the opinions, although, to see whether or not frequent mentions of one thing like “clean” are from clients saying a enterprise is or isn’t clear. Place subjects simply aren’t terribly subtle sentiment evaluation, at this level.

My knowledge set reveals that Individuals are placing premium deal with produce, so one takeaway right here is that the standard of your produce division drives customers to go away opinions. An ideal produce division may result in a fantastic score and nice consumer-created content material about your market. A disappointing produce part may create the reverse. I additionally discovered the prevalence of “organic” place subjects revealing, given stats I had seen on the 10X growth in purchases of natural produce between January and March of 2020. There’s a clear demand pattern right here for wholesome meals that needs to be informing stock.

Worth attributes

Google locations a 1-Four level “$” attribute on many listings as an analysis of costliness. It’s believed these designations stem, partially, from attribute questions Google asks customers, however the general knowledge set is incomplete. In my sampling, Google solely had a worth attribute for 42% of the top-ranked grocery shops. Of that quantity, 76% have been marked with the reasonable “$$” worth attribute.

Takeaway: As I discovered in my earlier piece on The Google Characteristics of America’s Top-Ranked Eateries, neither Google nor customers have a tendency to think about both the most cost effective or most costly meals choices to be essentially the most related. Ideas of thrift and spendiness differ drastically throughout the US, nevertheless it’s good to know modest worth analysis tends to correlate with high native rankings. That appears to be in-step with the present financial image. The grocery manufacturers you’re marketing don’t should be the most cost effective or the most costly; the perfect could be delivering good worth for an inexpensive worth.

Google Posts utilization earlier than and through COVID-19

Google Posts are a type of microblogging that permits manufacturers to publish recent content material to their Google Enterprise Profiles. Previous to the COVID-19 pandemic, 24% of grocers have been publishing Google Posts, however in 2020, solely 16% have been actively making any use of this function.

Takeaway: Google supplied special COVID-19 post capabilities to companies in 2020, however top-ranked grocery shops largely ignored this chance. Pre-pandemic utilization was very meager, with solely a couple of quarter of grocers utilizing Google Posts to spice up engagement. The eight% falloff in 2020 might paint an image of a vertical too preoccupied with different, extra pressing priorities to offer this function a strive.

Use of Google posts is just not believed to influence rating, and neglect of this function clearly didn’t maintain any of the themes again from reaching high rankings, but when a model you’re marketing can allocate assets to such a publishing, it’s value attempting. Moz Local will help you publish Google Posts to your listings, and improve the alternatives for customers to interact along with your profiles.

Google Questions & Solutions

Google Q&A is a Google Enterprise Profile operate that lets an organization publish and reply its FAQs, in addition to letting the general public ask and reply questions. Cumulatively, the fifty grocery shops in my survey have acquired 1,145 questions. The highest variety of questions for a single location is 192, and the lowest is 2.

Simply 14% of grocers have responded to any of the questions their shops have acquired, and in no case had a grocery retailer responded to all of its questions.

Takeaway: The vast majority of the questions I noticed have been leads — clients asking if a market had this or that product, or supplied a specific service or amenity. Sadly, public solutions, typically left by Google’s Native Guides, have been typically flippant and barren of knowledge to assist the client making the question. Whereas Q&A is just not believed to have any influence on rankings, ignoring clients is just not per objectives of offering glorious customer support.

Furthermore, ignoring leads has a financial context. One supply estimates that the typical American grocery journey invoice is $60. Which means that the overall variety of questions in my survey, if answered, may herald $68,700 for that pool of shops. Nevertheless, in my family, the typical grocery invoice is about $150 per journey, which may make answering this many questions in California value one thing like $171,750, if the outlets have the products and providers the shoppers are in search of. My numbers are simply estimates, however one factor I do know is that few manufacturers can afford to go away money on the desk.

I’d extremely advocate that grocery shops make the time to populate Google Q&A with their high FAQs, together with whether or not the enterprise presents supply, curbside service, and requires mask-wearing. Past this, utilizing a product like Moz Native will let you recognize every time a brand new query is available in at any of your areas, to be able to make sure no potential buyer is being ignored and that every one leads are the topic of cautious stewardship.

The COVID-19 diversifications top-ranked grocery shops have made

Past analyzing the GMB itemizing parts in my knowledge set, I phoned every of the grocery shops to ask them just a few questions to know how they’ve tailored achievement and insurance policies in response to the pandemic.

I may have relied on the Google attributes depicting curbside and supply service, however I’m glad I made the calls, as a result of I discovered discrepancies in use of those attributes and precise providers supplied. In some instances, shops with these facilities had not been tagged with these attributes but, and in others, the attributes that have been displayed have been fallacious.

These are my findings:

House grocery supply

62% of the shops in my survey set at the moment are providing dwelling grocery supply. I used to be shocked that this quantity wasn’t greater, given client demand for the most secure methods to maintain their households provided, coupled with the clear must maintain grocery employees as secure as potential.

Of this quantity, solely 12% of grocery shops I spoke with have managed to create an in-house supply service. 31 of the 50 manufacturers in my knowledge set have been having to go along with the expensive choice of third-party last-mile achievement. Of this quantity, 29% are utilizing Instacart, 26% are utilizing Doordash, eight% are utilizing Amazon Prime, Four% are utilizing Peapod and Shipt, and a pair of% are utilizing Grubhub. Three manufacturers have been partnering with multiple third-party service, and two have been providing each third-party and in-house supply choices.

Lastly, I noticed a number of cases of Google permitting third-party achievement firms to promote on the Google Enterprise Profiles of grocery shops. Grocery retailer workers who advised me that they had no supply service are virtually actually unaware of this practice. I discover this situation to be one of many least-acceptable in Google’s native playbook, significantly as a result of they place the burden on enterprise homeowners to attempt to get such advertising removed from their listings.

A enterprise working onerous to develop an in-house supply workforce doesn’t should have Doordash or Instacart or Grubhub parked on their itemizing, consuming away at earnings. Make certain you’re checking the Google Enterprise Profiles of any grocery shops you’re marketing and in search of removing of any third-party hyperlinks you don’t need.

Google Developments recorded the large spike in searches associated to grocery supply that occurred in spring of 2020 as Individuals sought methods for retaining their households provided whereas staying safely at dwelling. Once you couple this with the tragic reporting UFCW has been providing on the COVID-19 mortality of grocery workers, growing supply choices is crucial.

Retaining nearly all of the general public at dwelling and limiting face-to-face contact for grocery retailer workers has made dwelling supply a significant COVID-19 adaptation that should broaden past the 62% adoption price I noticed in my research.

Curbside service

For manufacturers which can be nonetheless struggling to develop a workable supply program, curbside pickup has been a welcome choice. 64% of the shops in my research are providing curbside service now — a quantity simply barely greater than the house supply determine. I noticed that in a number of instances, manufacturers that weren’t but set as much as do supply have been no less than in a position to create this achievement various, however we’d must see this determine at 100% to make sure nobody has to stroll right into a grocery retailer and threat an infection.

Masks coverage

Once I requested grocery retailer workers if their location required all workers and customers to put on masks, 83% stated sure and 17% stated no. This was an important query in my survey, given the state of the pandemic in the USA, and I need to share what I discovered past the numbers.

Within the cities/states the place grocery retailer employees reported no masking necessities, they invariably advised me they “lacked the authority to enforce mask-wearing”. Lack of presidency coverage has left the individuals in these communities helpless to guard themselves.

Critiques typically advised a special story for the 83% of grocery shops the place workers advised me masks are required. Regardless of a said mask-requirement coverage, reviewers report cases of encountering unmasked workers and patrons at some areas and categorical misery over this, typically stating they received’t return to those venues. Which means that the precise enforcement of PPE-wearing is definitely lower than 83%.

On a purely human stage, I sensed that my query about masking made some workers anxious, as in the event that they feared a adverse response from me once they advised me that masks have been required. I can solely think about the experiences a few of these workers members have had attempting to deal with clients refusing to guard themselves and others from contagion. The exchanges I had with workers additional cemented my understanding of the necessity for clear, nationwide coverage to scale back and, hopefully, eradicate COVID-19 so that everybody in our native communities is safeguarded.

My buddy and colleague Mike Blumenthal has performed the most effective job within the native website positioning trade documenting consumer demand for masking as evinced in reviews, and in addition, how to get political rant reviews from anti-maskers removed out of your GMB listings, ought to the shop you’re marketing obtain them. Out of my deep concern for grocery retailer employees and communities, it’s my robust hope that nationwide management will lead to 100% participation in grocery trade masking necessities in 2021.

Full contactless achievement

zero% of the grocery retailer manufacturers in my research have switched to contactless-only achievement, however this system might grow to be important in overcoming the general public well being emergency. When grocery shops can function as warehouses the place meals is saved for curbside pickup and supply, as an alternative of any in-store procuring, employees and clients can considerably scale back contact.

When the COVID-19 pandemic first emerged in America, markets like Oneota Community Food Coop in Decorah, Iowa switched to pick-up-only for a time, and might have to take action once more. In the meantime, my neighbor is receiving her full grocery supply each week from Imperfect Foods, which launched in San Francisco in 2015 and has skilled phenomenal expansion prior to now few years on its mission to ship economical meals in a handy method. This comes on the heels of the meal kit delivery bubble, encompassing Blue Apron, HelloFresh, Purple Carrot, and lots of different choices. Even comfort shops like 7-11 are making a powerful effort to go contactless.

In April of 2020, 40 million Americans placed online grocery orders. Speedy adaptation is completely potential, and till COVID-19 may be positioned within the nation’s rearview mirror, a nationwide effort could also be important to recast grocery manufacturers as curators of meals supply relatively than locations to buy in individual. Native search entrepreneurs ought to totally take part in grocery retailer consumer ideation on the way to form public notion that helps security for all.

Satisfaction, popularity, and rankings

Supply, curbside service, and strict masking insurance policies might not appear to have a direct connection to native search rankings, however within the bigger scheme of issues, they do. Prospects reward companies they love with constructive opinions. When a buyer is extraordinarily happy with how a enterprise like a grocery retailer takes care of them, studies show this motivates them to award opinions as a thank-you.

The extra you reveal to clients and communities that the grocery retailer you’re marketing cares for them, the extra you’ll develop your corpus of constructive opinions with excessive star scores. This, then, will help the native pack rating objectives you’re hoping to fulfill for max online visibility. And your popularity could have grow to be the type that generates excessive conversions. 79% of shoppers say contactless pickup is very important to them — no matter you are able to do to ship satisfaction to the patron majority is a really good transfer.

What I’ve discovered about agility from grocers and their entrepreneurs

“There shouldn’t be a brand between you and your customer. You shouldn’t be introducing them to somebody else and nobody should own your information.” — Brian Moyer, CEO, Freshop

It’s not overstating the case to say that the grocery trade is present process a revolution. Annual online grocery gross sales within the US elevated from $1.2 billion in August of 2019 to $7.2 billion in June of 2020.

As a neighborhood website positioning, I can’t consider one other trade I can be taught extra from about adaptation, ingenuity, and resilience. I’ve been following meals trade information, and was particularly engaged by a webinar I tuned into hosted by digital grocery software program supplier, Freshop. I’ll summarize seven key takeaways right here:

1) In the event you can develop an in-house supply program, do it, as a result of it’s the one option to preserve possession of the complete buyer expertise along with your model. It additionally makes monetary sense in the long term, as I coated beforehand right here in my column on Third Party vs. In-house delivery: A Guide to Informed Choice. Within the Freshop webinar, Brian Moyer reminded attendees that Blockbuster as soon as had the chance to purchase Netflix, however handed on the possibility. Now could be the time for grocery shops to guard themselves from giving their commerce away to the Instacarts and Doordashes on the scene.

2) No matter software program you employ to digitize your grocery stock, it needs to be robust on POS integration, stock administration, and analytics. I used to be impressed with the brief demo I noticed of Freshop’s analytics dashboard protection of choose occasions and slot achievement for supply administration, profitability throughout time, monitoring of each non-transactional and transactional behaviors, and integration of Google Analytics for measuring conversion charges.

three) Take a web page from meal package providers and supply them your self. Create breakfast kits, supper kits, dessert kits, vacation meal kits, and so forth. Make it straightforward for patrons to suppose when it comes to meals and get all the pieces they want in a few clicks.

Four) Take into account leveraging digital adverts in your grocery retailer web site from manufacturers you already carry. This will create an extra income stream.

5) Create online shoppable circulars. Do not forget that I noticed “deals” and “sales” displaying up as GMB place subjects? Many purchasers who used to take cues from print circulars can be taught to switch this behavior to clickable digital circulars.

6) Fastidiously consider the group help choices of the digital procuring software program you select. Most grocery shops aren’t direct rivals and will help each other out. An ideal instance I noticed was how one grocer shared the letter he wrote to use for taking SNAP funds. He was completely satisfied to let different grocers copy this kind letter to make use of for their very own purposes.

7) Rejoice the truth that online commerce has eliminated historic obstacles to clients finding retailer stock in a posh flooring plan. With a search field, any buyer can discover any product in any aisle. As tough as issues are proper now, that is one silver lining of real worth to grocers and their entrepreneurs.

Summing up

The dominant traits of Google’s high ranked grocery shops within the 50 US capitals are:

Being situated within the metropolis specified within the search

Engaging in GMB touchdown web page PA within the 40 vary

Not counting on spamming GMB enterprise titles

Utilizing “grocery store” as their major class

Successful a Four+ star score

Being closely reviewed and having acquired a evaluation within the final week

Receiving leads within the type of Q&A

Providing supply and curbside procuring choices

Requiring masks

The important thing areas of GMB alternative that aren’t but being utilized by this group to guard dominant visibility are:

Customer support within the type of evaluation responses

Lead administration within the type of solutions to Q&A

PR within the type of Google Posts

The grocery trade is present process a interval of serious problem and alternative encompassing:

The problem of digitizing stock

The problem of managing the complete client expertise with supply and curbside service to keep away from being minimize out by third events and to drastically improve security

The chance of promoting to clients in new methods by fulfilling new wants

The chance of constructing everlasting loyalty by creating memorable experiences of care and satisfaction through the pandemic that can inform post-pandemic relationships

I need to shut with a thank-you observe to my favourite, great-hearted neighborhood grocer — a family-owned nation retailer in a rural space. You discovered me ice throughout an influence shutoff within the midst of a fireplace, you discovered me bathtub tissue through the scarcity, and locally-distilled hand sanitizer to maintain my household secure. You arrange curbside pickup to guard me, and when my automobile was out of service, your loved ones supplied to convey groceries to my dwelling, regardless that you don’t but have the workers for a full supply service.

My grateful loyalty is yours.

As a neighborhood search marketer, I could take a look at knowledge, I could share numbers, however actually what I’m occupied with is individuals. Folks feeding the nation, deserved of each safety and safeguard ingenuity can devise to get us via these onerous occasions collectively. In the event you’re operating or marketing a grocery retailer and have native website positioning questions, please ask them within the feedback and I’ll do my greatest to offer useful solutions to help your success. Thanks for all that you just’re doing!

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Content Optimization - The Ultimate Search Engine Optimization Solution

Analysis has always been an important part of my work in SEO…

In the past, I was even one step ahead of my competitors. Because of this I was enabled to outrank big competitors with quite large budgets. If I tried a bit harder I would have been able to attain some position over time until I hit the first result.

Life was good, but it requires hard work…

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Over time, this is no longer a secret, but thanks to tools like Surfer. It is also not so difficult. The whole process has become less time-consuming, and having everything in one place is very convenient.

What has not changed for me is that I am still approaching this as always, and this may be slightly different from how some people use these tools.

In this article I want to show you how I use surfers with the same process that I first started using a few years ago … Let me show you how I use progressive optimization to guide decision making. I use and focus on 80/20 factors to move the needle fast.

Things to Keep In Mind

Progressive Optimization

An important difference between the progressive optimization approach and other approaches is that you spend most of your time optimizing your site and site content after posting.

This means that you spend a lot of time returning to your content, making small changes here and there, before returning to make changes later.

Depending on what type of optimization you are doing, you will need a variety of tools.

Where to Start?

When it comes to progressively optimizing your content, you’ll want to choose where to start.

Progressive optimization is not suitable for making many changes at the same time … because we are trying to maximize the separation of data.

If you made 5 changes on the page, and your rating improved by 6 positions. What changes were most significant?

What if the 4th change had a positive effect, and the 5th change failed?

What if you improved 8 positions without changing the 5th?

That is the method we think, and it is why we need to narrow the focus of any given round of changes.

This is because it is called progressive because we make the quick changes to try and achieve the best possible result sometime in the future.

The Power Factors

So, when you choose things to optimize for the first time, what are you going to focus on?

As a rule, it is the factors that have the greatest impact on your rating.

In true Pareto theory, it often seems that these factors make up 20%, giving you 80% of your results.

Let’s call them the Power Factors.

Page Title

URL

H1

H2, H3, H4, H5, H6

Term Frequency

“Important Terms”

Surfer gives you excellent data on most of these. The factors that I pay attention to in this article are those that I regularly use for any page that I optimize.

Other Tools You Need

These are not many tools. These tools are very useful things which will make your work a lot easier.

As I already told you, one of the things that has changed over the years is access to tools like surfers that make my life a lot easier. But there are some things that I have not changed over the past few years… 

I am still using a changelog to log what alterations were made, when they were made, and on what pages.

I am still using SERP Checkers and Spreadsheets to monitor & log results over time.

I am still using comparison matrices for visualizing opportunities (more on this later).

I am still using optimization calendars to plan what changes are being made to what pages and when. As well as what dates to go back and log the changes!

Since we spend time between changes, it can be easy to forget what you did and when.

It is also important to know what you have done so that you can undo these changes if the result does not work. It’s important to use backup and modification controls, as the third version of your page may have a higher rating than version 1, but not better than version 2, etc.

Break it Down

What Are The Different Types Of SEO?

At Syndiket, we believe four types of SEO exist – and we have an acronym to represent those 4 types of SEO. The acronym is T.R.A.P. 

“T” stands for Technical, “R” stands for Relevancy, “A” stands for Authority, and “P” stands for popularity. Search engine optimization has many smaller divisions within the 4 types, but all of them can be placed into one of these 4 buckets.

I’m Interested!

Technical SEO

Generally, technical SEO for local businesses carry the least importance for ranking. Technical SEO has a bare minimum that is required and this usually includes things like site speed, indexation issues, crawlability, and schema. Once the core technical parts are done, minimal upkeep is required.

Relevancy SEO

Relevancy is one of trivium elements of SEO. It has equal importance with popularity signals and authority signals. Relevancy signals are based on algorithmic learning principles. Bots crawl the internet every time a searcher has a search. Each search is given a relevancy score and the URLs that pop up for a query. The higher the relevancy score you attain, the greater your aggregated rating becomes in Google’s eyes. Digital marketing is a strange thing in 2020, and ranking a website requires the website to be relevant on many fronts.

Authority SEO

Google’s Co-creator, Larry Page, had a unique idea in 1998 which has led to the modern-day Google Empire. “Page Rank”, named after Larry Page himself, was the algorithm that established Google as a search engine giant. The algorithm ranked websites by authority. 

Every page of a website has authority and the sum of all pages has another authority metric. The authority metric is largely determined by how many people link to them (backlinks). The aggregate score of all pages pointing to a domain creates the domain score, which is what Syndiket calls “Domain Rating”, per Ahrefs metrics. The more a site is referenced, the more authority it has. But, the real improvement to the algorithm came when Google began to classify authority weight. 

If Tony Hawk endorsed Syndiket for skateboarding, it would carry a lot more authority than 5 random high school kids endorsing Syndiket. This differentiation in authority happened in 2012 with the Penguin update. Authority SEO is complicated but VERY important.

Popularity

Popularity signals are especially strong for GMB or local SEO, but popularity and engagement are used for all rankings. The goal of this signal is for Google to verify its own algorithm. You can check off all the boxes, but if your content is something real people hate, Google has ways to measure that. Syndiket has proprietary methods of controlling CTR (click-through rate) but we also infuse CRO methods into our work to make sure people actually like the content. Social shares and likes are also included in this bucket.

I’m Interested!

How To Use Surfer Like A Progressive Optimizer:

Step 1: Pick Your Target Page

The first step is to select your target page.

If you have an informational site, such as an affiliate site you might have to pick a page that is ranking between positions 8 and 14 for your primary target keyword.

Step 2: Identify Your 3 Main Keywords

After defining your target page, it’s time to identify your main target keywords.

Choose the three main target keywords.

Ideally, this should be permutations, alternative, or at least having the same intent and meaning.

Note: If you don’t have targeted keywords yet, you can always use the Surfer general keywords, phrases, or keywords and phrases function to help you identify some good keywords.

I think that getting the best overall results requires an analysis of some of the other related keywords that you’re targeting on your page.

Due to the amount of data available to you in Surfer, it is also more important to use the 80/20 rule the tool to “power factor” when analyzing multiple keywords per page.

Step 3: Identify Your Target Device

A very important feature of Surfer is the ability to analyze and analyze search results on your desktop or mobile devices.

Although most sites currently use the “Mobile First” index, this does not mean that the desktop does not matter.

Although most sites currently use the “Mobile First” index, this does not mean that the desktop does not matter.

First, John Muller, a Google employee, confirmed that they still provide 2: 1 desktop computers on mobile-oriented sites.

Yes, we have pages with both desktop & mobile user-agents. Mostly it is something like a 2-3:1 split, so when we transfer to mobile first indexing for a domain, it is 2/3rd mobile, 1/3rd desktop (the numbers are not fix, it is just what I usually see) 

More importantly. Mobile search results and desktop search results are different!

It is important to understand from which device your audience performs most of its searches, as you can optimize for the device from which you will receive the most traffic.

Step 4: Search & Filter Non-Relevant Results

Now you have given your keywords time to search.

Once the report is ready, you can move on to your results.

And now, thanks to a really good filtering tool, you can use the visibility icon (in the image below) to remove irrelevant results from your analysis.

Do it carefully, they come out because Google thinks it’s relevant. But equally, sometimes in the search results there are some real clangers in the SERPs that cannot be compared with your own site.

Optional extra filtering option: Turn off Averages.

You can turn off averages if you need to isolate the exact numbers for specific results.

This can be helpful if you have already optimized within averages, and are now trying to make results better by optimizing “up or down”.

I would recommend doing this after having already optimized your article for the ‘averages’.

Step 5: Log The Results For Your Focus Factor

Since it may take several weeks before returning to SERP to optimize one of the other factors, it is best to record the results for your focus factor.

Thus, when you return later to optimize any other factor, you can update your results and record data to the maximum.

You should log these factors in a comparison matrix for easy visualization:

This makes it easy to come back later and means you don’t have to constantly switch between the thoughts of the surfer. This is not what you should do, but it helps me to have

Here are some quick shortcuts for some of the “power factors” I’ve recommended analyzing and optimizing with:

Body > Exact Keywords

Title > Exact Keywords

Headings > H1 > Exact Keywords

Headings > H2 > Exact Keywords

Paragraphs > Exact Keywords

If you regularly use surfers, it is possible that you know where to find most of them, but I agree that I had a hidden motive here.

I wanted you to notice a pattern…

If you saw this, you may ask why I pay so much attention to “exact keywords.” And this is amazing, and I want to tell you why I do it.

Methods like TF-IDF, Density and True Density all use Term Frequency or “Keyword Frequency” as basic parts of their calculations.

I find it easier to use this basic data layer to optimize my sites.

It doesn’t matter what methods come and go, the main question of how many times was this word used will always be vital in some way.

You can use whatever you want, but would suggest you to follow my tutorials step by step.

Step 6: Setting Up Your Campaign Tracker

This step does not require anything special…

A simple spreadsheet with dates, keywords and status will do.

You don’t have to do anything special here; you can log changes daily, weekly or every 10 days…

Everything that works for you and your goals is in order. Logging data at “some” intervals is better than not logging.

Step 7: Setting Up Your Optimization Calendar

Source: https://www.hydratight.com/pt-br/resources/blogs/2016/12/dont-fail-prepare

Calendars are mainly used in our industry for meetings, social media and many more events 

It would be prudent to have a calendar for your optimization work too

In order to have progressive optimization, optimization calendar is essential. 

It makes you more efficient and effective.

Allows you to register changes in the campaign tracker, make new changes on your page and do the latest analysis on Surfer — all in a timely order. It can be a lot to keep on top of if you are doing this for multiple pages and sites.

Step 8: Setting Up Your Changelog

The only thing you must need in place is your changelog.

A changelog is important to keep track of what you are actually doing. Optimization is important for many of the same reasons as a calendar, campaign tracker, etc.

The best results, with progressive optimization, require a degree of organization with your workflow and processes regardless of the tools you are using.

You can find other ways around using the files. What you can’t do is find an alternate way around using a changelog.

To make this simple I am sharing a very basic changelog template for those of you who want to use it.

[FREE] Google Sheets Changelog Template: Click to make a copy.

Step 9: Start Optimizing

At this point there is nothing more to say other than go out there and get optimizing!

You have everything you need to get started =]

Worthy Mentions

There are many other features that I find really useful when using surfers for optimization purposes.

You can use them as part of the procedures described above or separately. No matter what you choose, if you are new to this tool, you should definitely be aware of these things.

Important Terms

We explained these as one of the “power factors”. Whereas some find it controversial, I as well as many others, and the folks at Surfer have all had pretty good results including terms that are expected to be seen in pieces of content.

Surfer helps you to find these easily by providing you access to common words and common phrases…

Quick Audit 

 “Surfer Audit” is one of my favorite features.

You can perform an audit to see how you stack up by isolating your URL in the results, or by adding it manually

This can be very useful for collecting data early, quickly checking or viewing the form of your site after a progressive optimization campaign.

It gives you some actionable term frequency recommendations.

It will also help you in pointing out any obvious issues where they arise (usually when well outside of the average).

Conclusion

There is no single way to use tools like Surfer. Although many prefer to use it to optimize content before publishing, or even change many things after publication I hope I have shown that you can use whatever approach you want as long as the system is well thought out.

Want More Info?

Let’s Chat!

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Content Optimization - The Ultimate Search Engine Optimization Solution

Analysis has always been an important part of my work in SEO…

In the past, I was even one step ahead of my competitors. Because of this I was enabled to outrank big competitors with quite large budgets. If I tried a bit harder I would have been able to attain some position over time until I hit the first result.

Life was good, but it requires hard work…

Get In Touch

Over time, this is no longer a secret, but thanks to tools like Surfer. It is also not so difficult. The whole process has become less time-consuming, and having everything in one place is very convenient.

What has not changed for me is that I am still approaching this as always, and this may be slightly different from how some people use these tools.

In this article I want to show you how I use surfers with the same process that I first started using a few years ago … Let me show you how I use progressive optimization to guide decision making. I use and focus on 80/20 factors to move the needle fast.

Things to Keep In Mind

Progressive Optimization

An important difference between the progressive optimization approach and other approaches is that you spend most of your time optimizing your site and site content after posting.

This means that you spend a lot of time returning to your content, making small changes here and there, before returning to make changes later.

Depending on what type of optimization you are doing, you will need a variety of tools.

Where to Start?

When it comes to progressively optimizing your content, you’ll want to choose where to start.

Progressive optimization is not suitable for making many changes at the same time … because we are trying to maximize the separation of data.

If you made 5 changes on the page, and your rating improved by 6 positions. What changes were most significant?

What if the 4th change had a positive effect, and the 5th change failed?

What if you improved 8 positions without changing the 5th?

That is the method we think, and it is why we need to narrow the focus of any given round of changes.

This is because it is called progressive because we make the quick changes to try and achieve the best possible result sometime in the future.

The Power Factors

So, when you choose things to optimize for the first time, what are you going to focus on?

As a rule, it is the factors that have the greatest impact on your rating.

In true Pareto theory, it often seems that these factors make up 20%, giving you 80% of your results.

Let’s call them the Power Factors.

Page Title

URL

H1

H2, H3, H4, H5, H6

Term Frequency

“Important Terms”

Surfer gives you excellent data on most of these. The factors that I pay attention to in this article are those that I regularly use for any page that I optimize.

Other Tools You Need

These are not many tools. These tools are very useful things which will make your work a lot easier.

As I already told you, one of the things that has changed over the years is access to tools like surfers that make my life a lot easier. But there are some things that I have not changed over the past few years… 

I am still using a changelog to log what alterations were made, when they were made, and on what pages.

I am still using SERP Checkers and Spreadsheets to monitor & log results over time.

I am still using comparison matrices for visualizing opportunities (more on this later).

I am still using optimization calendars to plan what changes are being made to what pages and when. As well as what dates to go back and log the changes!

Since we spend time between changes, it can be easy to forget what you did and when.

It is also important to know what you have done so that you can undo these changes if the result does not work. It’s important to use backup and modification controls, as the third version of your page may have a higher rating than version 1, but not better than version 2, etc.

Break it Down

What Are The Different Types Of SEO?

At Syndiket, we believe four types of SEO exist – and we have an acronym to represent those 4 types of SEO. The acronym is T.R.A.P. 

“T” stands for Technical, “R” stands for Relevancy, “A” stands for Authority, and “P” stands for popularity. Search engine optimization has many smaller divisions within the 4 types, but all of them can be placed into one of these 4 buckets.

I'm Interested!

Technical SEO

Generally, technical SEO for local businesses carry the least importance for ranking. Technical SEO has a bare minimum that is required and this usually includes things like site speed, indexation issues, crawlability, and schema. Once the core technical parts are done, minimal upkeep is required.

Relevancy SEO

Relevancy is one of trivium elements of SEO. It has equal importance with popularity signals and authority signals. Relevancy signals are based on algorithmic learning principles. Bots crawl the internet every time a searcher has a search. Each search is given a relevancy score and the URLs that pop up for a query. The higher the relevancy score you attain, the greater your aggregated rating becomes in Google’s eyes. Digital marketing is a strange thing in 2020, and ranking a website requires the website to be relevant on many fronts.

Authority SEO

Google’s Co-creator, Larry Page, had a unique idea in 1998 which has led to the modern-day Google Empire. “Page Rank”, named after Larry Page himself, was the algorithm that established Google as a search engine giant. The algorithm ranked websites by authority. 

Every page of a website has authority and the sum of all pages has another authority metric. The authority metric is largely determined by how many people link to them (backlinks). The aggregate score of all pages pointing to a domain creates the domain score, which is what Syndiket calls “Domain Rating”, per Ahrefs metrics. The more a site is referenced, the more authority it has. But, the real improvement to the algorithm came when Google began to classify authority weight. 

If Tony Hawk endorsed Syndiket for skateboarding, it would carry a lot more authority than 5 random high school kids endorsing Syndiket. This differentiation in authority happened in 2012 with the Penguin update. Authority SEO is complicated but VERY important.

Popularity

Popularity signals are especially strong for GMB or local SEO, but popularity and engagement are used for all rankings. The goal of this signal is for Google to verify its own algorithm. You can check off all the boxes, but if your content is something real people hate, Google has ways to measure that. Syndiket has proprietary methods of controlling CTR (click-through rate) but we also infuse CRO methods into our work to make sure people actually like the content. Social shares and likes are also included in this bucket.

I'm Interested!

How To Use Surfer Like A Progressive Optimizer:

Step 1: Pick Your Target Page

The first step is to select your target page.

If you have an informational site, such as an affiliate site you might have to pick a page that is ranking between positions 8 and 14 for your primary target keyword.

Step 2: Identify Your 3 Main Keywords

After defining your target page, it’s time to identify your main target keywords.

Choose the three main target keywords.

Ideally, this should be permutations, alternative, or at least having the same intent and meaning.

Note: If you don’t have targeted keywords yet, you can always use the Surfer general keywords, phrases, or keywords and phrases function to help you identify some good keywords.

I think that getting the best overall results requires an analysis of some of the other related keywords that you’re targeting on your page.

Due to the amount of data available to you in Surfer, it is also more important to use the 80/20 rule the tool to “power factor” when analyzing multiple keywords per page.

Step 3: Identify Your Target Device

A very important feature of Surfer is the ability to analyze and analyze search results on your desktop or mobile devices.

Although most sites currently use the “Mobile First” index, this does not mean that the desktop does not matter.

Although most sites currently use the “Mobile First” index, this does not mean that the desktop does not matter.

First, John Muller, a Google employee, confirmed that they still provide 2: 1 desktop computers on mobile-oriented sites.

Yes, we have pages with both desktop & mobile user-agents. Mostly it is something like a 2-3:1 split, so when we transfer to mobile first indexing for a domain, it is 2/3rd mobile, 1/3rd desktop (the numbers are not fix, it is just what I usually see) 

More importantly. Mobile search results and desktop search results are different!

It is important to understand from which device your audience performs most of its searches, as you can optimize for the device from which you will receive the most traffic.

Step 4: Search & Filter Non-Relevant Results

Now you have given your keywords time to search.

Once the report is ready, you can move on to your results.

And now, thanks to a really good filtering tool, you can use the visibility icon (in the image below) to remove irrelevant results from your analysis.

Do it carefully, they come out because Google thinks it’s relevant. But equally, sometimes in the search results there are some real clangers in the SERPs that cannot be compared with your own site.

Optional extra filtering option: Turn off Averages.

You can turn off averages if you need to isolate the exact numbers for specific results.

This can be helpful if you have already optimized within averages, and are now trying to make results better by optimizing “up or down”.

I would recommend doing this after having already optimized your article for the ‘averages’.

Step 5: Log The Results For Your Focus Factor

Since it may take several weeks before returning to SERP to optimize one of the other factors, it is best to record the results for your focus factor.

Thus, when you return later to optimize any other factor, you can update your results and record data to the maximum.

You should log these factors in a comparison matrix for easy visualization:

This makes it easy to come back later and means you don’t have to constantly switch between the thoughts of the surfer. This is not what you should do, but it helps me to have

Here are some quick shortcuts for some of the “power factors” I’ve recommended analyzing and optimizing with:

Body > Exact Keywords

Title > Exact Keywords

Headings > H1 > Exact Keywords

Headings > H2 > Exact Keywords

Paragraphs > Exact Keywords

If you regularly use surfers, it is possible that you know where to find most of them, but I agree that I had a hidden motive here.

I wanted you to notice a pattern…

If you saw this, you may ask why I pay so much attention to “exact keywords.” And this is amazing, and I want to tell you why I do it.

Methods like TF-IDF, Density and True Density all use Term Frequency or “Keyword Frequency” as basic parts of their calculations.

I find it easier to use this basic data layer to optimize my sites.

It doesn’t matter what methods come and go, the main question of how many times was this word used will always be vital in some way.

You can use whatever you want, but would suggest you to follow my tutorials step by step.

Step 6: Setting Up Your Campaign Tracker

This step does not require anything special…

A simple spreadsheet with dates, keywords and status will do.

You don’t have to do anything special here; you can log changes daily, weekly or every 10 days…

Everything that works for you and your goals is in order. Logging data at “some” intervals is better than not logging.

Step 7: Setting Up Your Optimization Calendar

Source: https://www.hydratight.com/pt-br/resources/blogs/2016/12/dont-fail-prepare

Calendars are mainly used in our industry for meetings, social media and many more events 

It would be prudent to have a calendar for your optimization work too

In order to have progressive optimization, optimization calendar is essential. 

It makes you more efficient and effective.

Allows you to register changes in the campaign tracker, make new changes on your page and do the latest analysis on Surfer — all in a timely order. It can be a lot to keep on top of if you are doing this for multiple pages and sites.

Step 8: Setting Up Your Changelog

The only thing you must need in place is your changelog.

A changelog is important to keep track of what you are actually doing. Optimization is important for many of the same reasons as a calendar, campaign tracker, etc.

The best results, with progressive optimization, require a degree of organization with your workflow and processes regardless of the tools you are using.

You can find other ways around using the files. What you can’t do is find an alternate way around using a changelog.

To make this simple I am sharing a very basic changelog template for those of you who want to use it.

[FREE] Google Sheets Changelog Template: Click to make a copy.

Step 9: Start Optimizing

At this point there is nothing more to say other than go out there and get optimizing!

You have everything you need to get started =]

Worthy Mentions

There are many other features that I find really useful when using surfers for optimization purposes.

You can use them as part of the procedures described above or separately. No matter what you choose, if you are new to this tool, you should definitely be aware of these things.

Important Terms

We explained these as one of the “power factors”. Whereas some find it controversial, I as well as many others, and the folks at Surfer have all had pretty good results including terms that are expected to be seen in pieces of content.

Surfer helps you to find these easily by providing you access to common words and common phrases…

Quick Audit 

 “Surfer Audit” is one of my favorite features.

You can perform an audit to see how you stack up by isolating your URL in the results, or by adding it manually

This can be very useful for collecting data early, quickly checking or viewing the form of your site after a progressive optimization campaign.

It gives you some actionable term frequency recommendations.

It will also help you in pointing out any obvious issues where they arise (usually when well outside of the average).

Conclusion

There is no single way to use tools like Surfer. Although many prefer to use it to optimize content before publishing, or even change many things after publication I hope I have shown that you can use whatever approach you want as long as the system is well thought out.

Want More Info?

Let's Chat!

Name

Company

Email Address

Campaign Scale

LocalStateNationalGlobal

Niche

Message

Submit

I am text block. Click edit button to change this text. Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper matti pibus leo.

Facebook-f Youtube Twitter Instagram

Services

SEO

PPC

Web Design

Branding

Consulting

Other

About Us

Case Studies

Learn

Tools

Careers

Locations

Nashville, TN

Chattanooga, TN

New York, NY

San Francisco, CA

Denver, CO

Syndiket Marketing © 2020 All rights reserved

Made with

in Nashville, TN

from Syndiket Marketing | SEO, Adwords, Web Design https://www.syndiket.com/services/seo-content/content-optimization/

[lxryrestate28349]

Will It Blend? Google Data Studio Rolls out Data Blending

Will It Blend? Google Data Studio Rolls out Data Blending

We knew it was coming, we waited for it, and now it’s finally here! Data blending is in Google Analytics, and it. is. glorious. The nice part about being the upcomer on the data viz scene is that the playbook is already scripted out, the questions become “which features do we prioritize?” and “when?”. The exact way that features are implemented can be drastically different but the underlying principles are the same, like joining data sources or as Data Studio calls it, ‘data blending’.

Data Studio has a couple of tricks up its sleeve, mainly it’s giant network of natively integrated awesome tools. (Check out the BigQuery connector!)

To catch us up, let’s review. Data Studio is the free visualization tool from Google. Built on the Google Drive technology, easy to create, collaborate, and share unlimited reports. We love our Google tools like Google Analytics and Google AdWords, so of course we love to use Data Studio to create great visualizations for our clients and blog readers. Also, of course, one of the best benefits of Data Studio is that we can visualize any data and others have created great ways to bring in non-Google data.

Which brings us back to the business at hand; let’s talk more about data blending and how you can immediately use this feature to make your life easier.

How To Blend Data in Google Data Studio

This feature is supposedly rolling out as of July 10, the day of the Google Marketing Live event. Already people are tweeting about the awesomeness. Check your Data Studio reports to see if you have it by clicking on any report element, then looking at the Data Source portion on the Data pane.

If you have Data Blending, you’ll see an option underneath your Data Source that says “Blend Data.”

If you don’t see it, don’t panic. Clear your cookies and refresh the page, log back in, and check again. If you still don’t see it, just wait a couple days and hopefully it shows up.

Blending Data Sources on a Common Key

Clicking on the Blend Data button will reveal a lower panel to help make this process easy. It will use your current data source and invite you to Add Another Data Source. The entire premise behind joining data together is to find a common piece of data in both data sets to connect on.

These Join keys don’t need to be named the same in both data sources but need to have the same data. It’s the same concept everywhere – we have two data sources and they have to have something in common for us to join them. Sometimes it’s a Page URL, sometimes it’s a date, or it can be internal user IDs.

For a simple Table element, drag and drop the dimension you want use to join, and then select which metrics you want to appear as columns.

Give your Blended Data Source a name, preferably mentioning both original data sources, then Close the Blend Data panel.

It’s important to note that you’re creating a new data source, that just contains the blended data: the common key and the dimensions and metrics that you selected. You won’t have both full data sources available to you all the time, only the fields that you explicitly put into this joined table, or blended data source.

Combine Charts Together with Data Blending

If you want to combine chart elements, this becomes even easier. If you’ve ever made two chart elements and strategically layered them on top of each other, prepare to be amazed.

First, pick two or more data sources you’d like to graph together. For instance, if you ever wanted to graph Google Search Console impressions, Google Ads impressions, and Google Analytics Pageviews all in the same graph, now you can.

Start by adding each graph individually. I picked a Search Console data source, a Google AdWords data source, and a Google Analytics source (with greatly modified numbers) and added them all to my report.

Then, to easily combine these charts, hold down CTRL or SHIFT and click on all chart elements, or draw a box around both of them to select all. You can select between 2 and 5 elements. Then, right-click and choose Blend Data.

Data Studio will automatically make you a new blended Data Source, with the common key being the date. It adds this data source to the report and combines these elements into a chart. Voila! (I tweaked my graph to adjust colors and renamed my metrics to make it a little more clear.)

Compare Performance Across Platforms

When you’re using different tools or providing different services to clients, it’s often a staple to be able to see all of these metrics together. Combining data in Excel, Sheets, or other platforms can become tedious or challenging.

At this time, data blending doesn’t seem to support calculations across data sources, but at least we can get them together in the same table, chart, etc. This allows us to see the information at one glance, and (this is a big plus!) easily use the same data and dimension filters to adjust all the elements at the same time.

Note: It will be more important than ever to have consistent naming conventions across your marketing channels. Imagine paid search campaigns that all indicate branded vs non-branded in the campaign name. You can view performance together, or drill down into a specific type of campaign.

Bringing In Personal and Meta Data

Now we’re talking. How about blending Google Analytics data with our Salesforce or our CRM system? Again, this all hinges on getting a common key in both platforms. We’ve written about this extensively. A key to pass between systems is often your Google Analytics client ID. You can store it in Google Analytics as a custom dimension, and pass it into your systems using forms or other mechanisms.

In the example below, I connected a Google Analytics data source with a client ID custom dimension, and a report from my Salesforce account that listed Client IDs and Company Names. Blended together, I can create an easily updatable report showing me which sections of the site companies are visiting, with a drop-down to focus in on a particular company.

Imagine what else we can do by combining these data sources! Sales regions can be mapped and reported on in aggregate or by sales team member. Conversion data from GA can be viewed alongside Salesforce information. Name, company, purchase history – all together!

Add Context To Performance

Some of the best applications will be taking real-world information and combining it with our online data. Weather data has often been called out as something we can track and combine. In five minutes, I pulled weather history for July, dropped that into a spreadsheet, and joined that with a Google Analytics property.

Do these two things have anything in common? From the graph, it’s clear, no, not really. But if you work in a seasonal or outdoor company, perhaps you have a direct need for this. Imagine what other data sources could help provide real-world context when blended together.

A few additional ideas:

Chart code changes against key site performance metrics.

Look at calendar or offline events data next to digital conversion rates.

Track ecommerce performance next to total company sales.

Compare Goals Across Google Analytics Views

Ok, this one’s amazing. Google Analytics has a limit of 20 goals per view. Yikes, ouch. No way around this, this one doesn’t even get better with Google Analytics 360. I’m not sure anyone really needs more than 20 goals, but if you do, a common workaround is to create multiple views and get 20 more goals to play with.

But now, you’ve got a tough reporting challenge – you need to grab data from two or more different views and combine them together in some sort of report. This sounds like a job for data blending! If you have two different GA views with the same info, but different goals, keep going.

Add one GA View as a data source to your report

Click Blend Data

Add the other GA View as another data source

Combine on a session-level dimension like Source/Medium, Default Channel Grouping, or Landing Page

Add Goals from each of the data sources

Compare Data Across Google Analytics Properties

Managing multiple websites? Different properties for the same company? Agencies managing multiple clients? It’s easier than ever to combine data to get a holistic report across all of your data needs.

Email Campaigns vs Website Performance

Here’s another great use case – bring in data about a specific campaign and compare open rates and click-through rates in the same table as website performance, goals completed, and Ecommerce performance.

Fun Ideas

We’ve written before about fun use cases for Data Studio, and how our team literally uses for real-world scenarios like health performance, financial monitoring, and more!

“I use Data Studio outside of work to track my small investment portfolio. Blended metrics will save me time spent in spreadsheets and allow me to quickly visualize performance of multiple data sources and better track overall goals.”

Michael Bartholow Senior Manager, Digital Marketing Strategy

Get Blending!

The power is in your hands – start playing around with blended data and see how it can help you! While a lot of this functionality was available in other platforms or programs, remember that we can now blend data sources with all of the additional benefits of Google Data Studio: easy to create, easy to share, easy to refresh.

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Will It Blend? Google Data Studio Rolls out Data Blending

Will It Blend? Google Data Studio Rolls out Data Blending

We knew it was coming, we waited for it, and now it’s finally here! Data blending is in Google Analytics, and it. is. glorious. The nice part about being the upcomer on the data viz scene is that the playbook is already scripted out, the questions become “which features do we prioritize?” and “when?”. The exact way that features are implemented can be drastically different but the underlying principles are the same, like joining data sources or as Data Studio calls it, ‘data blending’.

Data Studio has a couple of tricks up its sleeve, mainly it’s giant network of natively integrated awesome tools. (Check out the BigQuery connector!)

To catch us up, let’s review. Data Studio is the free visualization tool from Google. Built on the Google Drive technology, easy to create, collaborate, and share unlimited reports. We love our Google tools like Google Analytics and Google AdWords, so of course we love to use Data Studio to create great visualizations for our clients and blog readers. Also, of course, one of the best benefits of Data Studio is that we can visualize any data and others have created great ways to bring in non-Google data.

Which brings us back to the business at hand; let’s talk more about data blending and how you can immediately use this feature to make your life easier.

How To Blend Data in Google Data Studio

This feature is supposedly rolling out as of July 10, the day of the Google Marketing Live event. Already people are tweeting about the awesomeness. Check your Data Studio reports to see if you have it by clicking on any report element, then looking at the Data Source portion on the Data pane.

If you have Data Blending, you’ll see an option underneath your Data Source that says “Blend Data.”

If you don’t see it, don’t panic. Clear your cookies and refresh the page, log back in, and check again. If you still don’t see it, just wait a couple days and hopefully it shows up.

Blending Data Sources on a Common Key

Clicking on the Blend Data button will reveal a lower panel to help make this process easy. It will use your current data source and invite you to Add Another Data Source. The entire premise behind joining data together is to find a common piece of data in both data sets to connect on.

These Join keys don’t need to be named the same in both data sources but need to have the same data. It’s the same concept everywhere – we have two data sources and they have to have something in common for us to join them. Sometimes it’s a Page URL, sometimes it’s a date, or it can be internal user IDs.

For a simple Table element, drag and drop the dimension you want use to join, and then select which metrics you want to appear as columns.

Give your Blended Data Source a name, preferably mentioning both original data sources, then Close the Blend Data panel.

It’s important to note that you’re creating a new data source, that just contains the blended data: the common key and the dimensions and metrics that you selected. You won’t have both full data sources available to you all the time, only the fields that you explicitly put into this joined table, or blended data source.

Combine Charts Together with Data Blending

If you want to combine chart elements, this becomes even easier. If you’ve ever made two chart elements and strategically layered them on top of each other, prepare to be amazed.

First, pick two or more data sources you’d like to graph together. For instance, if you ever wanted to graph Google Search Console impressions, Google Ads impressions, and Google Analytics Pageviews all in the same graph, now you can.

Start by adding each graph individually. I picked a Search Console data source, a Google AdWords data source, and a Google Analytics source (with greatly modified numbers) and added them all to my report.

Then, to easily combine these charts, hold down CTRL or SHIFT and click on all chart elements, or draw a box around both of them to select all. You can select between 2 and 5 elements. Then, right-click and choose Blend Data.

Data Studio will automatically make you a new blended Data Source, with the common key being the date. It adds this data source to the report and combines these elements into a chart. Voila! (I tweaked my graph to adjust colors and renamed my metrics to make it a little more clear.)

Compare Performance Across Platforms

When you’re using different tools or providing different services to clients, it’s often a staple to be able to see all of these metrics together. Combining data in Excel, Sheets, or other platforms can become tedious or challenging.

At this time, data blending doesn’t seem to support calculations across data sources, but at least we can get them together in the same table, chart, etc. This allows us to see the information at one glance, and (this is a big plus!) easily use the same data and dimension filters to adjust all the elements at the same time.

Note: It will be more important than ever to have consistent naming conventions across your marketing channels. Imagine paid search campaigns that all indicate branded vs non-branded in the campaign name. You can view performance together, or drill down into a specific type of campaign.

Bringing In Personal and Meta Data

Now we’re talking. How about blending Google Analytics data with our Salesforce or our CRM system? Again, this all hinges on getting a common key in both platforms. We’ve written about this extensively. A key to pass between systems is often your Google Analytics client ID. You can store it in Google Analytics as a custom dimension, and pass it into your systems using forms or other mechanisms.

In the example below, I connected a Google Analytics data source with a client ID custom dimension, and a report from my Salesforce account that listed Client IDs and Company Names. Blended together, I can create an easily updatable report showing me which sections of the site companies are visiting, with a drop-down to focus in on a particular company.

Imagine what else we can do by combining these data sources! Sales regions can be mapped and reported on in aggregate or by sales team member. Conversion data from GA can be viewed alongside Salesforce information. Name, company, purchase history – all together!

Add Context To Performance

Some of the best applications will be taking real-world information and combining it with our online data. Weather data has often been called out as something we can track and combine. In five minutes, I pulled weather history for July, dropped that into a spreadsheet, and joined that with a Google Analytics property.

Do these two things have anything in common? From the graph, it’s clear, no, not really. But if you work in a seasonal or outdoor company, perhaps you have a direct need for this. Imagine what other data sources could help provide real-world context when blended together.

A few additional ideas:

Chart code changes against key site performance metrics.

Look at calendar or offline events data next to digital conversion rates.

Track ecommerce performance next to total company sales.

Compare Goals Across Google Analytics Views

Ok, this one’s amazing. Google Analytics has a limit of 20 goals per view. Yikes, ouch. No way around this, this one doesn’t even get better with Google Analytics 360. I’m not sure anyone really needs more than 20 goals, but if you do, a common workaround is to create multiple views and get 20 more goals to play with.

But now, you’ve got a tough reporting challenge – you need to grab data from two or more different views and combine them together in some sort of report. This sounds like a job for data blending! If you have two different GA views with the same info, but different goals, keep going.

Add one GA View as a data source to your report

Click Blend Data

Add the other GA View as another data source

Combine on a session-level dimension like Source/Medium, Default Channel Grouping, or Landing Page

Add Goals from each of the data sources

Compare Data Across Google Analytics Properties

Managing multiple websites? Different properties for the same company? Agencies managing multiple clients? It’s easier than ever to combine data to get a holistic report across all of your data needs.

Email Campaigns vs Website Performance

Here’s another great use case – bring in data about a specific campaign and compare open rates and click-through rates in the same table as website performance, goals completed, and Ecommerce performance.

Fun Ideas

We’ve written before about fun use cases for Data Studio, and how our team literally uses for real-world scenarios like health performance, financial monitoring, and more!

“I use Data Studio outside of work to track my small investment portfolio. Blended metrics will save me time spent in spreadsheets and allow me to quickly visualize performance of multiple data sources and better track overall goals.”

Michael Bartholow Senior Manager, Digital Marketing Strategy

Get Blending!

The power is in your hands – start playing around with blended data and see how it can help you! While a lot of this functionality was available in other platforms or programs, remember that we can now blend data sources with all of the additional benefits of Google Data Studio: easy to create, easy to share, easy to refresh.

https://ift.tt/2mddVEh

[repumktg61602]

Will It Blend? Google Data Studio Rolls out Data Blending

Will It Blend? Google Data Studio Rolls out Data Blending

We knew it was coming, we waited for it, and now it’s finally here! Data blending is in Google Analytics, and it. is. glorious. The nice part about being the upcomer on the data viz scene is that the playbook is already scripted out, the questions become “which features do we prioritize?” and “when?”. The exact way that features are implemented can be drastically different but the underlying principles are the same, like joining data sources or as Data Studio calls it, ‘data blending’.

Data Studio has a couple of tricks up its sleeve, mainly it’s giant network of natively integrated awesome tools. (Check out the BigQuery connector!)

To catch us up, let’s review. Data Studio is the free visualization tool from Google. Built on the Google Drive technology, easy to create, collaborate, and share unlimited reports. We love our Google tools like Google Analytics and Google AdWords, so of course we love to use Data Studio to create great visualizations for our clients and blog readers. Also, of course, one of the best benefits of Data Studio is that we can visualize any data and others have created great ways to bring in non-Google data.

Which brings us back to the business at hand; let’s talk more about data blending and how you can immediately use this feature to make your life easier.

How To Blend Data in Google Data Studio

This feature is supposedly rolling out as of July 10, the day of the Google Marketing Live event. Already people are tweeting about the awesomeness. Check your Data Studio reports to see if you have it by clicking on any report element, then looking at the Data Source portion on the Data pane.

If you have Data Blending, you’ll see an option underneath your Data Source that says “Blend Data.”

If you don’t see it, don’t panic. Clear your cookies and refresh the page, log back in, and check again. If you still don’t see it, just wait a couple days and hopefully it shows up.

Blending Data Sources on a Common Key

Clicking on the Blend Data button will reveal a lower panel to help make this process easy. It will use your current data source and invite you to Add Another Data Source. The entire premise behind joining data together is to find a common piece of data in both data sets to connect on.

These Join keys don’t need to be named the same in both data sources but need to have the same data. It’s the same concept everywhere – we have two data sources and they have to have something in common for us to join them. Sometimes it’s a Page URL, sometimes it’s a date, or it can be internal user IDs.

For a simple Table element, drag and drop the dimension you want use to join, and then select which metrics you want to appear as columns.

Give your Blended Data Source a name, preferably mentioning both original data sources, then Close the Blend Data panel.

It’s important to note that you’re creating a new data source, that just contains the blended data: the common key and the dimensions and metrics that you selected. You won’t have both full data sources available to you all the time, only the fields that you explicitly put into this joined table, or blended data source.

Combine Charts Together with Data Blending

If you want to combine chart elements, this becomes even easier. If you’ve ever made two chart elements and strategically layered them on top of each other, prepare to be amazed.

First, pick two or more data sources you’d like to graph together. For instance, if you ever wanted to graph Google Search Console impressions, Google Ads impressions, and Google Analytics Pageviews all in the same graph, now you can.

Start by adding each graph individually. I picked a Search Console data source, a Google AdWords data source, and a Google Analytics source (with greatly modified numbers) and added them all to my report.

Then, to easily combine these charts, hold down CTRL or SHIFT and click on all chart elements, or draw a box around both of them to select all. You can select between 2 and 5 elements. Then, right-click and choose Blend Data.

Data Studio will automatically make you a new blended Data Source, with the common key being the date. It adds this data source to the report and combines these elements into a chart. Voila! (I tweaked my graph to adjust colors and renamed my metrics to make it a little more clear.)

Compare Performance Across Platforms

When you’re using different tools or providing different services to clients, it’s often a staple to be able to see all of these metrics together. Combining data in Excel, Sheets, or other platforms can become tedious or challenging.

At this time, data blending doesn’t seem to support calculations across data sources, but at least we can get them together in the same table, chart, etc. This allows us to see the information at one glance, and (this is a big plus!) easily use the same data and dimension filters to adjust all the elements at the same time.

Note: It will be more important than ever to have consistent naming conventions across your marketing channels. Imagine paid search campaigns that all indicate branded vs non-branded in the campaign name. You can view performance together, or drill down into a specific type of campaign.

Bringing In Personal and Meta Data

Now we’re talking. How about blending Google Analytics data with our Salesforce or our CRM system? Again, this all hinges on getting a common key in both platforms. We’ve written about this extensively. A key to pass between systems is often your Google Analytics client ID. You can store it in Google Analytics as a custom dimension, and pass it into your systems using forms or other mechanisms.

In the example below, I connected a Google Analytics data source with a client ID custom dimension, and a report from my Salesforce account that listed Client IDs and Company Names. Blended together, I can create an easily updatable report showing me which sections of the site companies are visiting, with a drop-down to focus in on a particular company.

Imagine what else we can do by combining these data sources! Sales regions can be mapped and reported on in aggregate or by sales team member. Conversion data from GA can be viewed alongside Salesforce information. Name, company, purchase history – all together!

Add Context To Performance

Some of the best applications will be taking real-world information and combining it with our online data. Weather data has often been called out as something we can track and combine. In five minutes, I pulled weather history for July, dropped that into a spreadsheet, and joined that with a Google Analytics property.

Do these two things have anything in common? From the graph, it’s clear, no, not really. But if you work in a seasonal or outdoor company, perhaps you have a direct need for this. Imagine what other data sources could help provide real-world context when blended together.

A few additional ideas:

Chart code changes against key site performance metrics.

Look at calendar or offline events data next to digital conversion rates.

Track ecommerce performance next to total company sales.

Compare Goals Across Google Analytics Views

Ok, this one’s amazing. Google Analytics has a limit of 20 goals per view. Yikes, ouch. No way around this, this one doesn’t even get better with Google Analytics 360. I’m not sure anyone really needs more than 20 goals, but if you do, a common workaround is to create multiple views and get 20 more goals to play with.

But now, you’ve got a tough reporting challenge – you need to grab data from two or more different views and combine them together in some sort of report. This sounds like a job for data blending! If you have two different GA views with the same info, but different goals, keep going.

Add one GA View as a data source to your report

Click Blend Data

Add the other GA View as another data source

Combine on a session-level dimension like Source/Medium, Default Channel Grouping, or Landing Page

Add Goals from each of the data sources

Compare Data Across Google Analytics Properties

Managing multiple websites? Different properties for the same company? Agencies managing multiple clients? It’s easier than ever to combine data to get a holistic report across all of your data needs.

Email Campaigns vs Website Performance

Here’s another great use case – bring in data about a specific campaign and compare open rates and click-through rates in the same table as website performance, goals completed, and Ecommerce performance.

Fun Ideas

We’ve written before about fun use cases for Data Studio, and how our team literally uses for real-world scenarios like health performance, financial monitoring, and more!

“I use Data Studio outside of work to track my small investment portfolio. Blended metrics will save me time spent in spreadsheets and allow me to quickly visualize performance of multiple data sources and better track overall goals.”

Michael Bartholow Senior Manager, Digital Marketing Strategy

Get Blending!

The power is in your hands – start playing around with blended data and see how it can help you! While a lot of this functionality was available in other platforms or programs, remember that we can now blend data sources with all of the additional benefits of Google Data Studio: easy to create, easy to share, easy to refresh.

https://ift.tt/2mddVEh

[seo90210]

Will It Blend? Google Data Studio Rolls out Data Blending

We knew it was coming, we waited for it, and now it’s finally here! Data blending is in Google Analytics, and it. is. glorious. The nice part about being the upcomer on the data viz scene is that the playbook is already scripted out, the questions become “which features do we prioritize?” and “when?”. The exact way that features are implemented can be drastically different but the underlying principles are the same, like joining data sources or as Data Studio calls it, ‘data blending’.

Data Studio has a couple of tricks up its sleeve, mainly it’s giant network of natively integrated awesome tools. (Check out the BigQuery connector!)

To catch us up, let’s review. Data Studio is the free visualization tool from Google. Built on the Google Drive technology, easy to create, collaborate, and share unlimited reports. We love our Google tools like Google Analytics and Google AdWords, so of course we love to use Data Studio to create great visualizations for our clients and blog readers. Also, of course, one of the best benefits of Data Studio is that we can visualize any data and others have created great ways to bring in non-Google data.

Which brings us back to the business at hand; let’s talk more about data blending and how you can immediately use this feature to make your life easier.

How To Blend Data in Google Data Studio

This feature is supposedly rolling out as of July 10, the day of the Google Marketing Live event. Already people are tweeting about the awesomeness. Check your Data Studio reports to see if you have it by clicking on any report element, then looking at the Data Source portion on the Data pane.

If you have Data Blending, you’ll see an option underneath your Data Source that says “Blend Data.”

If you don’t see it, don’t panic. Clear your cookies and refresh the page, log back in, and check again. If you still don’t see it, just wait a couple days and hopefully it shows up.

Blending Data Sources on a Common Key

Clicking on the Blend Data button will reveal a lower panel to help make this process easy. It will use your current data source and invite you to Add Another Data Source. The entire premise behind joining data together is to find a common piece of data in both data sets to connect on.

These Join keys don’t need to be named the same in both data sources but need to have the same data. It’s the same concept everywhere – we have two data sources and they have to have something in common for us to join them. Sometimes it’s a Page URL, sometimes it’s a date, or it can be internal user IDs.

For a simple Table element, drag and drop the dimension you want use to join, and then select which metrics you want to appear as columns.

Give your Blended Data Source a name, preferably mentioning both original data sources, then Close the Blend Data panel.

It’s important to note that you’re creating a new data source, that just contains the blended data: the common key and the dimensions and metrics that you selected. You won’t have both full data sources available to you all the time, only the fields that you explicitly put into this joined table, or blended data source.

Combine Charts Together with Data Blending

If you want to combine chart elements, this becomes even easier. If you’ve ever made two chart elements and strategically layered them on top of each other, prepare to be amazed.

First, pick two or more data sources you’d like to graph together. For instance, if you ever wanted to graph Google Search Console impressions, Google Ads impressions, and Google Analytics Pageviews all in the same graph, now you can.

Start by adding each graph individually. I picked a Search Console data source, a Google AdWords data source, and a Google Analytics source (with greatly modified numbers) and added them all to my report.

Then, to easily combine these charts, hold down CTRL or SHIFT and click on all chart elements, or draw a box around both of them to select all. You can select between 2 and 5 elements. Then, right-click and choose Blend Data.

Data Studio will automatically make you a new blended Data Source, with the common key being the date. It adds this data source to the report and combines these elements into a chart. Voila! (I tweaked my graph to adjust colors and renamed my metrics to make it a little more clear.)

Compare Performance Across Platforms

When you’re using different tools or providing different services to clients, it’s often a staple to be able to see all of these metrics together. Combining data in Excel, Sheets, or other platforms can become tedious or challenging.

At this time, data blending doesn’t seem to support calculations across data sources, but at least we can get them together in the same table, chart, etc. This allows us to see the information at one glance, and (this is a big plus!) easily use the same data and dimension filters to adjust all the elements at the same time.

Note: It will be more important than ever to have consistent naming conventions across your marketing channels. Imagine paid search campaigns that all indicate branded vs non-branded in the campaign name. You can view performance together, or drill down into a specific type of campaign.

Bringing In Personal and Meta Data

Now we’re talking. How about blending Google Analytics data with our Salesforce or our CRM system? Again, this all hinges on getting a common key in both platforms. We’ve written about this extensively. A key to pass between systems is often your Google Analytics client ID. You can store it in Google Analytics as a custom dimension, and pass it into your systems using forms or other mechanisms.

In the example below, I connected a Google Analytics data source with a client ID custom dimension, and a report from my Salesforce account that listed Client IDs and Company Names. Blended together, I can create an easily updatable report showing me which sections of the site companies are visiting, with a drop-down to focus in on a particular company.

Imagine what else we can do by combining these data sources! Sales regions can be mapped and reported on in aggregate or by sales team member. Conversion data from GA can be viewed alongside Salesforce information. Name, company, purchase history – all together!

Add Context To Performance

Some of the best applications will be taking real-world information and combining it with our online data. Weather data has often been called out as something we can track and combine. In five minutes, I pulled weather history for July, dropped that into a spreadsheet, and joined that with a Google Analytics property.

Do these two things have anything in common? From the graph, it’s clear, no, not really. But if you work in a seasonal or outdoor company, perhaps you have a direct need for this. Imagine what other data sources could help provide real-world context when blended together.

A few additional ideas:

Chart code changes against key site performance metrics.

Look at calendar or offline events data next to digital conversion rates.

Track ecommerce performance next to total company sales.

Compare Goals Across Google Analytics Views

Ok, this one’s amazing. Google Analytics has a limit of 20 goals per view. Yikes, ouch. No way around this, this one doesn’t even get better with Google Analytics 360. I’m not sure anyone really needs more than 20 goals, but if you do, a common workaround is to create multiple views and get 20 more goals to play with.

But now, you’ve got a tough reporting challenge – you need to grab data from two or more different views and combine them together in some sort of report. This sounds like a job for data blending! If you have two different GA views with the same info, but different goals, keep going.

Add one GA View as a data source to your report

Click Blend Data

Add the other GA View as another data source

Combine on a session-level dimension like Source/Medium, Default Channel Grouping, or Landing Page

Add Goals from each of the data sources

Compare Data Across Google Analytics Properties

Managing multiple websites? Different properties for the same company? Agencies managing multiple clients? It’s easier than ever to combine data to get a holistic report across all of your data needs.

Email Campaigns vs Website Performance

Here’s another great use case – bring in data about a specific campaign and compare open rates and click-through rates in the same table as website performance, goals completed, and Ecommerce performance.

Fun Ideas

We’ve written before about fun use cases for Data Studio, and how our team literally uses for real-world scenarios like health performance, financial monitoring, and more!

“I use Data Studio outside of work to track my small investment portfolio. Blended metrics will save me time spent in spreadsheets and allow me to quickly visualize performance of multiple data sources and better track overall goals.”

Michael Bartholow Senior Manager, Digital Marketing Strategy

Get Blending!

The power is in your hands – start playing around with blended data and see how it can help you! While a lot of this functionality was available in other platforms or programs, remember that we can now blend data sources with all of the additional benefits of Google Data Studio: easy to create, easy to share, easy to refresh.

from FEED 9 MARKETING https://ift.tt/2mddVEh

[seoprovider2110]

Will It Blend? Google Data Studio Rolls out Data Blending

Will It Blend? Google Data Studio Rolls out Data Blending

We knew it was coming, we waited for it, and now it’s finally here! Data blending is in Google Analytics, and it. is. glorious. The nice part about being the upcomer on the data viz scene is that the playbook is already scripted out, the questions become “which features do we prioritize?” and “when?”. The exact way that features are implemented can be drastically different but the underlying principles are the same, like joining data sources or as Data Studio calls it, ‘data blending’.

Data Studio has a couple of tricks up its sleeve, mainly it’s giant network of natively integrated awesome tools. (Check out the BigQuery connector!)

To catch us up, let’s review. Data Studio is the free visualization tool from Google. Built on the Google Drive technology, easy to create, collaborate, and share unlimited reports. We love our Google tools like Google Analytics and Google AdWords, so of course we love to use Data Studio to create great visualizations for our clients and blog readers. Also, of course, one of the best benefits of Data Studio is that we can visualize any data and others have created great ways to bring in non-Google data.

Which brings us back to the business at hand; let’s talk more about data blending and how you can immediately use this feature to make your life easier.

How To Blend Data in Google Data Studio

This feature is supposedly rolling out as of July 10, the day of the Google Marketing Live event. Already people are tweeting about the awesomeness. Check your Data Studio reports to see if you have it by clicking on any report element, then looking at the Data Source portion on the Data pane.

If you have Data Blending, you’ll see an option underneath your Data Source that says “Blend Data.”

If you don’t see it, don’t panic. Clear your cookies and refresh the page, log back in, and check again. If you still don’t see it, just wait a couple days and hopefully it shows up.

Blending Data Sources on a Common Key

Clicking on the Blend Data button will reveal a lower panel to help make this process easy. It will use your current data source and invite you to Add Another Data Source. The entire premise behind joining data together is to find a common piece of data in both data sets to connect on.

These Join keys don’t need to be named the same in both data sources but need to have the same data. It’s the same concept everywhere – we have two data sources and they have to have something in common for us to join them. Sometimes it’s a Page URL, sometimes it’s a date, or it can be internal user IDs.

For a simple Table element, drag and drop the dimension you want use to join, and then select which metrics you want to appear as columns.

Give your Blended Data Source a name, preferably mentioning both original data sources, then Close the Blend Data panel.

It’s important to note that you’re creating a new data source, that just contains the blended data: the common key and the dimensions and metrics that you selected. You won’t have both full data sources available to you all the time, only the fields that you explicitly put into this joined table, or blended data source.

Combine Charts Together with Data Blending

If you want to combine chart elements, this becomes even easier. If you’ve ever made two chart elements and strategically layered them on top of each other, prepare to be amazed.

First, pick two or more data sources you’d like to graph together. For instance, if you ever wanted to graph Google Search Console impressions, Google Ads impressions, and Google Analytics Pageviews all in the same graph, now you can.

Start by adding each graph individually. I picked a Search Console data source, a Google AdWords data source, and a Google Analytics source (with greatly modified numbers) and added them all to my report.

Then, to easily combine these charts, hold down CTRL or SHIFT and click on all chart elements, or draw a box around both of them to select all. You can select between 2 and 5 elements. Then, right-click and choose Blend Data.

Data Studio will automatically make you a new blended Data Source, with the common key being the date. It adds this data source to the report and combines these elements into a chart. Voila! (I tweaked my graph to adjust colors and renamed my metrics to make it a little more clear.)

Compare Performance Across Platforms

When you’re using different tools or providing different services to clients, it’s often a staple to be able to see all of these metrics together. Combining data in Excel, Sheets, or other platforms can become tedious or challenging.

At this time, data blending doesn’t seem to support calculations across data sources, but at least we can get them together in the same table, chart, etc. This allows us to see the information at one glance, and (this is a big plus!) easily use the same data and dimension filters to adjust all the elements at the same time.

Note: It will be more important than ever to have consistent naming conventions across your marketing channels. Imagine paid search campaigns that all indicate branded vs non-branded in the campaign name. You can view performance together, or drill down into a specific type of campaign.

Bringing In Personal and Meta Data

Now we’re talking. How about blending Google Analytics data with our Salesforce or our CRM system? Again, this all hinges on getting a common key in both platforms. We’ve written about this extensively. A key to pass between systems is often your Google Analytics client ID. You can store it in Google Analytics as a custom dimension, and pass it into your systems using forms or other mechanisms.

In the example below, I connected a Google Analytics data source with a client ID custom dimension, and a report from my Salesforce account that listed Client IDs and Company Names. Blended together, I can create an easily updatable report showing me which sections of the site companies are visiting, with a drop-down to focus in on a particular company.

Imagine what else we can do by combining these data sources! Sales regions can be mapped and reported on in aggregate or by sales team member. Conversion data from GA can be viewed alongside Salesforce information. Name, company, purchase history – all together!

Add Context To Performance

Some of the best applications will be taking real-world information and combining it with our online data. Weather data has often been called out as something we can track and combine. In five minutes, I pulled weather history for July, dropped that into a spreadsheet, and joined that with a Google Analytics property.

Do these two things have anything in common? From the graph, it’s clear, no, not really. But if you work in a seasonal or outdoor company, perhaps you have a direct need for this. Imagine what other data sources could help provide real-world context when blended together.

A few additional ideas:

Chart code changes against key site performance metrics.

Look at calendar or offline events data next to digital conversion rates.

Track ecommerce performance next to total company sales.

Compare Goals Across Google Analytics Views

Ok, this one’s amazing. Google Analytics has a limit of 20 goals per view. Yikes, ouch. No way around this, this one doesn’t even get better with Google Analytics 360. I’m not sure anyone really needs more than 20 goals, but if you do, a common workaround is to create multiple views and get 20 more goals to play with.

But now, you’ve got a tough reporting challenge – you need to grab data from two or more different views and combine them together in some sort of report. This sounds like a job for data blending! If you have two different GA views with the same info, but different goals, keep going.

Add one GA View as a data source to your report

Click Blend Data

Add the other GA View as another data source

Combine on a session-level dimension like Source/Medium, Default Channel Grouping, or Landing Page

Add Goals from each of the data sources

Compare Data Across Google Analytics Properties

Managing multiple websites? Different properties for the same company? Agencies managing multiple clients? It’s easier than ever to combine data to get a holistic report across all of your data needs.

Email Campaigns vs Website Performance

Here’s another great use case – bring in data about a specific campaign and compare open rates and click-through rates in the same table as website performance, goals completed, and Ecommerce performance.

Fun Ideas

We’ve written before about fun use cases for Data Studio, and how our team literally uses for real-world scenarios like health performance, financial monitoring, and more!

“I use Data Studio outside of work to track my small investment portfolio. Blended metrics will save me time spent in spreadsheets and allow me to quickly visualize performance of multiple data sources and better track overall goals.”

Michael Bartholow Senior Manager, Digital Marketing Strategy

Get Blending!

The power is in your hands – start playing around with blended data and see how it can help you! While a lot of this functionality was available in other platforms or programs, remember that we can now blend data sources with all of the additional benefits of Google Data Studio: easy to create, easy to share, easy to refresh.

https://ift.tt/2mddVEh

[restateagnt17101]

Will It Blend? Google Data Studio Rolls out Data Blending

Will It Blend? Google Data Studio Rolls out Data Blending

We knew it was coming, we waited for it, and now it’s finally here! Data blending is in Google Analytics, and it. is. glorious. The nice part about being the upcomer on the data viz scene is that the playbook is already scripted out, the questions become “which features do we prioritize?” and “when?”. The exact way that features are implemented can be drastically different but the underlying principles are the same, like joining data sources or as Data Studio calls it, ‘data blending’.

Data Studio has a couple of tricks up its sleeve, mainly it’s giant network of natively integrated awesome tools. (Check out the BigQuery connector!)

To catch us up, let’s review. Data Studio is the free visualization tool from Google. Built on the Google Drive technology, easy to create, collaborate, and share unlimited reports. We love our Google tools like Google Analytics and Google AdWords, so of course we love to use Data Studio to create great visualizations for our clients and blog readers. Also, of course, one of the best benefits of Data Studio is that we can visualize any data and others have created great ways to bring in non-Google data.

Which brings us back to the business at hand; let’s talk more about data blending and how you can immediately use this feature to make your life easier.

How To Blend Data in Google Data Studio

This feature is supposedly rolling out as of July 10, the day of the Google Marketing Live event. Already people are tweeting about the awesomeness. Check your Data Studio reports to see if you have it by clicking on any report element, then looking at the Data Source portion on the Data pane.

If you have Data Blending, you’ll see an option underneath your Data Source that says “Blend Data.”

If you don’t see it, don’t panic. Clear your cookies and refresh the page, log back in, and check again. If you still don’t see it, just wait a couple days and hopefully it shows up.

Blending Data Sources on a Common Key

Clicking on the Blend Data button will reveal a lower panel to help make this process easy. It will use your current data source and invite you to Add Another Data Source. The entire premise behind joining data together is to find a common piece of data in both data sets to connect on.

These Join keys don’t need to be named the same in both data sources but need to have the same data. It’s the same concept everywhere – we have two data sources and they have to have something in common for us to join them. Sometimes it’s a Page URL, sometimes it’s a date, or it can be internal user IDs.

For a simple Table element, drag and drop the dimension you want use to join, and then select which metrics you want to appear as columns.

Give your Blended Data Source a name, preferably mentioning both original data sources, then Close the Blend Data panel.

It’s important to note that you’re creating a new data source, that just contains the blended data: the common key and the dimensions and metrics that you selected. You won’t have both full data sources available to you all the time, only the fields that you explicitly put into this joined table, or blended data source.

Combine Charts Together with Data Blending

If you want to combine chart elements, this becomes even easier. If you’ve ever made two chart elements and strategically layered them on top of each other, prepare to be amazed.

First, pick two or more data sources you’d like to graph together. For instance, if you ever wanted to graph Google Search Console impressions, Google Ads impressions, and Google Analytics Pageviews all in the same graph, now you can.

Start by adding each graph individually. I picked a Search Console data source, a Google AdWords data source, and a Google Analytics source (with greatly modified numbers) and added them all to my report.

Then, to easily combine these charts, hold down CTRL or SHIFT and click on all chart elements, or draw a box around both of them to select all. You can select between 2 and 5 elements. Then, right-click and choose Blend Data.

Data Studio will automatically make you a new blended Data Source, with the common key being the date. It adds this data source to the report and combines these elements into a chart. Voila! (I tweaked my graph to adjust colors and renamed my metrics to make it a little more clear.)

Compare Performance Across Platforms

When you’re using different tools or providing different services to clients, it’s often a staple to be able to see all of these metrics together. Combining data in Excel, Sheets, or other platforms can become tedious or challenging.

At this time, data blending doesn’t seem to support calculations across data sources, but at least we can get them together in the same table, chart, etc. This allows us to see the information at one glance, and (this is a big plus!) easily use the same data and dimension filters to adjust all the elements at the same time.

Note: It will be more important than ever to have consistent naming conventions across your marketing channels. Imagine paid search campaigns that all indicate branded vs non-branded in the campaign name. You can view performance together, or drill down into a specific type of campaign.

Bringing In Personal and Meta Data

Now we’re talking. How about blending Google Analytics data with our Salesforce or our CRM system? Again, this all hinges on getting a common key in both platforms. We’ve written about this extensively. A key to pass between systems is often your Google Analytics client ID. You can store it in Google Analytics as a custom dimension, and pass it into your systems using forms or other mechanisms.

In the example below, I connected a Google Analytics data source with a client ID custom dimension, and a report from my Salesforce account that listed Client IDs and Company Names. Blended together, I can create an easily updatable report showing me which sections of the site companies are visiting, with a drop-down to focus in on a particular company.

Imagine what else we can do by combining these data sources! Sales regions can be mapped and reported on in aggregate or by sales team member. Conversion data from GA can be viewed alongside Salesforce information. Name, company, purchase history – all together!

Add Context To Performance

Some of the best applications will be taking real-world information and combining it with our online data. Weather data has often been called out as something we can track and combine. In five minutes, I pulled weather history for July, dropped that into a spreadsheet, and joined that with a Google Analytics property.

Do these two things have anything in common? From the graph, it’s clear, no, not really. But if you work in a seasonal or outdoor company, perhaps you have a direct need for this. Imagine what other data sources could help provide real-world context when blended together.

A few additional ideas:

Chart code changes against key site performance metrics.

Look at calendar or offline events data next to digital conversion rates.

Track ecommerce performance next to total company sales.

Compare Goals Across Google Analytics Views

Ok, this one’s amazing. Google Analytics has a limit of 20 goals per view. Yikes, ouch. No way around this, this one doesn’t even get better with Google Analytics 360. I’m not sure anyone really needs more than 20 goals, but if you do, a common workaround is to create multiple views and get 20 more goals to play with.

But now, you’ve got a tough reporting challenge – you need to grab data from two or more different views and combine them together in some sort of report. This sounds like a job for data blending! If you have two different GA views with the same info, but different goals, keep going.

Add one GA View as a data source to your report

Click Blend Data

Add the other GA View as another data source

Combine on a session-level dimension like Source/Medium, Default Channel Grouping, or Landing Page

Add Goals from each of the data sources

Compare Data Across Google Analytics Properties

Managing multiple websites? Different properties for the same company? Agencies managing multiple clients? It’s easier than ever to combine data to get a holistic report across all of your data needs.

Email Campaigns vs Website Performance

Here’s another great use case – bring in data about a specific campaign and compare open rates and click-through rates in the same table as website performance, goals completed, and Ecommerce performance.

Fun Ideas

We’ve written before about fun use cases for Data Studio, and how our team literally uses for real-world scenarios like health performance, financial monitoring, and more!

“I use Data Studio outside of work to track my small investment portfolio. Blended metrics will save me time spent in spreadsheets and allow me to quickly visualize performance of multiple data sources and better track overall goals.”

Michael Bartholow Senior Manager, Digital Marketing Strategy

Get Blending!

The power is in your hands – start playing around with blended data and see how it can help you! While a lot of this functionality was available in other platforms or programs, remember that we can now blend data sources with all of the additional benefits of Google Data Studio: easy to create, easy to share, easy to refresh.

https://ift.tt/2mddVEh

[inetmrktng75247]

Will It Blend? Google Data Studio Rolls out Data Blending

Will It Blend? Google Data Studio Rolls out Data Blending

We knew it was coming, we waited for it, and now it’s finally here! Data blending is in Google Analytics, and it. is. glorious. The nice part about being the upcomer on the data viz scene is that the playbook is already scripted out, the questions become “which features do we prioritize?” and “when?”. The exact way that features are implemented can be drastically different but the underlying principles are the same, like joining data sources or as Data Studio calls it, ‘data blending’.

Data Studio has a couple of tricks up its sleeve, mainly it’s giant network of natively integrated awesome tools. (Check out the BigQuery connector!)

To catch us up, let’s review. Data Studio is the free visualization tool from Google. Built on the Google Drive technology, easy to create, collaborate, and share unlimited reports. We love our Google tools like Google Analytics and Google AdWords, so of course we love to use Data Studio to create great visualizations for our clients and blog readers. Also, of course, one of the best benefits of Data Studio is that we can visualize any data and others have created great ways to bring in non-Google data.

Which brings us back to the business at hand; let’s talk more about data blending and how you can immediately use this feature to make your life easier.

How To Blend Data in Google Data Studio

This feature is supposedly rolling out as of July 10, the day of the Google Marketing Live event. Already people are tweeting about the awesomeness. Check your Data Studio reports to see if you have it by clicking on any report element, then looking at the Data Source portion on the Data pane.

If you have Data Blending, you’ll see an option underneath your Data Source that says “Blend Data.”

If you don’t see it, don’t panic. Clear your cookies and refresh the page, log back in, and check again. If you still don’t see it, just wait a couple days and hopefully it shows up.

Blending Data Sources on a Common Key

Clicking on the Blend Data button will reveal a lower panel to help make this process easy. It will use your current data source and invite you to Add Another Data Source. The entire premise behind joining data together is to find a common piece of data in both data sets to connect on.

These Join keys don’t need to be named the same in both data sources but need to have the same data. It’s the same concept everywhere – we have two data sources and they have to have something in common for us to join them. Sometimes it’s a Page URL, sometimes it’s a date, or it can be internal user IDs.

For a simple Table element, drag and drop the dimension you want use to join, and then select which metrics you want to appear as columns.

Give your Blended Data Source a name, preferably mentioning both original data sources, then Close the Blend Data panel.

It’s important to note that you’re creating a new data source, that just contains the blended data: the common key and the dimensions and metrics that you selected. You won’t have both full data sources available to you all the time, only the fields that you explicitly put into this joined table, or blended data source.

Combine Charts Together with Data Blending

If you want to combine chart elements, this becomes even easier. If you’ve ever made two chart elements and strategically layered them on top of each other, prepare to be amazed.

First, pick two or more data sources you’d like to graph together. For instance, if you ever wanted to graph Google Search Console impressions, Google Ads impressions, and Google Analytics Pageviews all in the same graph, now you can.

Start by adding each graph individually. I picked a Search Console data source, a Google AdWords data source, and a Google Analytics source (with greatly modified numbers) and added them all to my report.

Then, to easily combine these charts, hold down CTRL or SHIFT and click on all chart elements, or draw a box around both of them to select all. You can select between 2 and 5 elements. Then, right-click and choose Blend Data.

Data Studio will automatically make you a new blended Data Source, with the common key being the date. It adds this data source to the report and combines these elements into a chart. Voila! (I tweaked my graph to adjust colors and renamed my metrics to make it a little more clear.)

Compare Performance Across Platforms

When you’re using different tools or providing different services to clients, it’s often a staple to be able to see all of these metrics together. Combining data in Excel, Sheets, or other platforms can become tedious or challenging.

At this time, data blending doesn’t seem to support calculations across data sources, but at least we can get them together in the same table, chart, etc. This allows us to see the information at one glance, and (this is a big plus!) easily use the same data and dimension filters to adjust all the elements at the same time.

Note: It will be more important than ever to have consistent naming conventions across your marketing channels. Imagine paid search campaigns that all indicate branded vs non-branded in the campaign name. You can view performance together, or drill down into a specific type of campaign.

Bringing In Personal and Meta Data

Now we’re talking. How about blending Google Analytics data with our Salesforce or our CRM system? Again, this all hinges on getting a common key in both platforms. We’ve written about this extensively. A key to pass between systems is often your Google Analytics client ID. You can store it in Google Analytics as a custom dimension, and pass it into your systems using forms or other mechanisms.

In the example below, I connected a Google Analytics data source with a client ID custom dimension, and a report from my Salesforce account that listed Client IDs and Company Names. Blended together, I can create an easily updatable report showing me which sections of the site companies are visiting, with a drop-down to focus in on a particular company.

Imagine what else we can do by combining these data sources! Sales regions can be mapped and reported on in aggregate or by sales team member. Conversion data from GA can be viewed alongside Salesforce information. Name, company, purchase history – all together!

Add Context To Performance

Some of the best applications will be taking real-world information and combining it with our online data. Weather data has often been called out as something we can track and combine. In five minutes, I pulled weather history for July, dropped that into a spreadsheet, and joined that with a Google Analytics property.

Do these two things have anything in common? From the graph, it’s clear, no, not really. But if you work in a seasonal or outdoor company, perhaps you have a direct need for this. Imagine what other data sources could help provide real-world context when blended together.

A few additional ideas:

Chart code changes against key site performance metrics.

Look at calendar or offline events data next to digital conversion rates.

Track ecommerce performance next to total company sales.

Compare Goals Across Google Analytics Views

Ok, this one’s amazing. Google Analytics has a limit of 20 goals per view. Yikes, ouch. No way around this, this one doesn’t even get better with Google Analytics 360. I’m not sure anyone really needs more than 20 goals, but if you do, a common workaround is to create multiple views and get 20 more goals to play with.

But now, you’ve got a tough reporting challenge – you need to grab data from two or more different views and combine them together in some sort of report. This sounds like a job for data blending! If you have two different GA views with the same info, but different goals, keep going.

Add one GA View as a data source to your report

Click Blend Data

Add the other GA View as another data source

Combine on a session-level dimension like Source/Medium, Default Channel Grouping, or Landing Page

Add Goals from each of the data sources

Compare Data Across Google Analytics Properties

Managing multiple websites? Different properties for the same company? Agencies managing multiple clients? It’s easier than ever to combine data to get a holistic report across all of your data needs.

Email Campaigns vs Website Performance

Here’s another great use case – bring in data about a specific campaign and compare open rates and click-through rates in the same table as website performance, goals completed, and Ecommerce performance.

Fun Ideas

We’ve written before about fun use cases for Data Studio, and how our team literally uses for real-world scenarios like health performance, financial monitoring, and more!

“I use Data Studio outside of work to track my small investment portfolio. Blended metrics will save me time spent in spreadsheets and allow me to quickly visualize performance of multiple data sources and better track overall goals.”

Michael Bartholow Senior Manager, Digital Marketing Strategy

Get Blending!

The power is in your hands – start playing around with blended data and see how it can help you! While a lot of this functionality was available in other platforms or programs, remember that we can now blend data sources with all of the additional benefits of Google Data Studio: easy to create, easy to share, easy to refresh.

https://ift.tt/2mddVEh

[duilawyer72210]

Will It Blend? Google Data Studio Rolls out Data Blending

Will It Blend? Google Data Studio Rolls out Data Blending

We knew it was coming, we waited for it, and now it’s finally here! Data blending is in Google Analytics, and it. is. glorious. The nice part about being the upcomer on the data viz scene is that the playbook is already scripted out, the questions become “which features do we prioritize?” and “when?”. The exact way that features are implemented can be drastically different but the underlying principles are the same, like joining data sources or as Data Studio calls it, ‘data blending’.

Data Studio has a couple of tricks up its sleeve, mainly it’s giant network of natively integrated awesome tools. (Check out the BigQuery connector!)

To catch us up, let’s review. Data Studio is the free visualization tool from Google. Built on the Google Drive technology, easy to create, collaborate, and share unlimited reports. We love our Google tools like Google Analytics and Google AdWords, so of course we love to use Data Studio to create great visualizations for our clients and blog readers. Also, of course, one of the best benefits of Data Studio is that we can visualize any data and others have created great ways to bring in non-Google data.

Which brings us back to the business at hand; let’s talk more about data blending and how you can immediately use this feature to make your life easier.

How To Blend Data in Google Data Studio

This feature is supposedly rolling out as of July 10, the day of the Google Marketing Live event. Already people are tweeting about the awesomeness. Check your Data Studio reports to see if you have it by clicking on any report element, then looking at the Data Source portion on the Data pane.

If you have Data Blending, you’ll see an option underneath your Data Source that says “Blend Data.”

If you don’t see it, don’t panic. Clear your cookies and refresh the page, log back in, and check again. If you still don’t see it, just wait a couple days and hopefully it shows up.

Blending Data Sources on a Common Key

Clicking on the Blend Data button will reveal a lower panel to help make this process easy. It will use your current data source and invite you to Add Another Data Source. The entire premise behind joining data together is to find a common piece of data in both data sets to connect on.

These Join keys don’t need to be named the same in both data sources but need to have the same data. It’s the same concept everywhere – we have two data sources and they have to have something in common for us to join them. Sometimes it’s a Page URL, sometimes it’s a date, or it can be internal user IDs.

For a simple Table element, drag and drop the dimension you want use to join, and then select which metrics you want to appear as columns.

Give your Blended Data Source a name, preferably mentioning both original data sources, then Close the Blend Data panel.

It’s important to note that you’re creating a new data source, that just contains the blended data: the common key and the dimensions and metrics that you selected. You won’t have both full data sources available to you all the time, only the fields that you explicitly put into this joined table, or blended data source.

Combine Charts Together with Data Blending

If you want to combine chart elements, this becomes even easier. If you’ve ever made two chart elements and strategically layered them on top of each other, prepare to be amazed.

First, pick two or more data sources you’d like to graph together. For instance, if you ever wanted to graph Google Search Console impressions, Google Ads impressions, and Google Analytics Pageviews all in the same graph, now you can.

Start by adding each graph individually. I picked a Search Console data source, a Google AdWords data source, and a Google Analytics source (with greatly modified numbers) and added them all to my report.

Then, to easily combine these charts, hold down CTRL or SHIFT and click on all chart elements, or draw a box around both of them to select all. You can select between 2 and 5 elements. Then, right-click and choose Blend Data.

Data Studio will automatically make you a new blended Data Source, with the common key being the date. It adds this data source to the report and combines these elements into a chart. Voila! (I tweaked my graph to adjust colors and renamed my metrics to make it a little more clear.)

Compare Performance Across Platforms

When you’re using different tools or providing different services to clients, it’s often a staple to be able to see all of these metrics together. Combining data in Excel, Sheets, or other platforms can become tedious or challenging.

At this time, data blending doesn’t seem to support calculations across data sources, but at least we can get them together in the same table, chart, etc. This allows us to see the information at one glance, and (this is a big plus!) easily use the same data and dimension filters to adjust all the elements at the same time.

Note: It will be more important than ever to have consistent naming conventions across your marketing channels. Imagine paid search campaigns that all indicate branded vs non-branded in the campaign name. You can view performance together, or drill down into a specific type of campaign.

Bringing In Personal and Meta Data

Now we’re talking. How about blending Google Analytics data with our Salesforce or our CRM system? Again, this all hinges on getting a common key in both platforms. We’ve written about this extensively. A key to pass between systems is often your Google Analytics client ID. You can store it in Google Analytics as a custom dimension, and pass it into your systems using forms or other mechanisms.

In the example below, I connected a Google Analytics data source with a client ID custom dimension, and a report from my Salesforce account that listed Client IDs and Company Names. Blended together, I can create an easily updatable report showing me which sections of the site companies are visiting, with a drop-down to focus in on a particular company.

Imagine what else we can do by combining these data sources! Sales regions can be mapped and reported on in aggregate or by sales team member. Conversion data from GA can be viewed alongside Salesforce information. Name, company, purchase history – all together!

Add Context To Performance

Some of the best applications will be taking real-world information and combining it with our online data. Weather data has often been called out as something we can track and combine. In five minutes, I pulled weather history for July, dropped that into a spreadsheet, and joined that with a Google Analytics property.

Do these two things have anything in common? From the graph, it’s clear, no, not really. But if you work in a seasonal or outdoor company, perhaps you have a direct need for this. Imagine what other data sources could help provide real-world context when blended together.

A few additional ideas:

Chart code changes against key site performance metrics.

Look at calendar or offline events data next to digital conversion rates.

Track ecommerce performance next to total company sales.

Compare Goals Across Google Analytics Views

Ok, this one’s amazing. Google Analytics has a limit of 20 goals per view. Yikes, ouch. No way around this, this one doesn’t even get better with Google Analytics 360. I’m not sure anyone really needs more than 20 goals, but if you do, a common workaround is to create multiple views and get 20 more goals to play with.

But now, you’ve got a tough reporting challenge – you need to grab data from two or more different views and combine them together in some sort of report. This sounds like a job for data blending! If you have two different GA views with the same info, but different goals, keep going.

Add one GA View as a data source to your report

Click Blend Data

Add the other GA View as another data source

Combine on a session-level dimension like Source/Medium, Default Channel Grouping, or Landing Page

Add Goals from each of the data sources

Compare Data Across Google Analytics Properties

Managing multiple websites? Different properties for the same company? Agencies managing multiple clients? It’s easier than ever to combine data to get a holistic report across all of your data needs.

Email Campaigns vs Website Performance

Here’s another great use case – bring in data about a specific campaign and compare open rates and click-through rates in the same table as website performance, goals completed, and Ecommerce performance.

Fun Ideas

We’ve written before about fun use cases for Data Studio, and how our team literally uses for real-world scenarios like health performance, financial monitoring, and more!

“I use Data Studio outside of work to track my small investment portfolio. Blended metrics will save me time spent in spreadsheets and allow me to quickly visualize performance of multiple data sources and better track overall goals.”

Michael Bartholow Senior Manager, Digital Marketing Strategy

Get Blending!

The power is in your hands – start playing around with blended data and see how it can help you! While a lot of this functionality was available in other platforms or programs, remember that we can now blend data sources with all of the additional benefits of Google Data Studio: easy to create, easy to share, easy to refresh.

https://ift.tt/2mddVEh

[ramonlindsay050]

Will It Blend? Google Data Studio Rolls out Data Blending

Will It Blend? Google Data Studio Rolls out Data Blending

We knew it was coming, we waited for it, and now it’s finally here! Data blending is in Google Analytics, and it. is. glorious. The nice part about being the upcomer on the data viz scene is that the playbook is already scripted out, the questions become “which features do we prioritize?” and “when?”. The exact way that features are implemented can be drastically different but the underlying principles are the same, like joining data sources or as Data Studio calls it, ‘data blending’.

Data Studio has a couple of tricks up its sleeve, mainly it’s giant network of natively integrated awesome tools. (Check out the BigQuery connector!)

To catch us up, let’s review. Data Studio is the free visualization tool from Google. Built on the Google Drive technology, easy to create, collaborate, and share unlimited reports. We love our Google tools like Google Analytics and Google AdWords, so of course we love to use Data Studio to create great visualizations for our clients and blog readers. Also, of course, one of the best benefits of Data Studio is that we can visualize any data and others have created great ways to bring in non-Google data.

Which brings us back to the business at hand; let’s talk more about data blending and how you can immediately use this feature to make your life easier.

How To Blend Data in Google Data Studio

This feature is supposedly rolling out as of July 10, the day of the Google Marketing Live event. Already people are tweeting about the awesomeness. Check your Data Studio reports to see if you have it by clicking on any report element, then looking at the Data Source portion on the Data pane.

If you have Data Blending, you’ll see an option underneath your Data Source that says “Blend Data.”

If you don’t see it, don’t panic. Clear your cookies and refresh the page, log back in, and check again. If you still don’t see it, just wait a couple days and hopefully it shows up.

Blending Data Sources on a Common Key

Clicking on the Blend Data button will reveal a lower panel to help make this process easy. It will use your current data source and invite you to Add Another Data Source. The entire premise behind joining data together is to find a common piece of data in both data sets to connect on.

These Join keys don’t need to be named the same in both data sources but need to have the same data. It’s the same concept everywhere – we have two data sources and they have to have something in common for us to join them. Sometimes it’s a Page URL, sometimes it’s a date, or it can be internal user IDs.

For a simple Table element, drag and drop the dimension you want use to join, and then select which metrics you want to appear as columns.

Give your Blended Data Source a name, preferably mentioning both original data sources, then Close the Blend Data panel.

It’s important to note that you’re creating a new data source, that just contains the blended data: the common key and the dimensions and metrics that you selected. You won’t have both full data sources available to you all the time, only the fields that you explicitly put into this joined table, or blended data source.

Combine Charts Together with Data Blending

If you want to combine chart elements, this becomes even easier. If you’ve ever made two chart elements and strategically layered them on top of each other, prepare to be amazed.

First, pick two or more data sources you’d like to graph together. For instance, if you ever wanted to graph Google Search Console impressions, Google Ads impressions, and Google Analytics Pageviews all in the same graph, now you can.

Start by adding each graph individually. I picked a Search Console data source, a Google AdWords data source, and a Google Analytics source (with greatly modified numbers) and added them all to my report.

Then, to easily combine these charts, hold down CTRL or SHIFT and click on all chart elements, or draw a box around both of them to select all. You can select between 2 and 5 elements. Then, right-click and choose Blend Data.

Data Studio will automatically make you a new blended Data Source, with the common key being the date. It adds this data source to the report and combines these elements into a chart. Voila! (I tweaked my graph to adjust colors and renamed my metrics to make it a little more clear.)

Compare Performance Across Platforms

When you’re using different tools or providing different services to clients, it’s often a staple to be able to see all of these metrics together. Combining data in Excel, Sheets, or other platforms can become tedious or challenging.

At this time, data blending doesn’t seem to support calculations across data sources, but at least we can get them together in the same table, chart, etc. This allows us to see the information at one glance, and (this is a big plus!) easily use the same data and dimension filters to adjust all the elements at the same time.

Note: It will be more important than ever to have consistent naming conventions across your marketing channels. Imagine paid search campaigns that all indicate branded vs non-branded in the campaign name. You can view performance together, or drill down into a specific type of campaign.

Bringing In Personal and Meta Data

Now we’re talking. How about blending Google Analytics data with our Salesforce or our CRM system? Again, this all hinges on getting a common key in both platforms. We’ve written about this extensively. A key to pass between systems is often your Google Analytics client ID. You can store it in Google Analytics as a custom dimension, and pass it into your systems using forms or other mechanisms.

In the example below, I connected a Google Analytics data source with a client ID custom dimension, and a report from my Salesforce account that listed Client IDs and Company Names. Blended together, I can create an easily updatable report showing me which sections of the site companies are visiting, with a drop-down to focus in on a particular company.

Imagine what else we can do by combining these data sources! Sales regions can be mapped and reported on in aggregate or by sales team member. Conversion data from GA can be viewed alongside Salesforce information. Name, company, purchase history – all together!

Add Context To Performance

Some of the best applications will be taking real-world information and combining it with our online data. Weather data has often been called out as something we can track and combine. In five minutes, I pulled weather history for July, dropped that into a spreadsheet, and joined that with a Google Analytics property.

Do these two things have anything in common? From the graph, it’s clear, no, not really. But if you work in a seasonal or outdoor company, perhaps you have a direct need for this. Imagine what other data sources could help provide real-world context when blended together.

A few additional ideas:

Chart code changes against key site performance metrics.

Look at calendar or offline events data next to digital conversion rates.

Track ecommerce performance next to total company sales.

Compare Goals Across Google Analytics Views

Ok, this one’s amazing. Google Analytics has a limit of 20 goals per view. Yikes, ouch. No way around this, this one doesn’t even get better with Google Analytics 360. I’m not sure anyone really needs more than 20 goals, but if you do, a common workaround is to create multiple views and get 20 more goals to play with.

But now, you’ve got a tough reporting challenge – you need to grab data from two or more different views and combine them together in some sort of report. This sounds like a job for data blending! If you have two different GA views with the same info, but different goals, keep going.

Add one GA View as a data source to your report

Click Blend Data

Add the other GA View as another data source

Combine on a session-level dimension like Source/Medium, Default Channel Grouping, or Landing Page

Add Goals from each of the data sources

Compare Data Across Google Analytics Properties

Managing multiple websites? Different properties for the same company? Agencies managing multiple clients? It’s easier than ever to combine data to get a holistic report across all of your data needs.

Email Campaigns vs Website Performance

Here’s another great use case – bring in data about a specific campaign and compare open rates and click-through rates in the same table as website performance, goals completed, and Ecommerce performance.

Fun Ideas

We’ve written before about fun use cases for Data Studio, and how our team literally uses for real-world scenarios like health performance, financial monitoring, and more!

“I use Data Studio outside of work to track my small investment portfolio. Blended metrics will save me time spent in spreadsheets and allow me to quickly visualize performance of multiple data sources and better track overall goals.”

Michael Bartholow Senior Manager, Digital Marketing Strategy

Get Blending!

The power is in your hands – start playing around with blended data and see how it can help you! While a lot of this functionality was available in other platforms or programs, remember that we can now blend data sources with all of the additional benefits of Google Data Studio: easy to create, easy to share, easy to refresh.

https://ift.tt/2mddVEh

[mortlend40507]

Will It Blend? Google Data Studio Rolls out Data Blending

Will It Blend? Google Data Studio Rolls out Data Blending

We knew it was coming, we waited for it, and now it’s finally here! Data blending is in Google Analytics, and it. is. glorious. The nice part about being the upcomer on the data viz scene is that the playbook is already scripted out, the questions become “which features do we prioritize?” and “when?”. The exact way that features are implemented can be drastically different but the underlying principles are the same, like joining data sources or as Data Studio calls it, ‘data blending’.

Data Studio has a couple of tricks up its sleeve, mainly it’s giant network of natively integrated awesome tools. (Check out the BigQuery connector!)

To catch us up, let’s review. Data Studio is the free visualization tool from Google. Built on the Google Drive technology, easy to create, collaborate, and share unlimited reports. We love our Google tools like Google Analytics and Google AdWords, so of course we love to use Data Studio to create great visualizations for our clients and blog readers. Also, of course, one of the best benefits of Data Studio is that we can visualize any data and others have created great ways to bring in non-Google data.

Which brings us back to the business at hand; let’s talk more about data blending and how you can immediately use this feature to make your life easier.

How To Blend Data in Google Data Studio

This feature is supposedly rolling out as of July 10, the day of the Google Marketing Live event. Already people are tweeting about the awesomeness. Check your Data Studio reports to see if you have it by clicking on any report element, then looking at the Data Source portion on the Data pane.

If you have Data Blending, you’ll see an option underneath your Data Source that says “Blend Data.”

If you don’t see it, don’t panic. Clear your cookies and refresh the page, log back in, and check again. If you still don’t see it, just wait a couple days and hopefully it shows up.

Blending Data Sources on a Common Key

Clicking on the Blend Data button will reveal a lower panel to help make this process easy. It will use your current data source and invite you to Add Another Data Source. The entire premise behind joining data together is to find a common piece of data in both data sets to connect on.

These Join keys don’t need to be named the same in both data sources but need to have the same data. It’s the same concept everywhere – we have two data sources and they have to have something in common for us to join them. Sometimes it’s a Page URL, sometimes it’s a date, or it can be internal user IDs.

For a simple Table element, drag and drop the dimension you want use to join, and then select which metrics you want to appear as columns.

Give your Blended Data Source a name, preferably mentioning both original data sources, then Close the Blend Data panel.

It’s important to note that you’re creating a new data source, that just contains the blended data: the common key and the dimensions and metrics that you selected. You won’t have both full data sources available to you all the time, only the fields that you explicitly put into this joined table, or blended data source.

Combine Charts Together with Data Blending

If you want to combine chart elements, this becomes even easier. If you’ve ever made two chart elements and strategically layered them on top of each other, prepare to be amazed.

First, pick two or more data sources you’d like to graph together. For instance, if you ever wanted to graph Google Search Console impressions, Google Ads impressions, and Google Analytics Pageviews all in the same graph, now you can.

Start by adding each graph individually. I picked a Search Console data source, a Google AdWords data source, and a Google Analytics source (with greatly modified numbers) and added them all to my report.

Then, to easily combine these charts, hold down CTRL or SHIFT and click on all chart elements, or draw a box around both of them to select all. You can select between 2 and 5 elements. Then, right-click and choose Blend Data.

Data Studio will automatically make you a new blended Data Source, with the common key being the date. It adds this data source to the report and combines these elements into a chart. Voila! (I tweaked my graph to adjust colors and renamed my metrics to make it a little more clear.)

Compare Performance Across Platforms

When you’re using different tools or providing different services to clients, it’s often a staple to be able to see all of these metrics together. Combining data in Excel, Sheets, or other platforms can become tedious or challenging.

At this time, data blending doesn’t seem to support calculations across data sources, but at least we can get them together in the same table, chart, etc. This allows us to see the information at one glance, and (this is a big plus!) easily use the same data and dimension filters to adjust all the elements at the same time.

Note: It will be more important than ever to have consistent naming conventions across your marketing channels. Imagine paid search campaigns that all indicate branded vs non-branded in the campaign name. You can view performance together, or drill down into a specific type of campaign.

Bringing In Personal and Meta Data

Now we’re talking. How about blending Google Analytics data with our Salesforce or our CRM system? Again, this all hinges on getting a common key in both platforms. We’ve written about this extensively. A key to pass between systems is often your Google Analytics client ID. You can store it in Google Analytics as a custom dimension, and pass it into your systems using forms or other mechanisms.

In the example below, I connected a Google Analytics data source with a client ID custom dimension, and a report from my Salesforce account that listed Client IDs and Company Names. Blended together, I can create an easily updatable report showing me which sections of the site companies are visiting, with a drop-down to focus in on a particular company.

Imagine what else we can do by combining these data sources! Sales regions can be mapped and reported on in aggregate or by sales team member. Conversion data from GA can be viewed alongside Salesforce information. Name, company, purchase history – all together!

Add Context To Performance

Some of the best applications will be taking real-world information and combining it with our online data. Weather data has often been called out as something we can track and combine. In five minutes, I pulled weather history for July, dropped that into a spreadsheet, and joined that with a Google Analytics property.

Do these two things have anything in common? From the graph, it’s clear, no, not really. But if you work in a seasonal or outdoor company, perhaps you have a direct need for this. Imagine what other data sources could help provide real-world context when blended together.

A few additional ideas:

Chart code changes against key site performance metrics.

Look at calendar or offline events data next to digital conversion rates.

Track ecommerce performance next to total company sales.

Compare Goals Across Google Analytics Views

Ok, this one’s amazing. Google Analytics has a limit of 20 goals per view. Yikes, ouch. No way around this, this one doesn’t even get better with Google Analytics 360. I’m not sure anyone really needs more than 20 goals, but if you do, a common workaround is to create multiple views and get 20 more goals to play with.

But now, you’ve got a tough reporting challenge – you need to grab data from two or more different views and combine them together in some sort of report. This sounds like a job for data blending! If you have two different GA views with the same info, but different goals, keep going.

Add one GA View as a data source to your report

Click Blend Data

Add the other GA View as another data source

Combine on a session-level dimension like Source/Medium, Default Channel Grouping, or Landing Page

Add Goals from each of the data sources

Compare Data Across Google Analytics Properties

Managing multiple websites? Different properties for the same company? Agencies managing multiple clients? It’s easier than ever to combine data to get a holistic report across all of your data needs.

Email Campaigns vs Website Performance

Here’s another great use case – bring in data about a specific campaign and compare open rates and click-through rates in the same table as website performance, goals completed, and Ecommerce performance.

Fun Ideas

We’ve written before about fun use cases for Data Studio, and how our team literally uses for real-world scenarios like health performance, financial monitoring, and more!

“I use Data Studio outside of work to track my small investment portfolio. Blended metrics will save me time spent in spreadsheets and allow me to quickly visualize performance of multiple data sources and better track overall goals.”

Michael Bartholow Senior Manager, Digital Marketing Strategy

Get Blending!

The power is in your hands – start playing around with blended data and see how it can help you! While a lot of this functionality was available in other platforms or programs, remember that we can now blend data sources with all of the additional benefits of Google Data Studio: easy to create, easy to share, easy to refresh.

https://ift.tt/2mddVEh

[seo53703]

Will It Blend? Google Data Studio Rolls out Data Blending

Will It Blend? Google Data Studio Rolls out Data Blending

We knew it was coming, we waited for it, and now it’s finally here! Data blending is in Google Analytics, and it. is. glorious. The nice part about being the upcomer on the data viz scene is that the playbook is already scripted out, the questions become “which features do we prioritize?” and “when?”. The exact way that features are implemented can be drastically different but the underlying principles are the same, like joining data sources or as Data Studio calls it, ‘data blending’.

Data Studio has a couple of tricks up its sleeve, mainly it’s giant network of natively integrated awesome tools. (Check out the BigQuery connector!)

To catch us up, let’s review. Data Studio is the free visualization tool from Google. Built on the Google Drive technology, easy to create, collaborate, and share unlimited reports. We love our Google tools like Google Analytics and Google AdWords, so of course we love to use Data Studio to create great visualizations for our clients and blog readers. Also, of course, one of the best benefits of Data Studio is that we can visualize any data and others have created great ways to bring in non-Google data.

Which brings us back to the business at hand; let’s talk more about data blending and how you can immediately use this feature to make your life easier.

How To Blend Data in Google Data Studio

This feature is supposedly rolling out as of July 10, the day of the Google Marketing Live event. Already people are tweeting about the awesomeness. Check your Data Studio reports to see if you have it by clicking on any report element, then looking at the Data Source portion on the Data pane.

If you have Data Blending, you’ll see an option underneath your Data Source that says “Blend Data.”

If you don’t see it, don’t panic. Clear your cookies and refresh the page, log back in, and check again. If you still don’t see it, just wait a couple days and hopefully it shows up.

Blending Data Sources on a Common Key

Clicking on the Blend Data button will reveal a lower panel to help make this process easy. It will use your current data source and invite you to Add Another Data Source. The entire premise behind joining data together is to find a common piece of data in both data sets to connect on.

These Join keys don’t need to be named the same in both data sources but need to have the same data. It’s the same concept everywhere – we have two data sources and they have to have something in common for us to join them. Sometimes it’s a Page URL, sometimes it’s a date, or it can be internal user IDs.

For a simple Table element, drag and drop the dimension you want use to join, and then select which metrics you want to appear as columns.

Give your Blended Data Source a name, preferably mentioning both original data sources, then Close the Blend Data panel.

It’s important to note that you’re creating a new data source, that just contains the blended data: the common key and the dimensions and metrics that you selected. You won’t have both full data sources available to you all the time, only the fields that you explicitly put into this joined table, or blended data source.

Combine Charts Together with Data Blending

If you want to combine chart elements, this becomes even easier. If you’ve ever made two chart elements and strategically layered them on top of each other, prepare to be amazed.

First, pick two or more data sources you’d like to graph together. For instance, if you ever wanted to graph Google Search Console impressions, Google Ads impressions, and Google Analytics Pageviews all in the same graph, now you can.

Start by adding each graph individually. I picked a Search Console data source, a Google AdWords data source, and a Google Analytics source (with greatly modified numbers) and added them all to my report.

Then, to easily combine these charts, hold down CTRL or SHIFT and click on all chart elements, or draw a box around both of them to select all. You can select between 2 and 5 elements. Then, right-click and choose Blend Data.

Data Studio will automatically make you a new blended Data Source, with the common key being the date. It adds this data source to the report and combines these elements into a chart. Voila! (I tweaked my graph to adjust colors and renamed my metrics to make it a little more clear.)

Compare Performance Across Platforms

When you’re using different tools or providing different services to clients, it’s often a staple to be able to see all of these metrics together. Combining data in Excel, Sheets, or other platforms can become tedious or challenging.

At this time, data blending doesn’t seem to support calculations across data sources, but at least we can get them together in the same table, chart, etc. This allows us to see the information at one glance, and (this is a big plus!) easily use the same data and dimension filters to adjust all the elements at the same time.

Note: It will be more important than ever to have consistent naming conventions across your marketing channels. Imagine paid search campaigns that all indicate branded vs non-branded in the campaign name. You can view performance together, or drill down into a specific type of campaign.

Bringing In Personal and Meta Data

Now we’re talking. How about blending Google Analytics data with our Salesforce or our CRM system? Again, this all hinges on getting a common key in both platforms. We’ve written about this extensively. A key to pass between systems is often your Google Analytics client ID. You can store it in Google Analytics as a custom dimension, and pass it into your systems using forms or other mechanisms.

In the example below, I connected a Google Analytics data source with a client ID custom dimension, and a report from my Salesforce account that listed Client IDs and Company Names. Blended together, I can create an easily updatable report showing me which sections of the site companies are visiting, with a drop-down to focus in on a particular company.

Imagine what else we can do by combining these data sources! Sales regions can be mapped and reported on in aggregate or by sales team member. Conversion data from GA can be viewed alongside Salesforce information. Name, company, purchase history – all together!

Add Context To Performance

Some of the best applications will be taking real-world information and combining it with our online data. Weather data has often been called out as something we can track and combine. In five minutes, I pulled weather history for July, dropped that into a spreadsheet, and joined that with a Google Analytics property.

Do these two things have anything in common? From the graph, it’s clear, no, not really. But if you work in a seasonal or outdoor company, perhaps you have a direct need for this. Imagine what other data sources could help provide real-world context when blended together.

A few additional ideas:

Chart code changes against key site performance metrics.

Look at calendar or offline events data next to digital conversion rates.

Track ecommerce performance next to total company sales.

Compare Goals Across Google Analytics Views

Ok, this one’s amazing. Google Analytics has a limit of 20 goals per view. Yikes, ouch. No way around this, this one doesn’t even get better with Google Analytics 360. I’m not sure anyone really needs more than 20 goals, but if you do, a common workaround is to create multiple views and get 20 more goals to play with.

But now, you’ve got a tough reporting challenge – you need to grab data from two or more different views and combine them together in some sort of report. This sounds like a job for data blending! If you have two different GA views with the same info, but different goals, keep going.

Add one GA View as a data source to your report

Click Blend Data

Add the other GA View as another data source

Combine on a session-level dimension like Source/Medium, Default Channel Grouping, or Landing Page

Add Goals from each of the data sources

Compare Data Across Google Analytics Properties

Managing multiple websites? Different properties for the same company? Agencies managing multiple clients? It’s easier than ever to combine data to get a holistic report across all of your data needs.

Email Campaigns vs Website Performance

Here’s another great use case – bring in data about a specific campaign and compare open rates and click-through rates in the same table as website performance, goals completed, and Ecommerce performance.

Fun Ideas

We’ve written before about fun use cases for Data Studio, and how our team literally uses for real-world scenarios like health performance, financial monitoring, and more!

“I use Data Studio outside of work to track my small investment portfolio. Blended metrics will save me time spent in spreadsheets and allow me to quickly visualize performance of multiple data sources and better track overall goals.”

Michael Bartholow Senior Manager, Digital Marketing Strategy

Get Blending!

The power is in your hands – start playing around with blended data and see how it can help you! While a lot of this functionality was available in other platforms or programs, remember that we can now blend data sources with all of the additional benefits of Google Data Studio: easy to create, easy to share, easy to refresh.

https://ift.tt/2mddVEh

[realtor10036]

Will It Blend? Google Data Studio Rolls out Data Blending

Will It Blend? Google Data Studio Rolls out Data Blending

We knew it was coming, we waited for it, and now it’s finally here! Data blending is in Google Analytics, and it. is. glorious. The nice part about being the upcomer on the data viz scene is that the playbook is already scripted out, the questions become “which features do we prioritize?” and “when?”. The exact way that features are implemented can be drastically different but the underlying principles are the same, like joining data sources or as Data Studio calls it, ‘data blending’.

Data Studio has a couple of tricks up its sleeve, mainly it’s giant network of natively integrated awesome tools. (Check out the BigQuery connector!)

To catch us up, let’s review. Data Studio is the free visualization tool from Google. Built on the Google Drive technology, easy to create, collaborate, and share unlimited reports. We love our Google tools like Google Analytics and Google AdWords, so of course we love to use Data Studio to create great visualizations for our clients and blog readers. Also, of course, one of the best benefits of Data Studio is that we can visualize any data and others have created great ways to bring in non-Google data.

Which brings us back to the business at hand; let’s talk more about data blending and how you can immediately use this feature to make your life easier.

How To Blend Data in Google Data Studio

This feature is supposedly rolling out as of July 10, the day of the Google Marketing Live event. Already people are tweeting about the awesomeness. Check your Data Studio reports to see if you have it by clicking on any report element, then looking at the Data Source portion on the Data pane.

If you have Data Blending, you’ll see an option underneath your Data Source that says “Blend Data.”

If you don’t see it, don’t panic. Clear your cookies and refresh the page, log back in, and check again. If you still don’t see it, just wait a couple days and hopefully it shows up.

Blending Data Sources on a Common Key

Clicking on the Blend Data button will reveal a lower panel to help make this process easy. It will use your current data source and invite you to Add Another Data Source. The entire premise behind joining data together is to find a common piece of data in both data sets to connect on.

These Join keys don’t need to be named the same in both data sources but need to have the same data. It’s the same concept everywhere – we have two data sources and they have to have something in common for us to join them. Sometimes it’s a Page URL, sometimes it’s a date, or it can be internal user IDs.

For a simple Table element, drag and drop the dimension you want use to join, and then select which metrics you want to appear as columns.

Give your Blended Data Source a name, preferably mentioning both original data sources, then Close the Blend Data panel.

It’s important to note that you’re creating a new data source, that just contains the blended data: the common key and the dimensions and metrics that you selected. You won’t have both full data sources available to you all the time, only the fields that you explicitly put into this joined table, or blended data source.

Combine Charts Together with Data Blending

If you want to combine chart elements, this becomes even easier. If you’ve ever made two chart elements and strategically layered them on top of each other, prepare to be amazed.

First, pick two or more data sources you’d like to graph together. For instance, if you ever wanted to graph Google Search Console impressions, Google Ads impressions, and Google Analytics Pageviews all in the same graph, now you can.

Start by adding each graph individually. I picked a Search Console data source, a Google AdWords data source, and a Google Analytics source (with greatly modified numbers) and added them all to my report.

Then, to easily combine these charts, hold down CTRL or SHIFT and click on all chart elements, or draw a box around both of them to select all. You can select between 2 and 5 elements. Then, right-click and choose Blend Data.

Data Studio will automatically make you a new blended Data Source, with the common key being the date. It adds this data source to the report and combines these elements into a chart. Voila! (I tweaked my graph to adjust colors and renamed my metrics to make it a little more clear.)

Compare Performance Across Platforms

When you’re using different tools or providing different services to clients, it’s often a staple to be able to see all of these metrics together. Combining data in Excel, Sheets, or other platforms can become tedious or challenging.

At this time, data blending doesn’t seem to support calculations across data sources, but at least we can get them together in the same table, chart, etc. This allows us to see the information at one glance, and (this is a big plus!) easily use the same data and dimension filters to adjust all the elements at the same time.

Note: It will be more important than ever to have consistent naming conventions across your marketing channels. Imagine paid search campaigns that all indicate branded vs non-branded in the campaign name. You can view performance together, or drill down into a specific type of campaign.

Bringing In Personal and Meta Data

Now we’re talking. How about blending Google Analytics data with our Salesforce or our CRM system? Again, this all hinges on getting a common key in both platforms. We’ve written about this extensively. A key to pass between systems is often your Google Analytics client ID. You can store it in Google Analytics as a custom dimension, and pass it into your systems using forms or other mechanisms.

In the example below, I connected a Google Analytics data source with a client ID custom dimension, and a report from my Salesforce account that listed Client IDs and Company Names. Blended together, I can create an easily updatable report showing me which sections of the site companies are visiting, with a drop-down to focus in on a particular company.

Imagine what else we can do by combining these data sources! Sales regions can be mapped and reported on in aggregate or by sales team member. Conversion data from GA can be viewed alongside Salesforce information. Name, company, purchase history – all together!

Add Context To Performance

Some of the best applications will be taking real-world information and combining it with our online data. Weather data has often been called out as something we can track and combine. In five minutes, I pulled weather history for July, dropped that into a spreadsheet, and joined that with a Google Analytics property.

Do these two things have anything in common? From the graph, it’s clear, no, not really. But if you work in a seasonal or outdoor company, perhaps you have a direct need for this. Imagine what other data sources could help provide real-world context when blended together.

A few additional ideas:

Chart code changes against key site performance metrics.

Look at calendar or offline events data next to digital conversion rates.

Track ecommerce performance next to total company sales.

Compare Goals Across Google Analytics Views

Ok, this one’s amazing. Google Analytics has a limit of 20 goals per view. Yikes, ouch. No way around this, this one doesn’t even get better with Google Analytics 360. I’m not sure anyone really needs more than 20 goals, but if you do, a common workaround is to create multiple views and get 20 more goals to play with.

But now, you’ve got a tough reporting challenge – you need to grab data from two or more different views and combine them together in some sort of report. This sounds like a job for data blending! If you have two different GA views with the same info, but different goals, keep going.

Add one GA View as a data source to your report

Click Blend Data

Add the other GA View as another data source

Combine on a session-level dimension like Source/Medium, Default Channel Grouping, or Landing Page

Add Goals from each of the data sources

Compare Data Across Google Analytics Properties

Managing multiple websites? Different properties for the same company? Agencies managing multiple clients? It’s easier than ever to combine data to get a holistic report across all of your data needs.

Email Campaigns vs Website Performance

Here’s another great use case – bring in data about a specific campaign and compare open rates and click-through rates in the same table as website performance, goals completed, and Ecommerce performance.

Fun Ideas

We’ve written before about fun use cases for Data Studio, and how our team literally uses for real-world scenarios like health performance, financial monitoring, and more!

“I use Data Studio outside of work to track my small investment portfolio. Blended metrics will save me time spent in spreadsheets and allow me to quickly visualize performance of multiple data sources and better track overall goals.”

Michael Bartholow Senior Manager, Digital Marketing Strategy

Get Blending!

The power is in your hands – start playing around with blended data and see how it can help you! While a lot of this functionality was available in other platforms or programs, remember that we can now blend data sources with all of the additional benefits of Google Data Studio: easy to create, easy to share, easy to refresh.

https://ift.tt/2mddVEh