7 Data Presentation Tips: Think, Focus, Simplify, Calibrate, Visualize++

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elegantThere are three elements to our "big data" efforts, or unhyped normal data efforts: Data Collection, Data Reporting, and Data Analysis.

(More on that here: DC-DR-DA: A Simple Framework For Smarter Decisions .)

We are all aware that the best companies in the world have an optimal DC-DR-DA allocation when it comes to time/money/people: 15%-20%-65%.

All well and good.

But there is one crucial part we often don't invest in sufficiently. The last mile. Data presentation! The actual output that is almost singularly responsible for driving the change we want in our organizations. The thing that is the difference between an organization that data pukes and the one that influences actions based on understandable insights.

I believe we should present our data as effectively as possible in order to first build our credibility, second to set ourselves apart from everyone else who can present complicated graphs/charts/tables, and third allow our leadership teams to understand the singular point we are trying to make so that the discussion moves off data very quickly and on to what to with the insights.

A vast majority of occasions where data is presented (reports, executive dashboards, conference presentations, or just plain here's a automated emailed thingy from Google Analytics ) end up being abject failures because most of the discussion is still about the data. And if you are sitting in a Nth level tactical meeting, that is ok. But if the occasion is a strategic discussion, any occasion about taking action on data, then you need to get off data as fast as you can.

It is hard to do. After all you spent so much time on collection, reporting and analysis. You want to show them all data stuff and how much you worked and how cool your technique was. But trust me, it is better for your career (and, this is a lot less important, but much better for your company/audience :) ) to get really, really good at data presentation.

This post shares eight before and after examples that illustrate seven data presentation tips that I hope will inspire you to look at your report/dashboard/PowerPoint slide in a new light. We will look at some simple errors, and some much more subtle ones that end up limiting our ability to communicate effectively with data.

Here's a quick summary:

#1. Don't be sloppy. Your data presentation is your brand.

#2. Bring insane focus, and simplify.

#3. Calibrate data altitude optimally.

#4. Eliminate distractions, make data the hero!

#5. Lines, bars, pies… stress… choose the best-fit.

#6. Consolidate data, be as honest as you can be.

#7. Ditch the text, visualize the story.

We are going to have a lot of fun, and learn some not-so-obvious lessons.

It's not the ink, it's the think.

An important point first.

This post is not about tufte'ing your work. It is not a post about expressing your inner Excel geek with the most advanced remastered sparklines or conditional scatter plots. Advanced, sophisticated visualizations are important. But I find that so many times people focus on the ink and not the think. Hence all the insights-free data visualizations floating around the web that are totally value-deficient, even as they are pretty.

In this post I simply want you to focus on the think and not the ink. What was the error in thinking? How can you ensure you never make that error? Then, go express your inner visualization beast. :)

[My inspiration for a focus on the think: Bob Mankoff]

Lesson 1: Don't be sloppy. Your data presentation is your brand.

This graph is from an article by the consulting company McKinsey.

It actually shows very interesting data. The article is a bit dry, but valuable.

Yet, I could not get over how sloppy the graph was. For me, and perhaps for others, the sloppiness made the data appear to be an amateurish effort (surprising, given the source) and took away from the deservedly mighty McKinsey brand.

Can you see what the problems are?

email over social media 1

The first problem is that the title is weirdly placed. Then the y-axis legend is even more weirdly placed. The most important part seems to be to get the names of the company, gigantic, over two lines and distracting.

Finally, this is picky, but why is most of the x-axis yearly and then suddenly just until Q2, 2013? And if it is only two quarters of data, why is it taking up the same distance as represented by one year?

Surprisingly sloppy from McKinsey, right?

Watch out for these errors. People in the room (in a small room or a board room or a conference auditorium) will know a lot less about the data than you will, their first impression, and often the lasting impression, might be how clean your data presentation is.

Even without access to the raw data (let's say I'm a busy McKinsey blog post writer), you can make a couple of simple changes to the graph to make it cleaner and less sloppy…

email over social media fixed 1

Clean up the title, rephrase it.

Move the y-axis description to the right place.

Make the source attribution much smaller. If the data is good, people will seek it out. If the data is stinky, no one cares. Either way, why make it intrusive?

Scroll back up. Then down. Much cleaner, right? 30 seconds of work.

If I had the raw data, I would also fix the x-axis and representation of the partial 2013 data. That is still bothering me. But at least you can see what 30 seconds can do.

When it comes to your work, take the 30 seconds.

[PS: The data in the graph is cool, you can see my brief analysis on my LinkedIn Influencer Channel: Email Still Rocks! Social, Surprisingly, Stinks!]

Lesson 2: Bring insane focus, and simplify.

I'm sure you've either seen someone present a slide that looks like, or you've created a slide/executive dashboard like this one. Or, both.

: )

Before you scroll any further, what errors, subtle or obvious, do you see? Don't rush. Give it some thought.

cpc trending brand non brand 2

[Minor Rant: Never, ever, never obsess this much about CPCs. Yes, cost per click is metric. But if you had to obsess about something, obsess about the value delivered to the business. You will never obsess about the cost per trade of your E-Trade portfolio, right? It could go down from $10 per trade to $1, and you could have completely gone bankrupt as a result of your trades. So, don't obsess about CPC. Focus on Economic Value from your search advertising. Focus on Profit from your search advertising. Focus on the outcome. As long as you make a profit, does it matter if your CPC is $1 or $200? And would it matter if your CPC went from $200 to $1 if you were making no profit?]

The metric CPC aside, we do present data like this all the time.

The first challenge is that there is too much of it. We have actuals and we have the YOY change. Then we have it for the company and its category. Finally, we have it segmented into desktop and mobile and as if that was not joyous enough, further segmented into Brand and Non-Brand.

As if that was not enough, the data presentation itself is a bit uninspired.

We can quickly fix it though.

First pick one primary thing to focus on. When you design dashboards this is absolutely critical.

In this case, I believe, the most interesting thing is the YOY change. I bring it center stage, and make the actual CPC as small as I possibly can (in case someone wants it that desperately).

Next I create a simpler data presentation, God bless Excel, by creating two big clusters next to each other. Now it's just a matter of two similar columns that we can distinguish with the use of color.

Here's the result…

cpc trending brand non brand fixed

Again, something very quick you can do. (I'm sure like me you have a favorite custom font you use to make your presentations really yours.)

The orange and purple are easy on the eyes, and distinguish the two clusters nicely. The size of the font used makes the things that should stand out, stand out easily.

Notice because the company performance is all in one row, it is much easier to see that their CPC year-over-year change is less than the category (something harder to see in the original version).

Bring insane focus to your data presentation. If you can, focus on a singular metric for each module/slide/element. Then present the data as simply as you possibly can. And often, you don't need to go very far from the defaults in Excel – though you are welcome to use any software you want.

Lesson 3: Calibrate data altitude optimally.

Here's a more subtle error.

Ignore the ugly graph and the terribly formatted axis, time periods used, etc. All simple fixes.

Look at the text under the graph. Do you see the problem? Don't scroll any further. Look at it again, see the mistake made?

confused paid organic 1

It is not completely obvious, but the Analyst is expecting that in the very short time the leadership team has to look at this data, that they'll also be clever enough to do the math for each row, commit it to memory and then compare all four rows and figure out which video is performing better.

Terrible error in judgment. The altitude is all over the place!

You are the Analyst. You do the math. Then make the hard decisions and figure out how to present data as effectively as you possibly can.

In this case I had to decide what the key point was (this is the think part). I believe it was that using advertising to drive views of a video fueled organic views as well.

That gave me the anchor, paid views. Then it was simply a matter of figuring out the best way to present the data. I decided to use an index of 100. All that's left now is to do the math in Excel and paste it on to the dashboard…

confused paid organic fixed 2

The recipient can get to the insight really fast because there is less data (fewer words and clutter), it is well thought out, and we can move to asking hard questions about performance.

What the heck happened with Video B? And OMG what is up with Video D???

That is what you want, shift the discussion from the data to what happened and what to do now.

Bonus: As the smart Analyst that you are, at this point you'll realized Earned and Paid Views don't tell the full story. So you'll change the table to Total Views and % Earned. You would not have known that's what you needed if you'd stuck with your original textual version! The value of focus and think.

Lesson 4: Eliminate distractions, make data the hero!

Raise your hand if you've not created a slide like the one below for your presentation. Come on!

My hand is raised.

We have all done this.

And it is so silly.

We take the most interesting part, the data, and surround it with clutter that only makes it harder to understand what the point is. The data is the hero, what is the need to have the arrows and the box and the descriptions? Is there any need for the useless stock photos (and what is up with the magnifying glass to represent research, who does that?)? And why repeat "use online sources," is that not obvious in the awfully crafted title?

Look at the image for a moment. Don't scroll. Stop. Really. Don't scroll. How would you decrapify this slide?

Got an answer? Ok, now scroll.

research to purchase process 1

Share your decrapified version via comments below.

My process was to simplify the title to something more direct and easy to understand. Then use three different bars to represent each stage of the process, and to fill each up to represent the percentages. Finally, I'm slightly allergic to terms like awareness and consideration. They are too generic, they encompass too much. So I took the direct route, just wrote down what each bar actually represents.

research to purchase process fixed 1

You can use different colors, mix to suit your own taste. Red in my case is to make the online usage stand out on a very large screen.

I'd experimented with having a break in the gray x-axis (yes, I worry about those things!), it looked nicer. But visually it ended up representing a break, rather than the continuity that each stage represents. Hence the single line you see above.

If you spend sometime on the think , it is so much easier to decrapify the data presentation to focus on the most essential element and make data the hero (again, so that you can get off the data very quickly and have a discussion about what the business should do).

Lesson 5: Lines, bars, pies… stress… choose the best-fit.

If you are a student of the Market Motive web analytics master certification course, you'll note my love for segmented trends rather than snapshots in time when it comes to data presentation.

Trends are often better at delivering deeper insights. And because all data in aggregate is crap, segmented trends are even better!

But, as all smart analysts know, often is not always.

Here's a great example… The dashboard module shows how American's consume media, and how that behavior has changed over the last four years.

Please take a minute and reflect on the graph. Do you love it? Does it communicate the change optimally?

line graph us media consumption 1

You'll agree, the graph is nice and clean. It is easy to understand what is going on. Sure we can line up the numbers on the right correctly, but that is a minor point.

As a Digital Marketing Evangelist, you can imagine I love the data. : ) I was not sure that I love the line graph.

I felt it would take too long to understand just how much things had changed. People would spend too much time trying to understand the graph. And even then, at a deep gut level, not internalize it (even though to you perhaps it is utterly obvious).

My decision was to eliminate the trend. Except for TV, the trends adds almost no value (and even for TV just a little). This allowed me to switch the x-axis to each media channel, they were the heroes here. And finally, switch to a bar graph.

Here's the result….

bar graph us media consumption 1

I believe this version shows the change much more starkly and since you can look at one channel at a time, you can absorb the change much, much faster than with the line graph.

While with the line graph you could see people spent more time with digital than with TV in 2013. The big rise in digital consumption vs. 2010 is much more obvious now. And while TV is physically from Digital in the above picture, you can easily see that one is much higher than the other.

Remember, often is not always. Question how you've always done things. Even question your teacher who might love segmented trended graphs! : )

Understand who your audience is, think about the point you are trying to make with your analysis, and then use the best-fit data presentation method.

Lesson 6: Consolidate data, be as honest as you can be.

This example comes from a presentation. The data was spread over two slides. Notice how nicely it is presented.

The first slide showed the desktop and laptop performance for search traffic for puppies (real data below, just not that category!)…

searches for puppies desktop

It is easy to see how puppies are doing in context of the average number of searches for land animals and sea animals. Put another way, company performance compared to two benchmarks.

The second slide illustrated the mobile search performance for puppies, and compared it to the same categories…

searches for puppies mobile

Both sets of data presented simply. You cannot misunderstand it.

So, what is the problem. Look at the graph above carefully. Then scroll up a little more, look at the first one. Now scroll back down.

See the problem?

One obvious problem is, why spread the data on to two different slides? Most people are terrible at keeping track of things as they jump slides/pages.

The second problem is more subtle.

The graphs make it seem like there are two similar sized problems to deal with for us as PuppiesRUs Inc. But that is not really true. Look at the y-axis.

Perhaps, for a good reason, we want the company to believe that they are similar sized problems because our company sucks at mobile and we want to light a sense of urgency under our collective butts.

I believe as an Analyst we should be as honest as possible in these cases. (I'm NOT implying that there was a deliberate attempt to not be honest above.) We should show the data in as honest a way as possible, we should be as objective as possible.

I simply took the data in the two graphs and put it on to one graph, same bar graph, and fixed the title to make the presentation simpler (I hate long complicated titles).

In an attempt to pay an homage to the importance of mobile, changed the color to red…

searches for puppies fixed

To our leadership team, the recipient of our presentation, it is really clear how we are performing overall and in mobile.

It is also clear that desktop plus tablet, blue, is the most important area of focus. We have to keep the pedal to the metal when it comes to that. But that mobile is also an important area deserving some dedicated focus.

There is no chance that they will inadvertently think the size of both the opportunities is the same.

An effective presentation of data by 1. consolidating it and 2. having it play off the same y-axis.

Lesson 7: Ditch the text, visualize the story.

Often we hear that data is overwhelming or that graphs are evil or that tables suck or… well, I'm sure you've heard it all.

Our response to that is to try and "simplify the story" by eliminating all that and just writing the insights in text with a big summary number.

That strategy does work some times. More often than not you end up with something super-ugly and value-deficient like this…

search data puke 1

Imagine yourself to be sitting in the audience and trying to internalize everything that's going on here! I'm sure someone is going to walk you through it. But still. Do you think there is any chance you can grasp the multiple agendas at play above?

I seriously doubt it. Scroll back up. Look at it!

Even if you only have two minutes, all I had in this case, it is pretty easy to fix the above textual representation and make it much easier to understand what is going on.

First, get your custom font. Ok, kidding.

First, think of what the key point is and replace the long red-book ended title with it. In this case: Search Opportunity.

Then draw a bar in PowerPoint, eyeball the size (no, really, don't even go in Excel to create the graph, no one is going to notice!), and fill in the sub-components.

For data you can't find an obvious home for, use call-outs.

Two minutes later…

search simple data presentation 1

So much easier to see that story is about how many people search for our company topics and that weight management and monitors are the most interesting. In this case we have the data that can fill out rest of the bar, but we want the leadership team/audience to focus on just two and those are the ones you see above.

It is less obvious how to illustrate the mobile growth. Two more bars? Perhaps a heat-map showing high and low? Nah! Just add two call-outs and you are done!

When the data's end state is a PowerPoint/Keynote presentation, use the fade transition (all other transitions are evil) and bring one piece of data at a time up on the screen. It will look beautiful and the audience with stay with you as you narrate other insights you know that are not represented on the slide. [A style of presentation you should use every time you present anything.]

Here's another example of eliminating text, reducing complexity, focusing the the key point and visualizing data simply to get off the data quickly and discuss actions.

Pause. Look at the example below. What is done right or done erroneously? If you had to improve on the power of communication for this example, what would you do?

Pause. Really think about it. Got it? Now scroll.

media targeting efficiency

The first simple mistake you likely won't make as an analyst is to use two different things to represent the same number. For example, either stick to the dollars or use the percentage. This might not seem like a big deal in isolation, but every little bit like this takes a tiny bit of your credibility away and it causes the audience to have to shift their minds a little. Over a number of these types of mistakes in your dashboard or your presentation take away 0.25% here and 0.5% there and 1% somewhere else. Taken together, you lose 30%. Why dig that hole for yourself to have to climb out of?

The second simple mistake, obvious in hindsight I'm sure, is that there is simply too much text. Why not simplify the data presentation to make it boom (!) impactful right away?

I did like the map, but it was intrusive. So my first act was to take the map, fade it out (use a white transparency, 13%). It is there, but it is not in the way.

Then I did not like the numbers, they don't add any value. Just throw in two simple bars (standard shape in PowerPoint, no Excel necessary), and add a touch of color to show targeting efficiency of TV and Radio. Finally add the bridging text and use the brace (use the little yellow handle to drag the brace so it is aligned) to show how well or badly each media channel is doing.

Red is bad, blue is good….

media targeting efficiency fixed

Scroll back up. Then back down. Then up. Then down. (Think of the Old Spice ad! :)

The presentation is simpler. Even without reading anything you can get a sense for what is good and bad. The questions will come fast and loose: Why do we do TV? And if there is 75% leakage, is it still worth it? What is the optimal media-mix for our efforts?

We believe that summarizing our findings in text is the solution. We believe tables and graphs add complexity. We could not be further from the truth.

Closing Thoughts.

It's not the ink, it's the think.

It takes a tiny amount of time to really look at the data you are presenting, really think about what you are trying to say and identify the singular point. Once you know that, it is only a couple of minutes of work to decrapify the report/dashboard/slide/spreadsheet and ensure we are presenting data as simply as possible using the most optimal visual.

You worked so hard to collect the data. Then invested all that time and energy in reporting it. Finally, really dug deep, did the analysis. Don't stop there. Spend time optimizing the end product. Your goal: Get of the data as fast as you can, switch to the discussion of actions.

Victory, I promise, will be yours!

As always, it is your turn now.

Which one of the eight examples above is your favorite? And the least? Would you have taken a radically different approach on any one of them? Care to share your version? What are your go to filters for taking something complicated and making it simple? What is your favorite annoying data presentation method? Is there a visualization strategy that consistently helps you switch the discussion from talking about the data to talking about what to do with the insights?

Please share your insights, recommendations, critique, alternatives and complaints via comments.

Thank you.

7 Data Presentation Tips: Think, Focus, Simplify, Calibrate, Visualize++ is a post from: Occam's Razor by Avinash Kaushik

February 25th 2014 Search Engine Marketing

SEO 101: Beyond the Basics

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SEO BasicsA phenomenal amount of material has been written about Search Engine Optimization (SEO) over the past decade (plus).

Although much of the material is still applicable, the amount of out-dated SEO tactics that are still being touted as best-practice is growing.

The other day, I read SEO 101: Beyond the Basics, a 31-page complimentary white paper / ebook that outlines current best practices that companies of all sizes can use to increase site visibility, increase traffic, and most importantly, improve conversion rates.

In this very well-written ebook, you will learn:

  • How search engines make money (and why it matters)
  • Why you need to know your audience and what they want
  • All about keyword usage
  • Best practices for writing post content on your blog
  • How to optimize posts, pages and your entire site
  • and more…

I appreciate that this book emphasizes the techniques and tips that I teach at Rosalind Gardner’s Academy for blogging affiliates. :-)

If you are not already a member of our Academy, pick up SEO 101: Beyond the Basics for free now. You will have to either supply your info or login through LinkedIn to access it, but it’s worth it.

Get the facts about what works now, so that you too can increase traffic to your website / blog.

Comments, questions or suggestions? Please leave a comment below!



Empowering Analysis Ninjas? 12 Signs To Identify A Data Driven Culture

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focusedEvery indicator we have is that companies are investing more in every facet of analytics. Tools. People. Consulting. Processes.

Yet, it is unclear if that increase in investment is being followed by a commensurate increase in value delivered to the organization's bottom-line.

A part of reason for this mis-match in value delivered is that there is a natural evolution that needs to occur. There is an analytics ladder of awesomeness each company needs to climb, and it just takes time. But a larger part of the reason is that companies don't quite make the right choices in what behavior to incentivize, they make mistakes when creating the organization structure, and in the expectations that are set for what success looks like.

First… it is important to realize that big data's big imperative is driving big action.

Second… well there is no second, it is all about the big action and getting a big impact on your bottom-line from your big investment in analytics processes, consulting, people and tools.

So in this post, let's look at twelve signs you can use as signals to identify if your organization is set up for magnificent success. Each sign is essentially an action you can take, expectation you can set up. It is specific, it is, this will not surprise you, impactful.

#12: Almost all reporting is off custom reports.
#11: Close to zero aggregated analysis exists, everything's segmented.
#10: The KPIs in your DMMM reflect your company size/evolutionary stage.
#9: Your qualitative analysis practice rocks like crazy!
#8: Your Team's DC, DR, DA effort allocation is 15%-20%-65%.
#7: 25% of all analytical effort is dedicated to data visualization/enhancing data's communicative power.
#6: All automated reports are turned off on a random day/week/month each quarter to assess use/value.
#5: 80% of your external consulting spend is focused super-hard analysis problems.
#4: The Analytics/Marketing skills in your Analysis Ninjas is 70/30.
#3. Your organization structure for magic with numbers is: Centralized Decentralization.
#2. The organization functions off a clearly defined Digital Marketing & Measurement Model.
#1. You know what your Return on Analytics is!

Before we go too deep, let's get a couple of definitions right first.

Reporting Squirrels vs. Analysis Ninjas.

No company hires anyone called a Reporting Squirrel. Everyone hires what they believe are Analysis Ninjas. Leaving people skills and capabilities aside, it is the work the employee does that makes them a Squirrel or a Ninja.

Reporting Squirrels spend 75% or more of their time in data production activities. The primary manifestation of this is in creation of reports for their direct leader, or team or division or bunch of people. In service of report creation the job includes: Pulling data, writing queries, fulfilling ad-hoc requests, scheduling data outputs (reports, dashboards), liaising with script implementers / IT teams to collect more data, etc.

Analysis Ninjas spend 75% or more of their time in analysis that delivers actionable insights. The primary manifestation of this is expressed in English (or native country language). An example is: "We should add these 80 keywords to our PPC portfolio with a max bid of $14." Another example is: "I recommend a shift of $150k from our Display budget to our Affiliate budget to increase profitability of our purple pants." In service of analysis the job includes: Pulling data, segmentation, slicing and dicing, drilling-up, drilling-down, drilling-around, modeling, creating unique datasets, answering business questions, writing requirements for data sources and structures for Reporting Squirrels to work with IT teams to create, etc.

Again, remember no company actually hires anyone called a Reporting Squirrel. Most companies hire a Web Analyst, Sr. Digital Analyst, Web Analysis Guru, Digital Marketing Analyst, so on and so forth. (Remember none of these jobs will do any data collection/IT work, even in medium-sized companies.) But if their primary output is just data, and not actions to take expressed in English or verbally in weekly senior staff meeting, then they are simply Reporting Squirrels.

It is important to understand this difference. If you remain delusional about this difference, your Return on Analytics (ROA) will remain negative.

reporting squirrels analysis ninjas

It is also important to understand that many medium and all large-sized companies feel need Reporting Squirrels. Primarily because they believe that the mere act of data regurgitation makes the organization smarter. (They ignore the obvious flaw that people upon whom this data is regurgitated often do not posses skills to understand the data, ability or access to ask clarifying questions of the data or key context to transform the regurgitated data into insights.) To convince them otherwise is a lost cause, they just feel they need Squirrels, they will hire Squirrels, you can make good money being one, neither I nor anyone else will ever advice against taking this job.

But, it is important for you to understand the difference for the impact it will have on your career. I recommend a honest self-assessment (after all you don't have to tell anyone the results). It is important that your company understands that there are two different roles. If the company has the revenues or size, it is important to hire for both roles to ensure the ROA will be positive.

Reporting Squirrel work has a minor incremental impact on a company's bottom-line, and rarely justifies the investment in analytics tools, people, consulting and processes. An Analysis Ninjas' work does. So let's look at the twelve signs that your company has an environment with incentives to move Reporting Squirrels work to become Analysis Ninja work and set up a structure where Analysis Ninjas thrive.

#12: Almost all reporting is off custom reports.

This one is so simple, and a great first step to incentivize Ninja behavior: Stop accepting any standard report from any tool.

All standard reports are simply the vendor engineer's attempt to showcase the data in the tool. They are generic mash-ups that tailor to almost no one's needs, and more often than not contain awful things like nine not-really-thought out metrics for one dimension in a report.

This means they don't apply to you, despite valiant attempts by your Squirrel to add Secondary Dimension or a in-line filter.

Force your analytics team to create custom reports. Rather than using standard reports to deliver they they think you need, they'll be forced to pause and ask you: "And what business question are you trying to answer?"

Kisses. Hugs. Angels singing!

Creating custom reports is hard work. You need to take the business question, distill it down the the core four or five metrics needed, identify relevant dimensions, add the filters to narrow and focus the scope of the data provided and include contextual drill-downs to aid decision making. (There in a nutshell are the four requirements of a complete custom report.)

search marketing data analysis vp digital

In the process you've created an incentive for the Squirrel to talk to the business folks, understand the actual business needs, upon creation of the report really look to see if it answers the question, what the answer is and if it really matters to the company (Ninja-work!).

Mandating only custom reports will not by itself lead to nirvana (see the 11 additional signs below), but it is a great first step. It incentives asking of questions, it reduces cookie-cutter implementations that so many Squirrels or external consultants will foist on you, and it increases the quality of what you get: An almost insight.

That is worth fighting for.

Bonus: Download: Three awesome analytics custom reports. Collection of end-to-end Paid Search analysis reports.

#11: Close to zero aggregated analysis exists, everything's segmented.

All data in aggregate is crap.

Total revenue. Number of Monthly Visits. Average Time on Spent. Site Conversion Rate. Downloads. App Installs.

There is an initial OMG that is how much we are selling to those many people! OMG! OMG! But since those numbers have no context or drill-downs, people get over it very quickly and set your automated data output to auto-delete.

Segmentation is the process of identifying important clusters inside your data.

For example, which countries contributed to total revenue. Or, which pool of customers is most profitable. Or, which campaigns cause the type of repeat visits that deliver 250% higher average order value? Or, which products are loss-leaders for people from Saskatchewan compared to Manitoba?

Once a custom report is created, asking for segmentation incentivizes the asking of the next layer of questions that will almost directly lead to an insight that will lead to a action by the business. So insist that no piece of data (report, dashboard, sexy table) will ever be presented without relevant segmentation.

cohort feb cpc 1

When you review the portfolio of segments being used by your Squirrels, ensure that they have Acquisition, Behavior AND Outcome segments.

Additionally a sign of mastery of segmentation analysis (only likely if you have Analysis Ninjas, hence a good test) is if you see User, Sequence and Cohort segments/analysis, along with the normal Session and Hit level segments/analysis.

Bonus: Download three awesome advanced segments. Marry custom reports to advanced segmentation for deeper insights!

#10: The KPIs in your DMMM reflect your company size/evolutionary stage.

(More on the Digital Marketing & Measurement Model, DMMM, in #2 below.)

Because we have access to so much data in Google Analytics, WebTrends, Adobe Analytics et. al. the instinctive response of the Squirrels is to go grab the most obvious metrics and start partying. Visits! Time on Site! Pageviews! Hurray! Hurray!

While these metrics sound good, and yes they do get a bunch of press coverage (they have good PR Agents), they are rarely deeply relevant and even more rarely yield valuable insights into business performance.

Pick hard metrics to designate as your key performance indicators. Ensure that they reflect the size of your organization, and its current evolutionary stage. This will set significantly higher expectations for your analytics team to understanding business needs, work harder on the KPIs to find insights, and to deliver a more relevant higher quality outcome (in custom reports with advanced segments applied).

A very good incentive.

Here's an example of KPIs that set a higher standard to meet for small, medium and large businesses, and measure end-to-end success…

best metrics small medium large business 1

You don't see Business Profitability up there, it is only for the Super Analysis Ninjas. If you measure true business profitability, you'll unleash so much Analysis Ninja power it will blow your mind.

Hence the importance of picking the right KPIs. They incentivize optimal Ninja behavior vs. useless data regurgitation.

Bonus: Kill Useless Web Metrics: Apply The "Three Layers Of So What" Test. Four Useless KPI Measurement Techniques.

#9: Your qualitative analysis practice rocks like crazy!

One sure sign of asking for more, forcing more Analysis Ninja type efforts is to have a robust qualitative analysis practice in your company. They force the Reporting Squirrels to move beyond their obsession with Site Catalyst and web analytics data. But the most important impact is that they will get access to a why source of data in addition to their what source of data.

(My second blog post covered what and why! Overview & Importance of Qualitative Metrics.)

Three primary types of qualitative analysis that should be a part of your raised expectation set are: Heuristic evaluations. Usability testing (lab based or online). Surveys.

Heuristic evaluations, as you'll read in the post, are simple and easy to do, all you need are resources you already have. Your goal should be at least 4 evaluation sessions a month.

Usability is now so affordable with so many good online options. Your goal should be at least 5 tests per month.


And finally by surveys I don't mean the 40 question puke of a survey that you are torturing your website visitors with right now! The world's greatest survey only needs you to ask three questions. Just three to get 85% of the actionable value you'll ever get from any survey (no matter how long you make it!). Your goal should be to have a task completion survey live on your site at all times.

What plus Why will create a powerful combination allowing your team to act like real Ninjas and arrive at actionable insights that can be presented in English and in lay terms. And guess what, that drives an impact on your bottom-line!

Bonus: In addition to qualitative analysis, Super Analysis Ninjas also engage in incredible competitive intelligence analysis. Do yours?

#8: Your Team's DC, DR, DA effort allocation is 15%-20%-65%.

Now that we have focused on the types of actual work that our analytics resources are engaged in, it is time to shift to the core of what we started with when we discussed the difference between a organization that has Reporting Squirrel work vs. one that has Analysis Ninja work.

I've split that into three pieces (simply to acknowledge the effort of our IT brethren): Data Capture, Data Reporting and Data Analysis.

Each quarter, if your practice is new, else every six months, audit the time spent by your analytical resources (in-house or consultants). Here is what the allocation looks like for organizations that are empowering Analysis Ninjas…

data capture data reporting data analysis

What does your effort distribution look like?

If you would like to evolve to the above distribution, and you will have to if you want positive ROA, here's a post with more details and helpful guidance: DC-DR-DA: A Simple Framework For Smarter Decisions.

#7: 25% of all analytical effort is dedicated to data visualization/enhancing data's communicative power.

Now that you understand the overall distribution of effort, I want to place a fine point on one facet of work that is truly Analysis Ninja work: Data Visualization.

Let met hasten to add I don't mean making things pretty or creating a data-pukey infographic. I really mean effort that enhances data's power to communicate effectively.

Reporting Squirrels so rarely have an incentive to focus on this, their time is taken up in shoveling the data. This is Analysis Ninja effort. Hence it is critical. After all, what's the point of all that data if it can't speak?

25% of all analytical effort should be dedicated to this quest. It is simply that important.

At the simplest level this is taking what we do every day and making it significantly easier to understand…

simplifying data presentation

Learn more, and how to, here: Excellent Analytics Tip #21: Convert Complex Data Into Simple Logical Stories.

Or it is leveraging a tag cloud or using conditional formatting or weighted sorts or many of the other simple techniques to allow data to speak for itself.

A more complex example might be to use Streamgraphs to visualize trends, patterns (say seasonality) for a chosen metric and dimension…


And perhaps an even more wonderful example might be to use Sunbursts to present a radically different way to understand content consumption patterns of users that lead to a desirable outcome for your business…


Dedicated data visualization efforts will transform the efficiency with with your organization identifies insights (go Ninjas!) and the speed with which these insights can be communicated (this time without English!) to drive big, impactful action.

Hence my recommendation that 25% of all analytical efforts be dedicated to this magnificently valuable venture. You'll separate the Squirrels from the Ninjas pretty quickly, and create the right incentives.

Bonus: Win Big With Analytics: Eliminate Data & Eschew Fake Proxies.

#6: All automated reports are turned off on a random day/week/month each quarter to assess use/value.

Over the years I've developed an allergy to data automation efforts. They are almost completely useless.

The primary reason for this is that automation is based on the assumption that every single day/week/month the question we want answered with data is exactly the same. While that was true through early 1900s, it is no longer true. The world changes too much every day.

Automation also contains the assumption that the person being regurgitated will look at this finite set of auto thingy and will get all their questions answered. This will only happen if nothing changes in the auto regurgitated thingy. If something changes, the first question will be why and then its useless because they have to call someone, open a ticket, get access, wait seven days.

data reporting automation

In a small number of cases automation is ok. The CxO is expected to take zero action. They have their five KPIs, they just want to know how things are going and then take the next sip of their expresso. If they see something interesting, they still won't have any responsibility to do anything, they'll just shoot an email off to someone else (or raise a withering eye in a meeting!). For all such use cases…. Fine, automate their dashboard. There might be a couple other scenarios, but not that many.

In summary: Report production can be automated, analysis can be to a small tiny extent, but identification of insights to action can't be automated. Yet.

Now the reality is that people will want automation. It just seems so good on paper and in our hearts. If you can't avoid it, make sure your analytics practice has this process: Turn off a random number of automated reports/dashboards/widgets/data blah at least once a quarter. See what happens.

If you are kicking at a Ninja level, you'll have this practice for daily reports, weekly reports and monthly reports. The practice will lead to automated culling of automated stuff that no one misses, or does not drive action.

For your Analysis Ninjas, elements of their job will be automated. Certain data pulls, certain initial data mashing, etc. But the actual job of finding insights can't be automated and never will. If they say it is automated, you have a Squirrel faking it as a Ninja.

#5: 80% of your external consulting spend is focused super-hard analysis problems.

Consultants are a key part of what will get you to glory faster, and more number of times.

As a young company (Stage 1) you might use them to massively accelerate implementation and deployment. (More on each stage, what you should own vs. what the consultant should do here: Web Analysis: In-house or Out-sourced or Something Else?)

consultant 2dclient 2dstages

The problem is that due to our under-powered expectations or consultant's lack of skills, that is all we expect of them after the initial implementation plus deployment engagement of three months.

We might add automation of reports (eeek!) to their work load, and data starts getting regurgitated. Because all that automation just shares data, your employees will simply ask for more data (only insights in English drive action). So that leads to more regurgitation.

A real sign that you are empowering a Ninja culture is that you'll be in Stage 4 in 12 months or less (assuming you start from scratch in month one). Your consultants are handling challenges that you have no capacity to deal with (media-mix modeling, complex non-line behavior analysis, controlled experimentation, customer lifetime value optimization etc.). They will be adding real and material value by closing your sophistication gaps, by helping you innovate on the bleeding edge.

If you hire consultants, and they are not in Stage 4 (or 80% of their efforts powering advanced DA) then you have Reporting Squirrel consultants faking it as Analysis Ninjas. That is ok. Recognize that. Pay them accordingly, and accept your company's lack of improvement.

#4: The Analytics/Marketing skills in your Analysis Ninjas is 70/30.

The type of people you hire is critical in creating a Ninja culture. (Yes, yes, yes, tools are important and vendors are amazing, and all that stuff. Remember the 10/90 rule for magnificent analytics success.)

Here's a typical job description for a Sr. Web Analyst: "You have experience working with advanced web analytic methodologies, rich data techniques, experimentation, A/B & Multivariate testing. You have a passion for data and information that allows for laser focused strategies and decisions to be made. SQL and web analytics is your wheel house."

And that is important, it will form the bedrock of their skills. (Please, please, please do not ask for 15 years of "advanced web analytics experience," it does not exist and you are mistaking white hair for wisdom.)

70 30 people

But also look for 30% of their skills to be in immediately adjacent areas. For most digital analysts, that is marketing (online and offline), persuasion, communication and customer service. If you are unique to a certain niche, look for the 30% to be in areas immediately adjacent to that core niche. In your job description ask for it, in the interview ensure they have them (along with testing for critical thinking).

Focusing on just numbers skills overlooks the importance of other things that are key when it comes to just looking at data or making magical sense of it all. For the latter you need a much deeper understanding of business strategy, marketing objectives, customer experience and competitive realities. That's where the 30% skills play such a key role.

You will need people who can understand the See-Think-Do framework, or have the knowledge to create a new business framework for you because they are so good at business and analytical thinking! You will need people who can not only understand data, but data myths that get marketing people fired .

You hire narrowly, you'll end up with a Reporting Squirrel even if you call her/him the Director of Web Intelligence Services.

Are you hiring current/future Analysis Ninjas, or one-trick ponies?

Bonus: More on one-trick ponies and the 70/30 rule.

#3. Your organization structure for magic with numbers is: Centralized Decentralization.

Do you have an organization structure that will incentivize Analysis Ninja behavior, and where Analysis Ninjas will thrive?

centralized decentralized distributed 1

Some organizations have a centralized org structure for their analytics practice. This is ok for small companies, it falls apart pretty quickly for larger companies (or worse, evolves into an order taking bureaucratic IT organization).

Others have a completely decentralized structure work at some level. But with everyone doing their own thing it ends up being a structure were there are no efficiencies of scale, little incentive to innovate, and almost no optimizing for the global maxima.

In Chapter 14 of Web Analytics 2.0 I describe my favorite org structure: centralized decentralization. There is a lean (# of people) and agile central tem that is responsible for all the pro's you see mentioned above and also satellite lean team (of one or a very small number of people) in the BU's / divisions, that are responsible for the pro's you see mentioned above for decentralized teams.

Any company hoping to empower Analysis Ninjas will have a model very close to centralized decentralization.

Bonus: Who Should Own Digital Analytics? A Framework For Critical Thinking.

#2. The organization functions off a clearly defined Digital Marketing & Measurement Model.

You can do every single one of the above ten things and still fail.

Sad, isn't it? So much work, and still fail? Yes.

The single biggest reason for failures of your big/small/tiny/giant data effort is simple: A lack of any connection between the data effort and business priorities.

Your Squirrels or Ninjas spend valiant efforts, find amazing data, incredible insights, and yet if they are not aligned with business priorities nothing will get actioned. Causing incredible waste (and frustrated Squirrels!).

Yet, most senior leaders don't know how to answer the question, what should our analytics efforts focus on? Or what questions we can answer with data? The latter especially results in a massive laundry list of stuff for the Squirrel/Ninja to do, and still no tie to the business.

I'd developed the Digital Marketing and Measurement Model as a simple five step process that each organization can go through on a quarterly basis. At the end of the process, in which Sr. Leaders, Marketers and Analysts provide input, you end up with extreme clarity on what's important to the business, what data and analysis to focus the analytical efforts on. No running around. No making stuff up. Extreme focus and tie to business.

You can create a DMMM for a non-ecommerce (with goals and goal value!) content-only site like the one you are on now…

dmmm occams razor 1

And you can definitely create one for your for-profit or ecommerce digital efforts…

digital marketing measurement model step five

A clearly defined and well understood digital marketing and measurement model is absolutely critical in creating a culture that empowers Analysis Ninjas. It brings a sharp focus to their work, it ensures their insights will be actioned, and that in turn brings joy to everyone's lives. As a bonus, it forces the company leadership to really, really, think about what they are solving for with digital – such a big gigantic bonus!

Bonus: Five-Step Process for Creating your Digital Marketing and Measurement Model.

#1. You know what your Return on Analytics is!

The surest sign that you've created an organization that is truly rocking analysis, and empowering Analysis Ninjas, is that on a quarterly basis you compute your Return on Analytics (ROA).

Everyone in the organization gets measured and every dollar spent is evaluated in terms of the resulting addition to the bottom-line (or cost savings delivered), why not analytics?

Here's the formula…

return on analytics spend formula details 1

If you have Reporting Squirrels in your company, this is an impossible task (and they'll tell you that). If you have Analysis Ninjas in your company, this is not hard at all (and they'll tell you that as well!).

Beyond that delightfully satisfying test, measuring ROA ensures that your senior management team is aware of the value your big data efforts are adding to the company. That in turn results in their full support and incremental investment in analytics efforts, which in turn fuels a virtuous cycle that leaves the employees happy, the senior leadership delighted and the company richer.

What's not to love?

Bonus: Download the Return on Analytics Calculation Model.

That's it. Twelve signs that your company has created the optimal incentives, structure and expectations where Analysis Ninjas will thrive, or evolve to if you only have Reporting Squirrels today.

Truly Data-Driven Analysis Ninja-Empowering Achievement Guide.

Go ahead and do a diagnostic of how many of these signs exist in your company. Here's how to grade yourself…

If signs 9, 10, 11, 12 exists, you have the core foundations required. Level bronze achieved.

In addition to that, if signs 5, 6, 9, 8 exist, you are the envy of your peer group. Level silver achieved.

In addition to that, if signs 2, 3, 4 exist, your financial performance is constantly discussed on CNBC! Level gold achieved.

In addition to that, if sign 1 exists, you are so successful and dominant as a company you are about to be sued by the government because they are confident you are doing something illegal (except you are not). Level platinum achieved.

What if you have random signs form various levels? 3, 7, 11? You likely run a Reporting Squirrel farm. The clusters, as identified above, are the key in achieving each level successfully and scalably.

I wish you all the very best.

As always, it is your turn now.

Are you in an Analysis Ninja or Reporting Squirrel work role? Do you agree with the 12 signs outlined above? Is there a sign you've found to be a key indicator that's not mentioned above? Which of the 12 signs has proven to be most difficult for your company, current or past? Do you have a tip, or five, to share with others of things you've done to get to level platinum? What is the single biggest barrier Analysis Ninjas face? If you could only pick three signs for your company/country, which ones would they be?

Please share your critique, insights, stories, examples and helpful guidance via comments below.

Thank you.

Empowering Analysis Ninjas? 12 Signs To Identify A Data Driven Culture is a post from: Occam's Razor by Avinash Kaushik

January 7th 2014 Search Engine Marketing

Rap Genius Searches for New Traffic Tactic After Google Slap

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It’s a good thing Rap Genius has an app coming out next week, because it just lost more than half its typical mobile Web traffic thanks to Google

Rapper Nas in a Fila headband

Rap Genius has been in battle mode for the past couple days. Google penalized the site —where people go for musical lyrics and other media—over apparent violations of its search engine code of conduct, involving link kickbacks.

Rap Genius revealed its own search scandal by publicly soliciting bloggers to post links to the site in exchange for tweets. It’s not arms for drugs, but Google takes any system gaming seriously.

Today, if a person Google searched for “Rap genius,” its website was nowhere to be found—the equivalent of online annihilation. Rap Genius, which has raised $15 million from venture capital heavyweights like Andreessen Horowitz and counts about 40 million unique visitors a month—saw its traffic drop about 64 percent today following Google’s downgrade, according to Quantcast data.

Most of that traffic comes from the mobile Web, which makes the company’s app next week an even more important launch. It was unclear how long Google would suppress the company’s results, but JCPenney was once penalized in search rankings for 90 days.

“The app will make us less dependent on Google,” co-founder Mohbod Moghadam said. “Everyone is screaming for an app.”

One of the major features of the app, built for the iPhone, is a song detector that calls up lyrics to whatever is being played through speakers—using Shazam-like technology.

With more than half of Rap Genius users visiting on mobile, the founders hope that the app will be the gateway to the site instead of Google. It’s part of a broader strategy that only has been made more urgent by the Google punishment.

Moghadam said that Rap Genius has more than 1 million registered users, but that’s only a small fraction of total visits. The company hopes to convert those lurkers—just passing through—into sign-ups.

Rap Genius is known for more than posting hip-hop lyrics, and the site has expanded into categories like rock music, art, news, fashion and poetry. It allows users to add publicly edited and ranked annotations within the content. For instance, famous singers could explain their lyrics by posting notes within each line.

Moghadam revealed some of the more advanced visions he has for the app, including allowing famous people to upload video clip annotations—about 10-seconds long—directly from mobile devices.

He said he also is petitioning brands to create verified accounts. The platform is moving beyond text into images that might be suitable for fashion content.

Rap Genius already is exploring the concept of sponsored or promoted annotations. The clothing maker Fila, for instance, posted a photo within a post about Nas lyrics in which the rapper mentions the brand. Moghadam said he is going after other brands like Karl Lagerfeld and Hublot.

They are also working on annotation platforms that are powered by Rap Genius but exported to other publishing sites.

Moghadam said he wouldn’t comment any further on the search engine troubles. However, Danny Sullivan of Search Engine Land, a site dedicated to the industry, said he was unsure Rap Genius even broke the rules.

Google would likely restore the rank shortly, he said.

“Google can’t do more than wrist-slap them for that,” Sullivan said in an email. “People searching for ‘Rap Genius’ expect—and should get—the actual site coming up first.”


Digital Marketing And Analytics: Two Ladders For Magnificent Success

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step by step The most common mistakes digital practitioners and leaders make is to either do things in the wrong order, or to try and do too much at one time.

Progress in digital marketing and analytics in either scenario becomes painful (the organization / systems / thinking is simply not in the optimal position). People become frustrated (you hire smart people, they run off to build you the Taj Mahal, meanwhile you don't have a functioning toilet). Business results suffer.

There is something in humans that makes us want to do the hard things, to shoot for the most complex right away, to want to be challenged to infinity. In many cases, it is a tendency we have to learn to restrain.

More often than not, magnificent success results from executing a business plan that is rooted in a strong understanding of the landscape of possibilities, and a deep self-awareness of business capabilities. These business plans will contain a structured approach, do this, then do this2, then make sure we are really good at this3, then this 4 and so on and so forth.

In other words: Evolution. It works.

Said another way, digital revolutions more often than not fail. One day your leadership realizes you stink at digital (all of it or just Facebook or search and display or mobile or whatever). They find the closest industry leader (L'Oreal, Booking, Zyrtec, Innocent Drinks, CSC Consulting). They say: "Do whatever we need to in order to get there in 90 days. Go!!"

If you hear that, run. Else you'll be standing in a place where a flaming crater will appear in the near future.

I'll be the first to admit that selling evolution is hard. Revolutions just sound so darn sexy! Still, reality is reality.

In this post I want to arm you with the evolution you should undertake in your companies when it comes to marketing and analytics. Additionally, I'll make the hard tough difficult painful choices on your behalf and order things to deliver the highest possible impact, so you'll know exactly what to do and what you will get from it all.

In other words: Two inspiring ladders of awesomeness for you! One for digital marketing and one for digital analytics.

Your ladder might look a little different, but I hope the process I follow will help you make the hard choices most relevant for your company and the evolutionary position it finds itself in.


Digital Marketing: Ladder of Awesomeness/Sustainable Success.

My current title is Digital Marketing Evangelist so you can just imagine how absolutely excited I am about all the digital possibilities. Owning audiences, instead of just renting them. Earning time, instead of just buying it on TV. Creating persistent relationships, instead of just transient ones. Not letting budgets limit our creativity. And so much more. I'm like a kid in a candy store. I want to do everything right away. I want to go from single cell life to fully formed homo sepians in seven days.

I've also discovered that that is the easiest path to failure. : )

So, based on my spectacular successes and painful failures around the world, I've developed a ladder of sustainable success. Here is what it looks like:

digital marketing ladder of magnificient success 1

Let's look at each step on the ladder in some detail.

The very first thing you want to do is create an acceptable website. One that reflects the customer expectations of 2013. A good example, for e-commerce and non-ecommerce sites, is http://www.csc.com/. Look at the colors. Look at the icons. Look at the way the text is laid out, how video is incorporated, the structure of the site and everything else. Your first job is to beat them at everything. During this stage you should also invest a lot in Search Engine Optimization. You will have great content, in a good experience, and focus on getting free traffic.

[To learn more about the Do in stage one please review my See-Think-Do-Coddle framework for content, marketing and measurement.]

Second, create the world's greatest mobile experience. Yes. Don't do paid search. Don't run to buy display ads. Definitely do not start Tweeting or embarrassing your brand on Facebook (we'll do that in a bit). Focus on the mobile experience. Because of this lovely graph from Business Insider and it's representation platforms people use to visit top destinations….

business insider mobile visits behavior

Scary, right? Exciting, right? Focus on mobile like crazy, tablets in particular. Beat CSC's experience. Beat Motrin. Beat Beneful. Don't be like IBM's tablet experience (old, substantially brand negative). Or Ford (it is amazing that in 2013, for such an expensive product, it looks so…. 2005).

Now that you have build a decent foundation and are getting a decent amount of free traffic you know what is working and what is not, you are ready to move to step three. Start investing in your email marketing strategy for extending relationships, and your paid search strategy for brand terms. Email allows you to start building a owned audience that you can (if you don't stink) start relying on (rather than constantly having to rent them from TV or Google). People typing a million variations phrases with your brand terms are looking for you, make sure you show up and capture the traffic you deserve.

Step four is focusing on expanding your reach to new relevant audiences. The cool part about display advertising is that we can build our brands cost effectively, introduce our products to a new audience, and create demand based on a number of intent signals (this last part is often missing from offline media). Based on what people read, what sites they've visited, their demographic and psychographic signals and so much more. Don't go all crazy with display ads, just focus on your brand, products and services. Learn, get better, try some more.

The site is now working well across platforms, we are starting to get a lot of free and some paid traffic, we are optimizing for conversions and task completion rate, time to move to step five in the ladder and focus on creating micro-outcomes on our website. Here is what it looks like for the Venetian hotel and casino in Macao:

macro micro outcomes venetian macao

In orange is the macro-outcome (number of casino room reservations), in purple are the micro-outcomes. All clustered into See-Think-Do. Less than two percent of people on your website will complete the macro-outcome (conversion). Having a robust cluster of micro-outcomes allows you to deliver something of value to the other 98% and establish a relationship with them (and get some economic value in exchange!). The smartest companies in the world are very good at this, step five. It does require working with your CMO, VPs, Directors, IT, Offline Sales, UX, IT, and more people than you could ever imagine. It is worth it.

Time to start kicking things up a notch in step six. Start investing in creating the world's most beautiful, functional, brand-enhancing, customer joy inducing website! You have content, you have traffic, you have micro-outcomes, you are making loads of money. Invest in the site experience now to differentiate yourself from the competition, and create irrational loyalty. Beat Bonobos (I. Love. Them!). Beat L'Oreal (except for their irritating 40 question survey in a single long window, they are nearly flawless). Beat Palms casino (try booking, try the menu, try anything, pretty awesome all around).

You are a big company and you can do two big things at one time. Now is also the right time to start investing in Facebook and YouTube. These two social platforms (eschew others at this point) allow you to learn how to earn attention in two different form factors. In both cases you'll learn quickly that pimping is the best way to fail. Expressed by me on behalf of all humans on earth: The world's greatest social media strategy: 1. Entertain Me 2. Inform Me. 3. Provide Utility. Nothing else works. Learn that in step six.

[Bonus: Facebook Marketing: Best Metrics, ROI, Business Value ]

Now that your earned, owned and paid media strategies are in full swing, and you are the proud owner of the world's greatest desktop and mobile website, let's focus on enhancing your ability to get a massive audience. (Cartoon by Hugh MacLeod)

long tail orgasm1

Step seven is to to build out an incredible category/industry/ecosystem targeting Search and Display strategy. This will result in you getting magnificent at brand marketing, at the See and Think stages. The result will be an even larger owned audience, less getting into dog-eat-dog Do stage fights. You'll have complete spectrum of coverage, being there from understanding customer intent at the earliest stages and converting that into demand for what you have to offer.

From step five on you were likely already delivering some multi-channel value for your company. Some of your micro-outcomes were likely already connected to your offline existence (maps, phone calls, offer redemptions, etc.). Now in step eight, we really kick things up multiple notches when it comes to creating a truly fantastic multi-channel (or the flavor of the month, omni-channel) execution engine.

multichannel marketing value analysis framework

The picture above is from my first book, Web Analytics: An Hour A Day, from page 235. It is a part of multi-channel analytics chapter.

There is a lot of difficult work to be done (systems, processes, integrations, optimizations) in order to ensure that your digital existence is driving nonline value. Now is the time to undertake that work. Not in step three. Definitely not in step one. Now. Step eight (after you've gotten the first seven things done).

The last step before nirvana, step nine, is to focus on getting better at loyalty marketing. (Cartoon by Tom Fishburne)

brand loyalty

My definition of loyalty marketing, from the Coddle-stage, is to create unique content and to execute targeted marketing for those people/business entities, who have purchased from you two times or more. I have a higher standard for who our customer is. Not the person/business entity who's purchased from us once (they might not have had a choice), but the entity that's purchased from us twice at least (because the second time they made a choice to do business with us). Have a completely separate and focused set of people and work to deliver joy and delight to these entities. It is the only recipe for long term sustainable success.

Now you know the nine steps to nirvana. And you know exactly the order in which you should consider prioritizing your efforts. If you do step five before two, you can. But your success will be much more limited.

Understand the choices that resulted in what you are supposed to do in each step, then customize this, using the choices above, to create your own step ladder to deliver amazing digital marketing success to your company.

The cool thing about the web is that you don't have to do all of the above based on faith, you have a BFF in data! Let's go there.

Digital Analytics: Ladder of Awesomeness/Sustainable Success.

If you open your copy of Google/Adobe Analytics or CoreMetrics or Webtrekk you'll notice that every single report has a gigantic number of metrics in it. And…. they have many reports!

So on day one, as soon as we get access to the digital analytics tool, we go all crazy. Not only do we puke out a lot of data to every breathing human up and down the chain of command, we treat every bit of data with equal importance. The first part is frustrating, the second part is deadly.

Regardless of if you are a B2B or B2C or A2Z company, regardless of if you are big or small, regardless of how great you think you are, I believe you can benefit from taking one step at a time when it comes to ensuring that data analysis drives business value. It might seem sacrilegious to suggest that you should worry about Visits first and not Profitability, but that is exactly what I'm going suggest because when we overshoot our capabilities, we fail to hit even our local maxima (forget about ever hitting the global maxima !).

My assumption is that everyone on this blog is smart enough to balance for focus and ensuring the company stays a viable entity as it climbs each step in the ladder of success. Hence none of you will mis-understand that recommending a focus on CPA in stage four means you run the company to the ground because you ignore business fundamentals!

[A tiny hidden agenda I have in this post is to share how to make hard choices. You can imagine how difficult it is to say focus on page depth, don't focus on conversion rate, or don't worry about any content metric, focus on clicks. It seems crazy. But a big part of being successful is being able to understand business reality and have the skill to make these hard choices. I hope you'll pick up a couple of tips about making those choices.]

Ready to read something outrageously controversial? ; )

digital analytics ladder of magnificient success

Focus on Visits and Click-thru Rates first. Don't do anything else. Nothing. Just Visits and CTRs. Focus your analysis on looking at dimensions that help you understand where your precious visitors are coming from, if you are doing any kind of inbound marketing (in the digital marketing ladder I recommend SEO in stage one) then what is getting more clicks and what is not. Optimize for Visits and CTRs will help you focus your precious energy on certain geographies, certain referring sources, certain keywords, certain digital activities and optimize to get higher clicks. A very good thing in stage one.

Now that people are showing up, we are ready to see what content they are consuming and how well/badly our welcome pages are doing. Focus on Bounce Rates ("I came, I puked, I left!") to help you optimize your landing pages and the sources driving traffic to those pages. Calls to action, text, graphics, offers, bids, ad text, targeting and more. Your job is to get in front of the right person, get them to the right page, and entice them to stay.

page depth analysis1

In stage two also focus on Pages per Visit, or Page Depth, (don't use time on site, it is problematic) as in the sample table above. This will help you optimize both for mobile and desktop experiences.

It is time to make some money in stage three. (See what I mean by making tough choices? Obsessing about making money first will cause your company to make the wrong choices initially. Just make sure you are not losing money, then obsess about it only in stage three.) For B2B companies Macro Outcome Rate is related to lead generation, for B2C it is often the e-commerce Conversion Rate. Additionally in stage three focus on Page Value, with it you are not only optimizing for content consumption (stage two) you are also optimizing for which content most creates revenue. Then zero in on that content and people/teams inside the company that create that content.

Your business is now humming on all three of the initial key things you need to do for acquisition, behavior and outcome. In stage four become an insane fanatic about extracting the highest possible value you can from every dollar you are spending on marketing and advertising. Focus on optimizing your Cost per Acquisition (CPA).

cost per acquisition 31

This will not only reduce cost, if you do it right, it will force your company to invest more in activities that improve shareholder value and kill the shiny objects that our management teams chase due to advice from "marketing gurus." This effort is so important that I want you to focus on it singularly (unlike all other stages).

Stage five, as in the case of our digital marketing ladder of success, calls for stepping up our level of sophistication. Focus on cart and checkout abandonment rate (don't combine the two). Go buy a simple A/B testing tool (Visual Website Optimizer, Optimizely), go crazy optimizing every little thing to take money from the people who want to give it to you! It is also time to become more sophisticated about identifying the value of your marketing spend, focus on the Assisted Conversions metric (you'll find it in the Multi-Channel Funnels report). Make decisions based on last click conversions delivered AND the assisted conversions. Don't worry about attribution modeling yet. Just focus on the last column in that report, then optimize your campaign targeting, content and success measures.

We've nailed down what we are doing on our owned platforms, time to focus on our rented platforms. You are working very hard by this stage on Facebook, YouTube etc, stay away from awful metrics like Views, Likes, etc. So, in stage six, obsess about Conversation Rate and Amplification, two of my four best social media metrics ever.

dashboard best social media metrics1

The above metrics will force your company to use social for what social is really good at. Force them to execute my recommendation for greatest social media strategy: 1. Entertain Me 2. Inform Me. 3. Provide Utility.

Stage seven where you start to focus on the metric that differentiates losers from winners: Economic Value. We focus on all 100% of our visitors (not just the one or two percent that will convert), we will focus on all of the See-Think-Do-Coddle audience consideration stages. The surest way to do that is if we identify the micro-outcomes and the economic value each outcome adds to our business. This is so amazing because it will force your company to focus on what makes money now, what will make money 90 days from now and 9 months from now!

None of the above was really hard. Stage eight is hard! We are going to obsess about Profitability. Not just the fake "ROI" number in many digital analytics tool, but true profitability. At the very minimum, for a dimension you care about like campaign… Profitability = Revenue generated – campaign cost – cost of goods sold. You can add other costs if you have access to them.

Profitability is one of the main reasons I'm so excited about cost data upload into Google Analytics. Now you can measure what the actual amount of money each campaign/activity delivers to your business. You can do it for Bing, email, AOL ads, social, even SEO! You can finally see that the Conversion rate for Yahoo! ads is 10%, the Average Order Value is $200, compare it to Google ads conversion rate of 4% and Average Order Value of $100, and notice that the Profit per Order from Yahoo! is -$15 and for Google it is $163. #omg

Stage eight also includes improving the sophistication of analyzing the offline impact of our online activities. Multi-channel measurement and optimization. It is a long hard slog, but by the time you get to stage eight, you are ready, your company is ready, you are going to get so rich!

The last stage, stage nine, is also the most strategic and deadly awesome: Optimizing for customer lifetime value.

life time value lifetime net profit 11

Asking you to wait until stage nine for LTV is like saying don't believe in Jesus until time x. It seems silly. It seems insane. The sad reality is that it takes a lot (from a data, people, process perspective) to be ready to optimize for LTV. But by this stage you've put all your ducks in the proper order, you've done your multi-channel optimization (and more critically data integrations required between your online and offline sources), you have moved away from considering cookies to be customers to changing your entire Google Analytics existence to focus on people (across devices, channels, online and offline). Now you are ready for LTV. And you are going to do it without frustration and with a huge fast impact on your business. [For more guidance see the LTV post and download the lifetime value model.]

Bish. Bam. Boom! You are there. You've achieved nirvana! : )

Closing Thoughts.

It is hard to have the discipline to systematically get good at one thing at a time. But evolution works spectacularly well. That is what we need.

It seems crazy that you are a large company with tons of people and money. Gosh, you have 25 people just in your digital analytics team and a two million dollar a year adobe analytics contract. Still, for all those people prioritize one stage at a time (while other things can happen, they just won't be a corporate priority), and move your company forward one stage at a time.

It is hard to get nine women to make a baby in one month.

I wish you all the best in climbing the digital ladder of amazing success.

As always, it is your turn now.

Do you agree with the step-by-step approach? Would you change any stage in the digital marketing ladder? Perhaps do Email before SEO, or Social as stage one? How about the analytics ladder? Would you make different choices in the order of the metrics? Is there a metric I'm over-valuing or completely missing from the ladder? If you've been successful getting your company to be good at many things all at one time, what's your secret?

Please share your perspectives, critique, life lessons, and insights via comments below.

Thank you.

Digital Marketing And Analytics: Two Ladders For Magnificent Success is a post from: Occam's Razor by Avinash Kaushik

The Weekly Compete Pulse

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Weekly Pulse

Here’s a round up of our favorite digital marketing stories from the web this week:

10 Google Analytics Advanced Segments That Reveal Search & Social ROI Anyone who has used Google Analytics knows that getting actionable insights from your data isn’t always the easiest task. That is why the more savvy of Google Analytics users know that the real key in getting what you want from your data is in the use of advanced segments. Unfortunately, those new to advanced segments may not know where to start. That is why the people over at Search Engine Watch put together this excellent list of advanced segments to help you get insights into your social data.

How & When You Can Turn SEM From A Checkbox To A Core Business Component As search engine marketing (SEM) becomes an invaluable component of many digital marketing budgets, companies who are engaging in it just to “check it off” on their to do digital marketing portfolio aren’t getting the full value out of it competing companies that are treating it as a core component are. In this post from Search Engine Land, the author describes the difference between the two types of companies and how you can become the latter.

How To Get Interactive Branding Right As experiences like New Coke have shown, branding exercises can easily spiral into unmitigated disasters. Hard enough to take if you’re a globe-striding corporation; but if you’re a small unit just starting out it can be a disaster. However, there is one type of ‘business’ that nearly always seems to excel at branding: non-profits. See how non-profits are succeeding at interactive branding and how you can apply their successful strategies to your business.

The Most Effective Tactics for Acquiring Facebook Fans and Twitter Followers Digital marketers do not believe that the most commonly used tactics for acquiring Facebook fans and Twitter followers are very effective in delivering quality community and audience members, according to a recent report from ExactTarget. See what marketers think are the most common strategies and what they think are the most effective.

What was your favorite digital marketing story this week? We’d love for you to share links in the comments!

Adding Digital Marketing Magic to a Creative Paper Cup Company

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In 2012 we introduced you to the Digital Marketing Makeover . A bid by us and a team of experienced Bing Ads Accredited Professionals to help small businesses thrive in economical challenging times by offering digital marketing advice. So far we’ve helped very creative chef from Cheshire , a Scottish entrepreneur and a catering business . Today we’re casting an analytical and creative eye on a manufacturing business – The Paper Cup Company .
As you expect from a business that…(read more)

Providing “Not Provided” – How You Can Still See Search Referral Data

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Not Provided

You’ve seen the headlines. Google is rolling out secure search for everyone. Marketers shouldn’t fear this change though; this is just another step towards progress in the ever-changing world of search. Instead of burying ourselves in organic keyword lists, we must start taking a more holistic approach to search marketing and begin taking steps towards seamlessly combining paid and organic search data. With developing products and concepts like Google Now and One Microsoft, the future of search is thrilling. Content strategies and social marketing must complement and integrate with every aspect of search; this is only the beginning of the next chapter of search in which keywords are only a small part of the puzzle.

Two years ago Google started encrypting their data by defaulting any search by a user signed into Google to Secure Sockets Layer, more commonly known as SSL. Expecting to lose around 10% of search referral data, some digital marketers were upset but accepting and understanding. After all, they could still get a general idea of how users were getting to their site and if a user is signed into Google then encrypting via SSL makes sense for privacy reasons. Releasing a statement on their blog, it was hard to argue with the logic:

“As search becomes an increasingly customized experience, we recognize the growing importance of protecting the personalized search results we deliver. As a result, we’re enhancing our default search experience for signed-in users.”

After Google made the change, a precedent was set and less than a year after Google made the first change, Firefox released a version of their browser that defaulted to Google’s secure search. A few months after that, Safari in iOS 6 began using Google’s secure search. And a few months after that, the latest release of Chrome began encrypting all searches submitted via its omnibox. All of these changes contributed to the steadily increasing percentage of search referral data that was being shown as “not provided.”

Not Provided

With privacy becoming increasingly important, it should be no surprise that this move was made. Not only is a niche being carved out for privacy-focused products, Google has always placed a high emphasis on improving the security of their searches. Their awareness of this rising consumer value is evidenced by the statement they released in the wake of the change:

“We added SSL encryption for our signed-in search users in 2011, as well as searches from the Chrome omnibox earlier this year. We’re now working to bring this extra protection to more users who are not signed in.”

Fortunately, there are still ways for you to understand search referral data. By using carefully orchestrated Google AdWords campaigns in concert with Compete PRO, you will have access to both organic and paid search referrals. In a search environment that will soon be dominated by encrypted search, not only will this put you ahead of the competition, but it will continually offer you insights into how customers are getting to your site and what you should focus your efforts on optimizing.

How can you still see your organic search referral data with 100% “Not Provided”

With Compete PRO, not only can you see the search volume that a certain search term brings to your site, you can see other search-related data as well:

  • Keyword & Referral Share: Obviously the most important and the most valuable, the actual search queries (and the share of the total search referral visits that each query makes up) that are bringing visitors to your site.
  • Paid & Natural Share: For each search term, you can see how much of the traffic is natural and how much is paid. If you are bidding on the terms then you probably already have a good idea of these numbers already. However, this data can prove to be invaluable when looking at your competitors.
  • Time Index: Along with search referral share and paid/natural share, we also offer two different time indexes for each search term. The first, Average Time Index, is an engagement metric found in Site and Category Search Referral Reports. This metric is indexed to 100, with 100 representing the keyword term that resulted in the most average time per visit being spent on the site. The other metric, Total Time Index, is also indexed to 100, with 100 representing the keyword term that resulted in the most total time spent on the site.
  • Search Insights: Compete PRO also offers seven different search insights which are preset filter configurations based on common data use cases for Search marketing. They call out valuable insights in the data by automatically setting the filters to predefined ranges, reducing the noise in large data sets. You can see the following search insights within Compete PRO: Highly engaging keywords, high traffic keywords, paid keywords, natural keywords, engaging long tail keywords, enthusiast keywords, and long tail keywords.

Not only are all of these data sets crucial to have for your own site, using Compete PRO also allows you to gather data from your competitors’ sites as well. This information was valuable before, but now that the day “Not Provided” makes up 100% of your competitors’ search referral data is right around the corner, and the only way to see it is through Compete PRO, it is invaluable. Not convinced? Try out a free trial of Compete PRO today or contact us if you have any questions.

If you want more advanced keyword analysis features, check out Ascend, which provides marketers with visibility into crucial data on the search engine results page (SERP) to help reduce overall spend, pinpoint and mitigate competitive exposure, optimize share of voice, and align search with the shoppers path-to-purchase.

November 5th 2013 Google, Search, Search Engine Marketing, sem, SEO

Search: Not Provided: What Remains, Keyword Data Options, the Future

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patterns 25In late 2011, Google announced an effort to make search behavior more secure. Logged-in users were switched to using httpS from http. This encrypted their search queries from any prying eyes, and kept from being passed on to websites the users visits after seeing search results.

This led to the problem we, Marketers, SEOs, Analysts, fondly refer to as not provided .

Following revelations of NSA activities via Mr. Snowden, Google has now switched almost all users to secure search, resulting in even more user search queries showing up as not provided in all web analytics tools.

Yahoo! has recently announced switching to httpS as standard for all mail users, indicating secure search might follow next. That of course will mean more referring keyword data will disappear.

At the moment it is not clear whether Bing, Baidu, Yandex and others will move to similarly protect users’ search privacy; if and when they do, the result will be loss of even more keyword-level user behavior data.

Initially, I was a little conflicted about the whole not provided affair.

As an analyst, I was upset that this change would hurt my ability to analyze the effectiveness of my beloved search engine optimization (SEO) efforts – which are really all about finding the right users using optimal content strategies.

But it is difficult to not look at the wider picture. Repressive (and some not-overtly repressive) regimes around the world aggressively monitor user search behavior (and more). This can place many of our peer citizens in grave danger. As a citizen of the world, I was happy that Google and Yahoo! want to protect user privacy.

I'm a lot less conflicted now. I've gone through the five stages in the Kubler-Ross model. Besides, I've also come to realize that there is a lot I can still do!

In this post I want to share four angles on secure search:

1. Implications of Secure Search Decision.

2. What Is Not Going Away. #silverlinings

3. Alternatives For Keyword Data Analysis.

4. Possible Future Solutions.

While not provided is not an optimal scenario, you'll see that things are not as bad as initial impressions might indicate, yes there are new challenges, but we also have some alternative solutions, and realize that the SEO industry is not done innovating. Ready?

1. Implications of Secure Search Decision.

No keyword data in analytics tools.

We are headed towards having zero referring keywords from Google and, perhaps, other search engines.

not provided trend analytics5

This impacts all digital analytics tools, regardless of what company and whether they use javascript or log files or magic beans to collect data.

Depending on the mobile device and browser you are using (for example, Safari since iOS 6), you have already been using secure search for a while regardless of the search engine you use. So that data has been missing for some time.

There are a number of "hacks" out there with promises of getting close enough keyword data, or for marrying not provided with some of the remaining data and landing pages. These are well meaning, but almost always yield zero value or worse drive you in a sub-optimal direction. Please been careful if you choose to use them.

No keyword data in competitive intelligence/SEO tools.

Perhaps you (like me) use competitive intelligence or SEO tools to monitor keyword performance. For example, for L'Oreal:

competitive intel kw report23

Secure Search will also impact data in these tools. It will be increasingly distorted because it will reflect only traffic from the small audience of visitors who are not yet using secure search or are using other non-secure search engines or only the type of people who allow their behavior to be 100% monitored – including SSL/httpS. Sample and sampling bias.

You can read this post to learn how these tools collect data: The Definitive Guide To (8) Competitive Intelligence Data Sources.

I really loved having this data. It was such a great way to see what competitors were doing or where I was beating them on paid or organic or brand or category terms. Sadly, it does not matter which tool you use. These tools will only show you a more distorted view of reality. Please be very careful about what you do with keyword data from these tools (though they provide a lot of other data, all of which was of the same quality as in the past).

These changes impact my AdWords spend sub-optimally. A lot of the keywords I used to add to my campaigns came from the long, long tail I saw in my organic search data (I would take the best performers there and use PPC to get more traffic) and from competitive intelligence research. With both of these sources gone, my AdWords spend may take a dive because I can't find these surprising keywords — even using the tools you'll see me mention below! How is this in Google's interest?

No keyword-level conversion analysis.

We have a lot of wonderful detailed data at a keyword level when we log into SiteCatalyst or WebTrends or Google Analytics. Bounce Rates, % New Visits, Visit Duration, Goal Conversions, Average Order Value.

All this data will no longer be available for organic search keywords.

As hinted above, our ability to understand the long tail — often as much as 80% of search traffic — will be curtailed. We can guess our brand terms and product keywords, but the wonderful harvest of category-type, and beyond, keywords is gone.

Current keyword data is only temporarily helpful.

Remember: On a daily basis 15% of the queries on Google have never been seen before by the search engine. Daily! For all 15 years of Google's existence!

That is one reason the data we have for the last year or so, even as not provided ramped up, might only be temporarily helpful in our analysis.

Another important reason historical data becomes stale pretty quickly is that any nominally functioning business will have new products, new content, new business priorities, and all that impacts your search strategy.

Finally, with every change in the search engine interface the way people use search changes. This in turn mandates new SEO (and PPC) strategies, if we don't want to fail.

So, use the data you have today for a little while to guesstimate your SEO performance or optimize your website. But know that the view you have will become stale and provide a distorted view of reality pretty soon.

2. What Is Not Going Away. #silverlinings

While we are losing our ability to do detailed keyword analysis, we are retaining our ability to do strategic analysis. Search engine optimization continues to be important, and can still get a macro understanding of performance and identify potentially valuable keywords.

Aggregated search engine level analysis.

The Multi-Channel Funnels folder in Google Analytics contains the Top Conversion Paths report. At the highest level, across visits by focusing on unique people, the report shows the role search plays in driving conversions.

You can see how frequently it is the starting point for a later conversion, you can see how frequently it is in the middle, and you can see how frequently it is the last click.

multi channel funnels top paths report1

I like starting with this report because it allows us to have a smarter beyond-the-last-click discussion and answer these questions: What is the complete role of Search in the conversion process? How does paid search interplay with organic search?

From there, jump to my personal favorite report in MCF, Assisted Conversions.

We can now look at organic and paid search differently, and we are able to see the complete value of both. We can see how often search is the last click prior to conversions, and how often it assists with other conversions.

multi channel funnels channel grouping1

The reason I love the above view is that for each channel, I'm able to present our management team a simple, yet powerful, understanding of the contribution of our marketing channels – including search.

Selfishly, now we can show the complete value, in dollars and cents, we deliver via SEO.

[Bonus: For more on next steps and attribution modeling please see: Multi-Channel Attribution Modeling: The Good, Bad and Ugly Models.]

If you are interested in only the last-click view of activities (please don't be interested in this!), you can of course look at your normal Channels or All Traffic reports in Google Analytics.

This is a simple custom report I use to look at the aggregated view:

organic paid search split1

As the report above demonstrates, you can still report on your other metrics, like Unique Visitors, Bounce Rates, Per Visit Value and many others, at an aggregated level. You can see how Google is doing, and you can see how Google Paid and Organic are doing.

So from the perspective of reporting organic search performance to senior management, you are all set. Where we are out of luck is taking things down from here to the keyword level. Yes, there will still be some data in the keyword report, but since not provided is an unknown unknown, you have no idea what that segment represents.

Organic landing pages report.

Search engine optimization is all about pages and the content in those pages.

You can use a custom landing pages report (click that link to download) and apply your organic search segment to that report to get a view that looks like this:

organic search landing pages1

The top landing pages getting traffic from organic search. And of course our Acquisition, Behavior, Outcome metrics.

See Page Value there? Now you also know how much value is delivered when each of these pages is viewed by someone who came from organic search.

So let's say you spent the last few weeks optimizing pages #2, #3 and #5; well, now you can be sad that they are delivering the lowest page value from organic search. Feel sad.

Or, just tell your boss/client: "No, no, no, you misunderstood. I was optimizing page #4!" : )

The custom landing pages report also includes the ability drill down to keyword level, just click on the page you are interested in and you'll see this:

organic search landing pages keywords1

With every passing day this drilldown will become more and more useless. But for now, it is there if you want to see it.

Let me repeat a point. I've noticed some of our peer SEOs making strong recommendations to take action based on the keywords you are able to see beyond not provided. I'm afraid that is a career-limiting move. You have no idea what these words represent – head, mid, tail, something else – or what is in the blank not provided bucket. Be very careful.

Paid search keyword analysis report.

We all of course still have access to keyword level analysis for our paid search spend.

paid search analysis google analytics1

There is one really interesting bit in the paid search reports that you can use for SEO purposes.

When you submit your keywords and bids, the search engine will match them against user search queries. In Google Analytics you have Keyword, in your AdWords report, as above, but if you create a custom report you can drill down from Keyword to Matched Search Query. The latter is what people actually type. So for "chrome notebook," above, if I look at the Matched Search Query I can see all 25 variations the users typed. This is very useful for SEO.

You can download my custom report, it is #2 in this post: Paid Search/AdWords Custom Reports

Beyond this, be judicious about what inferences you draw from your paid search performance. Some distinguished SEO experts have advocated that you should use the distribution of visits/conversions/profits of your AdWords keywords and use that to make decisions about effectiveness of your SEO efforts. Others are advising you to bid on AdWords and guesstimate various things about SEO performance. Sadly these are also career-limiting moves.


When you look at your AdWords data, you have no idea which of these four scenarios is true for your business:

four paid organic search scenarios1

And if you don't know which is true — and you really won't with not provided in your way — is it prudent to use your AdWords performance to judge SEO? I would humbly suggest not.

If you want to stress test this,…. go back to your 2011 (pre-not provided) data for paid and organic and see what you can find. And remember since then Google has made sixteen trillion changes to how both paid and organic search work, and your business has at least made 25.

Don't assume that your SEO strategy should reflect the prioritizations implied by your AdWords keyword data. The reason SEO worked so well is that you would get traffic you might not have known/guessed/realized you wanted/deserved.

3. Alternatives For Keyword Data Analysis.

With not provided eliminating almost all of our keyword data, initially for some search engines/browsers and likely soon from all, we face challenges in understanding performance. Luckily we can avail ourselves of a couple of alternative, if imperfect/incomplete, options.

Webmaster Tools.

Here are the challenges Google's Webmaster Tools solves: Which search queries does my website show up for, and what does my click-through rate look like?

I know this might sound depressing, but this is the only place you'll see any SEO performance data at a keyword level. Look at the CTR column. If you do lots of good SEO — you work on the page title, url, page excerpt, author image and all that wonderful stuff — this is where you can see whether that work is getting you more clicks. You work harder on SEO, you raise your rankings (remember don't focus on overall page rank, it is quite value-deficient), you'll see higher CTRs.

google webmaster tools 1

You will see approximately 2,000 search queries. These are not all the search queries for which your site shows up. (More on this in the bonus section below.)

There are a couple of important things to remember when you use this data.

If you go back in history and do comparative analysis for last year's data when not provided was low, you'll notice that your top 100 keywords in Google Analytics or Site Catalyst are not quite the same as those in WebMaster Tools. They use two completely different sources of data and data processing.

Be aware that even if you sort by Clicks (and always sort by clicks), the order in which these queries appear is not a true indication of their importance (in GA when I could see it, I would see a different top 25 as an example). The numbers are also soft or directional. For example, even with 90% not provided Google Analytics told me I had 500 visits from "avinash kaushik" and not 150 clicks as shown above.

Despite these two caveats, Webmaster Tools should be a key part of your SEO performance analysis.

It is my hope that if this is how search engines are comfortable sharing keyword level data, that over time they will invest resources in this tool to increase the number of keywords and improve the data processing algorithms

Our good friends at Microsoft also provide Bing Webmaster Tools, and don't forget the excellent Yandex Webmaster Tools. Take keyword performance data from anyone who'll give it to you reliably.

1. Google's Webmaster Tools only stores your data for 90 days. If you would like to have this data for a longer time period, you can download it as a csv. Another alternative is to download it automatically using Python. Please see this post for instructions: Automatically download webmaster tools search queries data

2. GWT only shows you data for approximately 2,000 queries which returned your site in search results. Hence it only displays a sub-set of your query behavior data. The impact of this is in the top part of the table above, Impressions and Clicks. During this time period my site received 1,800k Impressions in search results, but GWT is only showing data for 140k of those impressions because it is only displaying 2,574 user queries. Ditto for Clicks. If I download all the data for the 2k queries shown in GWT, that will show behavior for just 8,000 of the 50,000 clicks my site received from Google in this time period. Data for 42,000 clicks is not shown because those queries are beyond the 2k limit in GWT.

Update: 3. In his comment below Jeff Smith shares a tip on how to structure your GWT account to possibly expanding the dataset to get more information. Please check it out.

Update: 4. Another great tip. Kartik's comment highlights that you can link your GWT account with your AdWords account and get paid and organic click data for the same keyword right inside AdWords. Click to read a how-to guide and available metrics.

Google Keyword Planner.

The challenge Google Keyword Planner solves: What keywords (user search queries) should my search engine optimization program focus on?

In the Keyword Planner you have several options to identify the most recent keywords — the most relevant keywords — to your website. The simplest way to start is to look for keyword recommendations for a specific keyword.

I choose the "search for new keyword and ad group ideas" section and in the landing page part type in the URL I'm interested in. Just as an example, I’m using the Macy's women's activewear page:

adwords keyword planner1

A quick click of the Get Ideas button gives us … the ideas!

I can choose to look at the Ad Group ideas or the Keyword Ideas.

keyword planner activewear

There are several specific applications for this delightful data.

First, it tells me the keywords for which I should be optimizing this specific page. I can go and look at the words I'm focused on, see if I have all the ones recommended by the Keyword Planner, and if not, I can include them for the next round of search engine optimization efforts.

Second, I have some rough sense for how important each word is, as judged by Avg. Monthly Searches. The volume can help me prioritize which keywords to focus on first.

Third, if this is my website (and Macy's is not!), I can also see my Ad Impression Share. Knowing how often my ad shows up for each keyword helps me prioritize my search engine optimization efforts.

It would be difficult to do this analysis for all your website pages. I recommend the top 100 landing pages (check that the 100 include your top product pages and your top brand landing pages — if not, add them to the list).

With the advent of not provided we lost our ability to know which keywords we should focus on for which page; the Google Keyword Planner helps solve that problem to an extent.

You don't have to do your analysis just by landing pages. If you would like, you can have the tool give you data for specific keywords you are interested in. Beyond landing pages, my other favorite option is to use the Product Category to get data for a whole area of my business.

For example, suppose I'm assisting a non-profit hospital with its analytics and optimization efforts. I'll just drill down to the Health category, then the Health Care Service sub-category and finally the Hospitals & Health Clinics sub-sub-category:

product category keyword searches1

Press Get Ideas button and — boom! — I have my keywords. In this case, I've further refined the list to only focus on a particular part of the US:


product category keyword searches details1

I have the keyword list I need to focus my search engine optimization efforts. Not based on what the Hospital CEO wants or what a random page analysis or your mom suggested, but rather based on what users in our geographic area are actually typing into a search engine!

A quick note of caution: As you play with the Keyword Planner, you'll bump into a graph like this one for your selected keyword or ad group ideas. It shows Google's estimate of how many possible clicks you could get at a particular cost per click.

keyword tool clicks1

Other than giving you some sense for traffic, this is not a relevant graph. I include it here just to show you that it is out there and I don't want you to read too much into it.

Google Trends.

The challenge Google Trends tool solves: What related and fastest-rising keywords should I focus on for my SEO program?

Webmaster tools focuses us on clicks and the Keyword Planner helps us with keywords to target by landing pages. Google Trends is valuable because it helps expand our keyword portfolio (top searches) and the keywords under which we should be lighting a fire (rising searches).

Here's an example. I'm running the SEO program for Liberty Mutual, Geico, AAA or State Farm. My most important query is car insurance (surprise!). I can create a report in Google Trends for the query "car insurance" and look at the past 12 months of data for the United States.

The results are really valuable:

google trends car insurance1

I can see which brand shows up at the top (sadly it’s not me, it’s Progressive), I can see the queries people are typing, and I can see the fastest-rising queries and realize I should worry about Safeco and Arbella. I can also see that Liberty Mutual's massive TV blitz is having an impact in increasing brand awareness and Geico seems to be having support problems with so many people looking for its phone number.

I can click on the gear icon at the top right and download a bunch more data, beyond the top ten. I can also focus on different countries, or just certain US states, or filter for the last 90 days.

I can also focus on different countries, or just some of the states in the US or only for the last 90 days. The options are endless.

There are two specific uses for this data.

First, I get the top and rising queries to consider for my SEO program. Not just queries either, but deeper insights like brand awareness, etc.

Second, I can use this to figure out the priorities for the content I need to create on my website to take advantage of evolving consumer interests and preferences.

If you have an ability to react quickly (not real-time, just quickly) the Google Trends tool can be a boon to your SEO efforts.

Competitive Intelligence / SEO Tools.

Competitive intelligence tools solve the challenge of knowing: What are my competitors up to? What is happening in my product/industry category when it comes to search?

SEO tools solve the challenge of knowing: What can I do to improve my page ranks, inbound links, content focus, social x, link text y, etc.?

There are many good competitive intelligence tools out there. They will continue to be useful for other analysis (referring domains, top pages, display ads, overall traffic etc.), but as I mentioned at the top of this post, the search keyword level data will attain a even lower quality. Here's a report I ran for L'Oreal:

competitive intel kw report1

If you see any keyword level data in these tools, you should assume that you are getting a distorted view of reality. Remember, all other data in these tools is fine. Just not any of the keyword level data.

There are many good SEO tools out there that provide a wide set of reports and data. As in the case of the CI tools, many other reports in these SEO tools will remain valuable but not the keyword level reports. As not provided moves toward 100% due to search switching to https, they will also lose their ability to monitor referring keywords (along with aforementioned repressive and sometimes not-so-overtly repressive regimes).

When the keywords are missing, the SEO tools will have to figure out if the recommendations they are making about "how to rank better with Bing/Google/Yahoo!" or "do a, b, c and you will get more keyword traffic" are still valid. At a search engine level they will remain valid, but at a keyword level they might become invalid very soon (if they’re not already)

Even at a search engine level, causality (in other words, “do x and y money will come to you”) will become tenuous and the tools might switch to correlations. That is hard and poses a whole new set of challenges.

Some of the analysis these tools start to provide might take on the spirit of: "We don't know whether factors m, n, and q that we are analyzing/recommending, or all this link analysis and link text and brand mentions and keyword density, specifically impact your search engine optimization/ranking at a keyword level, or if our recommendations move revenue, but we believe they do and so you should do them."

There is nothing earth-shatteringly wrong about it. It introduces a fudge factor, a risky variable. I just want you to be aware of it. And if you want to feel better about this, just think of how you make decisions about offline media – that is entirely based on faith!

Just be aware of the implications outlined above, and use the tools/recommendations wisely.

big bets

4. Possible Future Solutions.

Let's try to end on a hopeful note. Keyword data is almost all gone, what else could take its place in helping us understand the impact of our search engine optimization efforts? Just because the search engines are taking keywords away does not mean SEO is dead! If anything, it is even more important.

Here are a couple of ideas that come to my mind as future solutions/approaches. (Please add yours via comments below.)

Page "personality" analysis.

At the end of the day, what are we trying to do with SEO? We are simply trying to ensure that the content we have is crawled properly by search engines and that during that process the engines understand what our content stands for. We want the engines to understand our products, services, ideas, etc. and know that we are the perfect answer for a particular query.

I wonder if someone can create a tool that will crawl our site and tell us what the personality of each page represents. Some of this is manifested today as keyword density analysis (which is value-deficient, especially because search engines got over "density" nine hundred years ago). By personality, I mean what does the page stand for, what is the adjacent cluster of meaning that is around the page's purpose? Based on the words used, what attitude does the page reflect, and based on how others are talking about this page, what other meaning is being implied on a page?

If the Linguistic Inquiry and Word Count (LIWC) can analyze my email and tell me the 32 dimensions of my personality, why can't someone do that for my site’s pages beyond a dumb keyword density analysis?

If I knew the personality of the page, I could optimize for that and then the rest is up to the search engine.

Crazy idea? Or crazy like a fox idea? : )

Non-individualized (not tied to visits/cookies/people) keyword performance data.

A lot of the concern related to privacy is valid, and even urgent when these search queries are tied to a person. The implications can be grim in many parts of the world.

But, I wonder if Yahoo!/Bing/Google/Yandex would be open to creating a solution that delivers non-individualized keyword level performance data.

I would not know that you, let's say Kim, came to my website on the keyword "avinash rocks so much it is pretty darn awesome" and you, Kim, converted delivering an order of $45. But the engines could tell us that the keyword "avinash rocks so much it is pretty darn awesome" delivered 100 visits of which 2% converted and delivered $xx,xxx revenue.

Think of it as turbo-charged webmaster tools – take what it has today and connect it to a conversion tracking tag. This protects user privacy, but gives me (and you) a better glimpse of performance and hence better focus for our organic search optimization efforts.

Maybe the search engines can just give us all keywords searched more than 100 times (to protect privacy even more). Still non-individualized.

I don't know the chances of this happening, but I wanted to propose a solution.

Controlled experimentation.

Why not give up on the tools/data and learn from our brothers and sisters in TV/Print/Billboards land and use sophisticated controlled experiments to prove the value of our SEO efforts?

(Remember: Using the alternative data sources covered above, you already know which keywords to focus your efforts on.)

In the world of TV/Radio/Print we barely have any data – and what we do have is questionable – hence the smartest in the industry are using media mix modeling to determine the value delivered by an ad.

We can do the same now for our search optimization efforts.

First, we follow all the basic SEO best practices. Make sure our sites are crawlable (no javascript wrapped links, pop-ups with crazy code, Flash heavy gates, page tabs using magic to show up, etc.), the content is understandable (titles in images, unclear product names, crazy stuff), and you are super fantastically sure about what you are doing when you make every page dynamic and "personalized customized super-relevant" to each visitor. Now it does not matter what ranking algorithm the search engine is using, it understands you.

Now its time for the SEO Consultant's awesomely awesome SEO strategy implementation.

Try not to go whole hog. Pick a part of the site to unleash the awesomely awesome SEO strategy. One product line. One entire directory or content. A section of solutions. A cleanly isolatable cluster of pages/products/services/solutions/things.

Implement. Measure the impact (remember you can measure at a Search Engine and Organic/Paid level). If it’s a winner, roll the strategy out to other pages. If not, the SEO God you hired might only be a seo god.

At some level, exactly as in the case of TV/Radio/Print, this is deeply dissatisfying because it takes time, it requires your team to step up their analytical skills and often you only understand what is happening and not why. But, it is is something.

I genuinely believe the smartest SEOs out there will go back to school and massively upgrade their experimentation and media mix modeling skills. A path to more money via enriching skills and reducing reliance on having perfect data.

There is no doubt that secure search, and the delightful result not provided, creates a tough challenge for all Marketers and Analysts. But it is here, and I believe here to stay.

My effort in this post has been to show that things are not as dire as you might have imagined (see the not going away and alternatives sections). We can fill some gaps, we can still bring focus to our strategy. I'm also cautiously optimistic that there will be future solutions that we have not yet imagined that will address the void of keyword level performance analysis. And I know for a fact that many of us will embrace controlled experimentation and thereby rock more and charge more for our services or get promoted.

Carpe diem!

As always, it is your turn now.

I'm sure you have thoughts/questions on why not provided happened. You might not have made it through all the five stages Kubler-Ross model yet. That is OK, I respect your questions and your place in the model. Sadly I'm not in a position to answer your questions about that specifically. So, to the meat of the post …

Is there an implication of not having keyword level data that I missed covering? From the data we do have access to, search engine level, is there a particular type of analysis that is proving to be insightful? Are there other alternative data sources you have found to be of value? If you were the queen of the world and could create a future solution, what would it do?

Please share your feedback, incredible ideas, practical solutions and OMG you totally forgot that thing thoughts via comments.

Thank you.

PS: Here's my post on how to analyze keyword performance in a world where only a part of the data was in not provided bucket: Smarter Data Analysis of Google's https (not provided) change: 5 Steps. For all the reasons outlined in the above post this smarter data analysis option might not work any more. But if only a small part of your data, for any reason, is not provided, please check out the link.

Search: Not Provided: What Remains, Keyword Data Options, the Future is a post from: Occam's Razor by Avinash Kaushik

Paid Search And Marketing Grow Further & Further Apart

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A few months back, I wrote an article for Marketing Land called “Is The Art Of Paid Search Marketing Dead?” in which I foolishly suggested there was still a small bit of art left in search marketing. Art? Are you kidding me? Ugh. I haven’t been so wrong or felt so foolish in a long […]

Please visit Search Engine Land for the full article.

October 7th 2013 Search Engine Marketing