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Five Strategies for Slaying the Data Puking Dragon.


If you bring sharp focus, you increase chances of attention being diverted to the right places. That in turn will drive smarter questions, which will elicit thoughtful answers from available data. The result will be data-influenced actions that result in a long-term strategic advantage.

It all starts with sharp focus.

Consider these three scenarios…

Your boss is waiting for you to present results on quarterly marketing performance, and you have 75 dense slides. In your heart you know this is crazy; she won’t understand a fraction of it. What do you do?

Your recent audit of the output of your analytics organization found that 160 analytics reports are delivered every month. You know this is way too many, way too often. How do you cull?

Your digital performance dashboard has 16 metrics along 9 dimensions, and you know that the font-size 6 text and sparkline sized charts make them incomprehensible. What’s the way forward?

If you find yourself in any of these scenarios, and your inner analysis ninja feels more like a reporting squirrel, it is ok. The first step is realizing that data is being used only to resolve the fear that not enough data is available. It’s not being selected strategically for the most meaningful and actionable insights.

As you accumulate more experience in your career, you’ll discover there are a cluster of simple strategies you can follow to pretty ruthlessly eliminate the riffraff and focus on the critical view. Here are are five that I tend to use a lot, they are easy to internalize, take sustained passion to execute, but always yield delightful results…

1. Focus only on KPIs, eliminate metrics.

Here are the definitions you’ll find in my books:

Metric: A metric is a number.

KPI: A key performance indicator (KPI) is a metric most closely tied to overall business success.

Time on Page is a metric. As is Impressions. So are Followers and Footsteps, Reach and Awareness, and Clicks and Gross Ratings Points.

Each hits the bar of being “interesting,” in a tactical oh that’s what’s happening in that silo soft of way. None, passes the simple closely tied to overall business success standard. In fact, hold on to your hats, a movement up or down 25% in any of those metrics may or may not have any impact on your core business outcomes.

Profit is obviously a KPI, as is Likelihood to Recommend. So too are Installs and Monthly Active Users, Orders and Loyalty, Assisted Conversions and Call Center Revenue.

Each KPI is of value in a strategic oh so that is why we are not making money or oh so that is why we had a fabulous quarter sort of way. A 25% movement in any of those KPIs could be the difference between everyone up and down getting a bonus or a part of the company facing layoffs. Often, even a 5% movement might be immensely material. What metric can say that?

When you find yourself experiencing data overload, don an assassin’s garb, identify the metrics and kill them. They are not tied to business success, and no senior leader will miss them. On the ground, people will use metrics as micro diagnostic instruments, but they already do that.

A sharp focus on KPIs requires concentrating on what matters most. Every business will have approximately six KPIs for a CEO. Those six will tie to another six supplied to the CMO.

After you go through the assassin’s garb process above, if it turns out that you have 28 KPIs… You need help. Hire a super-smart consultant immediately!

2. Focus only on KPIs that have pre-assigned targets.

This is a clever strategy, I think you are going to love it.

Targets are numerical values you have pre-determined as indicators success or failure.

Turns out, creating targets is insanely hard.

You have to be great at forecasting, competitive intelligence, investment planning, understanding past performance, organization changes and magic pixie dust (trust me on that one).

Hence, most companies will establish targets only for the KPIs deemed worthy of that hard work.

Guess what you should do with your time? Focus on analysis that is worth your hard work!

Start by looking at your slides/report/dashboard and identify the KPIs with established targets. Kill the rest.

Sure, there will be howls of protest. It’ll be John. Tell him that without targets you can’t identify if the performance is good or bad, a view every CEO deserves.

John will go away and do one of two things:

1. He will agree with you and focus on the KPIs that matter.

2. He will figure out how to get targets for all 32 metrics along all 18 dimensions.

You win either way. 🙂

An added benefit will be that with this sharp focus on targets, your company will get better at forecasting, competitive intelligence, investment planning, org changes, magic pixie dust and all the other things that over time become key assets. Oh, your Finance team will love you!

Special caution: Don’t ever forget your common sense, and strive for the Global Maxima. It is not uncommon for people to sandbag targets to ensure they earn a higher bonus. If your common sense suggests that the targets are far too low, show industry benchmarks. For example, the quarterly target may be 400,000 units sold. Common sense (and company love) tell you this seems low, so you check actuals to find that in the second month, units sold are already 380,000. Suspicion confirmed. You then check industry benchmarks: It is 1,800,000. WTH! In your CMO dashboard, report Actuals, Target and Benchmark. Let him or her reach an independent, more informed, conclusion about the company’s performance.

3. Focus on the outliers.

Turns out, you are the analyst for a multi-billion dollar corporation, with 98 truly justifiable KPIs (you are right: I’m struggling to breathe on hearing that justification, but let’s keep going). How do you focus on what matters most?

Focus your dashboards only on the KPIs where performance for that time period is three standard deviations away from the mean.

A small statistics detour.

If a data distribution is approximately normal then about 68 percent of the data values are within one standard deviation of the mean, about 95 percent are within two standard deviations, and about 99.7 percent lie within three standard deviations. [Wikipedia]

By saying focus on only reporting on KPIs whose performance is three standard deviations from the mean, I’m saying ignore the normal and the expected. Instead, focus on the non-normal and the unexpected.

If your performance does not vary much, consider two standard deviations away from the mean. If the variation is quite significant, use six (only partly kidding!).

The point is, if performance is in the territory you expect, how important is it to tell our leaders: The performance is as it always is.

Look for the outliers, deeply analyze the causal factors that lead to them, and take that to the executives. They will give you a giant hug (and more importantly, a raise).

There are many ways to do approach this. Take this image from my January 2007 post: Analytics Tip #9: Leverage Statistical Control Limits

Having an upper control limit and a lower control limit makes it easy to identify when performance is worth digger deeper into. When you should freak out, and when you should chill.

Look for outliers. If you find them, dig deeper. If not, move on permanently, or at least for the current reporting cycle.

Use whichever statistical strategies you prefer to find your outliers. Focus sharply.

4. Cascade the analysis and responsibility for data.

In some instances you won’t be able to convince the senior leader to allow you to narrow your focus. He or she will still want tons of data, perhaps because you are new or you are still earning credibility. Maybe it is just who they are. Or they lack trust in their own organization. No problem.

Take the 32 metrics and KPIs that are going to the CMO. Pick six critical KPIs for the senior leader.

Cluster the remaining 26 metrics.

You’ll ask this question:

Which of these remaining 26 metrics have a direct line of sight to the CMO’s six, and might be KPIs for the VPs who report to the CMO?

You might end up with eight for the VPs. Great.

Now ask this question:

Which of these remaining 18 metrics have a direct line of sight to the eight being reported to the VPs, and might be KPIs for the directors who report to the VPs?

You might end up with 14 for the directors.


Repeat it for managers, then marketers.

Typically, you’ll have none remaining for the Marketers.

Here’s your accomplishment: You’ve taken the 32 metrics that were being puked on the CMO and distributed them across the organization by level of responsibility. Furthermore, you’ve ensured everyone’s rowing in the same direction by creating a direct line of sight to the CMO’s six KPIs.

Pat yourself on the back. This is hard to do. Mom is proud!

Print the cascading map (CMO: 6 > VPs: 8 > Directors: 14 > Managers: 4), show it to the CMO to earn her or his confidence that you are not throwing away any data. You’ve simply ensured that each layer reporting to the CMO is focused on its most appropriate best sub-set, thus facilitating optimal accountability (and data snacking).

I’ll admit, this is hard to do.

You have to be deeply analytically savvy. You have to have acquired a rich understanding of the layers of the organization and what makes them tick. You have to be a persuasive communicator. And, be able to execute this in a way that demonstrates to the company that there’s real value in this cascade, that you are freeing up strategic thinking time.

You’ll recognize the overlap between the qualities I mention above and skills that drive fantastic data careers. That’s not a coincidence.

Carpe diem!

5. Get them hooked on text (out-of-sights).

If everything else fails, try this one. It is the hardest one because it’ll demand that you are truly an analysis ninja.

No senior executive wants data. It hurts me to write that, but it is true.

Every senior executive wants to be influenced by data and focus on solving problems that advance the business forward. The latter also happens to be their core competence, not the former.

Therefore, in the next iteration of the dashboard, add two more pieces of text for each metric:

1. Why did the metric perform this way?

Explain causal factors that influenced shifts. Basically, the out-of-sights (see TMAI #66 if you are a subscriber to my newsletter). Identifying the four attributes of an out-of-sight will require you to be an analysis ninja.

2. What actions should be taken?

Explain, based on causal factors, the recommended next step (or steps). This will require you to have deep relationships with the organization, and a solid understanding of its business strategy.

When you do this, you’ll begin to showcase multiple factors.

For the pointless metrics, neither the Why nor the What will have impact. The CMO will kill these in the first meeting.

For the decent metrics, it might take a meeting or three, but she’ll eventually acknowledge their lack of value and ask you to cascade them or kill them.

From those remaining, a handful will come to dominate the discussion, causing loads of arguments, and resulting in productive action. You’ll have known these are your KPIs, but it might take the CMO and her team a little while to get there.

After a few months, you’ll see that the data pukes have vanished. If you’ve done a really good job with the out-of-sights and actions, you’ll notice notice that the focus has shifted from the numbers to the text.

Massive. Yuge. Victory.

If more examples will be of value, I have two posts with illuminating examples that dive deeper into this strategy…

Strategic Dashboards: Best Practices, Tips, Examples | Smart Dashboard Modules: Insightful Dimensions And Best Metrics

You don’t want to be a reporting squirrel, because over time, that job will sap your soul.

If you find yourself in that spot, try one of the strategies above. If you are desperate, try them all. Some will be easier in your situation, while others might be a bit harder. Regardless, if you give them a shot, you’ll turn the tide slowly. Even one month in, you’ll feel the warm glow in your heart that analysis ninjas feel all the time.

Oh, and your company will be data-influenced — and a lot more successful. Let’s consider that a nice side effect. 🙂

Knock ’em dead!

As always, it is your turn now.

Have you used any of the above mentioned strategies in your analytics practice? What other strategies have been effective in your company? What is the hardest metric to get rid of, and the hardest KPI to compute for your clients? Why do you think companies keep hanging on to 28 metric dashboards?

Please share your ideas, wild theories, practical tips and examples via comments.

Thank you.


Orignal Article Can Be Found Here

The Very Best Digital Metrics For 15 Different Companies!

Colors The very best analysts distill, rather than dilute. The very best analysts focus, when most tend to scatter. The very best analysts display critical thinking, rather than giving into just what’s asked of them. The very best analysts are comfortable operating with ambiguity and incompleteness, while all others chase perfection in implementation / processing / reports. The very best analysts know what matter’s the most are not the insights from big data but clear actions and compelling business impact communicated simply.

The very best analysts practice the above principles every day in every dimension of their jobs. When I interview candidates, tt is that practice that I try to discern carefully. When I see evidence of these qualities in any candidate, my heart is filled with joy (and the candidate’s inbox is filled with a delightful job offer).

This post shares one application of the above skills.

People ask me this seemingly simple question all the time: What Key Performance Indicators should we use for our business? I usually ask in return: What are you trying to get done with your digital strategies?

From experience, I know that there is no one golden metric for everyone. We are all unique snowflakes! 🙂 Hence the optimal answer to the question comes from following a five-step process to build out the Digital Marketing and Measurement Model.

But, what if we did not have that opportunity? What if I was pushed to answer that question with just a cursory glance at their digital existence?

While it is a million times less than ideal, I can still come up with something good based on my distillation skills, application of critical thinking, comfort in operating in ambiguity and prioritizing what will likely help drive big actions. It won’t be perfect, but that is the entire point of this post. It is important, even critical, that we know how to operate in such a environment.

To impress you with the breadth and depth of possibilities, I’m going to take 15 completely different digital companies and share what are the very best key performance indicators (metrics) for each. I don’t know these companies intimately, just like you all I have is access to their digital existence. That’s what makes it such a great exercise of the aforementioned skills.


In the past I’ve shared a cluster of metrics that small, medium and large businesses can use as a springboard…

These are great starting points, but there is an assumption that based on your expertise and business knowledge that you’ll be able to personalize these.

The challenge I want to take on is to be specific in my recommendations, and to share how we can be very nimble and agile.

You’ll see three consistent patterns in the thinking expressed below (I encourage you to consider adopting them as well).

1. You’ll notice that I ask the five questions that help me identify the higher order bits related to the company. This is critical. They are from my post The Biggest Mistake Web Analysts Make… And How To Avoid It!

2. I am a passionate believer in focusing on the Macro AND Micro-Outcomes. It is the only way to ensure your leadership is not trapped in the let’s solve for only 2% of our business success thinking.

3. It pains me how quickly silos emerge in every company. There are Search people and Content people and Landing Page Optimizers and Cart fixers and Attribution Specialists and more. Everyone solves for their own silo, and IF everyone delivers you get to a local maxima. #tearsofpain One way of removing silos and focusing on the entire business is to leverage Acquisition, Behavior and Outcome metrics. This will allow, nay force, our senior business leaders to see the complete picture, see more of cause and effect, and create incentives for the disparate teams to work together.

A small change I’ll make in this post is that when I recommend the metrics, I’ll follow the Outcomes | Behavior | Acquisition structure. I’m reversing the order because when you talk to Senior Executives, they first, sadly sometimes only, care about all the moolah. We bend to this reality.

Hold me accountable to the above three patterns, if you see a mistake… please let me know via the comment form below.

Also, it is unlikely that I’ll have perfect answers for all 15 businesses below. Please chime and let me know what you would use instead or simply how would you improve the collection of metrics for each type of company.


Let’s look at 15 completely different business, and pick just six metrics (two each for A, B and O) that would be the very best ones to measure their digital success. The goal is for each company’s Google Data Studio to not look like a CDP (customized data puke), but to be a focused strategic dashboard with an emphasis on IABI.

If you want to play along. Don’t read what I’ve chosen. Click on the site link, go browse around, go to their social pages, checkout the mobile app, then write down the six metrics you would choose. Then, read on to see what I picked. You’ll discover immense learnings in the gaps between each set of choices (and share yours with me in comments below!).

Ecommerce: Betabrand

I love Betabrand. Their clothes and accessories are eclectic. The brand has a joy that is infectious. And, I’ve been impressed at how they’ve innovated when it comes to what business they really are in.

Here are six O, B, A metrics I would recommend for Betabrand’s strategic dashboard:

Outcomes: Revenue | Ideas Funded
Behavior: Path Length | Cart Abandonment Rate
Acquisition: Assisted Conversions | Share of Search

Every ecommerce site has to obsess about Revenue, hence I use that as the Macro-Outcome. After a consideration of their business evolution, I picked Ideas Funded as the important micro-outcome.

I love driving strategic emphasis on Path Length for larger ecommerce sites as it encourages an obsession away from one-night stands which is the standard operating model for most sites. The implications of Path Length will force a broader analysis of the business, which is harder and hence you’ll hire smarter analysts (#awesome). I feel Cart Abandonment is such an overlooked metric, it has tentacles into everything you are doing!

No decent ecommerce entity can live without a hard core focus on acquisition strategies that are powered by out-of-sights from Assisted Conversions data. Finally, Search (organic and paid) continues to be one of the largest contributor of traffic on mobile and desktop. Analyzing your Share of Search, from context you can glean from competitive intelligence tools), is extremely valuable.

Six simple insanely powerful metrics, simple business booming strategic dashboard.

What’s most important above is the thinking on display, the approach to identifying what’s absolutely essential, and an obsession with the higher-order bits. You swap out Ideas Funded for something relevant, and the above six can be used by any large ecommerce business.

A quick best practice.

You’ll also segment these metrics by your most important priorities.

For example, your company is shifting aggressively into leveraging Machine-Learning in your marketing strategies and hence have made a shift to Smart Display Campaigns a huge priority. Wonderful. You would segment the Assisted Conversions report by your Smart Display Campaigns to validate the power of Machine Learning. Remember: All data in aggregate is crap, segment or suck.

For the rest of this post, I’m going to try really hard to stay with the non-segmented metrics as it is much harder to pull that off. But on occasion I’ll mention the segment that would need more analytical focus as I believe it would yield a higher percentage of out-of-sights. You’ll see that on display in parenthesis (for example below).

Small Business Ecommerce: Lefty’s Sports Cards & Collectibles 

What if you are a tiny local business in a narrow niche, should you use the same approach as Betabrand? No. Always adapt to what’s most important and sensible for you (every measurement decision you make has a cost!).

Within a few minutes of visiting Lefty’s site – put on your sunglasses first – it will be clear that Lefty’s does not really care about their website. You can still put together a quick dashboard that will allow Jim and Bob to make smarter decisions by understanding the importance of their digital presence. Here’s how they could invest their limited budget smartly:

Outcomes: Autograph Pre-orders | Email Signups
Behavior: Unique Page Views (Gallery) | Bounce Rate (Mobile)
Acquisition: Visits | Click-to-delivery Rate

When my kids and I go meet their baseball heroes for autographs, we always book online. Hence the macro-outcome. Additionally, it is pretty clear from their site that email is a very big deal for them – and an ideal cheap marketing / acquisition strategy for them – hence the micro-outcome is Email signups.

Lefty’s stinks when it comes to user experience, even more so on mobile. Hence, I elevated Bounce Rate to a KPI (something I advice against). With the assumption that Galleries drive a lot of people to sign up, the value of UPVs rise in stature.

For a small business Visits are an important metric, even 500 more Visits a week can be huge. Since email is so important as an acquisition channel (and since likely nothing else works for them), I choose one of my three favorite email marketing metrics, CTDR.

Though we have looked at only a couple businesses, I hope you are starting to see common patterns in the approach to identify KPIs. Focus on what’s actually important from a strategy perspective. Macro and Micro-Outcomes. A focus on getting a sense for what the business is actually doing to make the hard choices needed to get to the perfect A, B, O metrics.

A quick best practice.

The metrics you elevate to Key Performance Indicators rarely stay there forever – that would be suicide. You’ll go through the normal metrics lifecycle

If you truly create strategic dashboards, follow the complete process above every six months. On the other hand, if your dashboards are CDPs (customized data pukes), be honest with yourself, I recommend doing this every three months.

B2B / Enterprise Sales: Salesforce

Very little B2B selling is data driven, this gives me profound grief. Mostly because in a B2B context we can deliver such an amazing impact! We as in digital marketers, salespeople, support people, analysts. Let me come back to that thought in a moment, here’s what I would recommend we measure for Salesforce:

Outcomes: Lead Conversion Rate (Visitor) | Trailheads Certified
Behavior: Page Value | Session Quality 
Acquisition: Visitors (Mobile) | Click-thru Rate (Paid)

Since every SINGLE thing of customer value at ends with the same gosh darn lead gen form, we measure Leads. 🙂 We focus on the better conversion rate definition, divide it by Visitors (or Users in GA). It creates an incentive to focus on people, and give each individual visitor the breathing room they need to convert (the burden then shifts to the company to be able to think smarter when it comes to the experience and incentives). I choose Trailhead Certified as the micro-outcome as there are multiple points of value from the Trailheads program (lower support costs, higher retention, faster time to value for clients etc.).

The site has tons and tons of content, almost haphazardly so. Hence for behavior the magical Page Value metric. It will help Salesforce hold every piece of content accountable for delivering business impact (macro or/and micro). Session Quality leverages machine learning to provide Salesforce with behavioral analysis to help personalize the user experience and customize off-site marketing experience. It is a cool KPI you should explore for businesses of any kind.

Mobile is massively undervalued by most B2B companies (including SF), hence the acquisition emphasis there. CTR puts the emphasis on right message to the right person at the right time.

B2B analytics are insanely sexy and exciting. Yes. Really. Please be creative in your analytics efforts, and don’t take no for an answer when it comes to the value of analytics. Don’t accept the excuse oh but all the sales come via phone or I convert at industry events or our buyers are old school! 

A quick best practice.

Push. But, be picky, focus on big important pieces. For example, Salesforce spends tons of people/money on social media posting/activity and you can see this on display on their Facebook, Twitter, YouTube, and other social platforms. A cursory review will demonstrate that a low double digit number of humans engage with this massive amount of content Salesforce publishes. Almost all that investment is wasted (and don’t even get me started on the opportunity cost!).

Yet, you won’t notice it in my KPIs. Yes, their current social strategy not great use of time or money, but we have bigger fish to fry. Make tough choices.

Newspapers: Tampa Bay Times

I am a huge political junkie and it truly breaks my heart that newspapers are dying. I pay monthly subscriptions for the Guardian, New York Times, Washington Post, The New Yorker and National Geographic. We are a better humanity thanks to the work of journalists, I hope the industry finds a sustainable business model.

You’ll see my pet peeves about what media entities don’t measure currently in my recommendations:

Outcomes: New Subscriptions | My Edition Signups 
Behavior: Recency | Unique Page Views (Content Groups)
Acquisition: Visits (Referrals) | % New Visits

With advertising revenue in a tailspin, New Subscriptions are more important than ever and hence that’s our macro-outcome KPI. I have a massive bias against the current click-bait, let’s go viral, “hot story of the moment” traffic. I humbly believe the answer is to solve for loyalty, which if we don’t suck at it, will drive New Subs. Hence, the micro-outcome choice is My Edition Signups. It forces TBT to assess if people find the site valuable enough to open an account, and is TBT then personalizing the experience enough to drive loyalty.

Continuing the obsession with deeper relationships… TBT is a newspaper that’s updated 80k times a day, how does the Recency distribution look like? I visit the New Yorker 8 times each day on average (closer relationship, higher perception of value, and as a result I’m a paying subscriber). Our second behavior metric, Unique Page Views, helps quantify content consumption.

Here’s a lovely graph, from one of my older posts, that would be immensely valuable in trying to find the balance between content production and content consumption.

I would tweak it a bit. For each section of the site, Unique Page Views vs. Amount of Content published in that section. It provides critical food for thought in trying to balance what content and people does it need more of and less of.

In picking acquisition metrics I’m trying to counterbalance my bias to have deeper individual relationships over time. Visits – with an emphasis on referrals, with a deeper segmentation of social and mobile because of how humans get content these days – and % New Visits to grow.

A quick best practice.

You are always going to have biases. It is ok. Invest in becoming aware of them. And, when you catch yourself taking actions due to those biases, correct for them in the best way possible. In the above case, I counterbalanced for my bias in Behavior and Outcomes by choosing against my bias in the Acquisition section.

Charity/Non-Profits: The Smile Train

As some of you know, 100% of the proceeds from both of my books are donated to charity. Thus far, well over $100,000 each to The Smile Train, Doctors Without Borders and Ekal Vidyalaya. Thanks for buying my books.

Digital is a valuable component of The Smile Train’s strategy, here’s how we can measure effectiveness…

Outcomes: Donations (Online, Tracked phone calls) | Cause Related Clicks
Behavior: Amplification Rate | Completed Views (Videos, Stories)
Acquisition: Visitors (Geo) | Clicks (Social)

Donations, straightforward. Of all the micro-outcomes the one that was really innovative (and trackable!) was the Cause Related Marketing effort. So clever of them to become a part of people’s lives to raise money rather than the usual annual donation.

Charities can only market themselves so much, they have to figure out how to get the rest of us to do it for them. They have great content, if we believe in them then ST has to get us to amplify it for them. I love the stories they have, there is the obligatory collection of social links on the top, but they don’t overtly ask you to amplify. How about if I scroll through most of the story then a subtle pop-up from the bottom-right asking me to amplify via my social channels? I can get them to more people like me, more donations. Hence, Amplification Rate is my first behavior metric (to incentivize both ST and site visitors). Smile Train has precious resources, leverage event tracking to measure completed views of all the content is a fabulous way to drive a persistent focus on content optimization.

Charities have opinions about where their donors come from, I recommend a Geo segmentation strategy to understand Visitors to the site to broaden the leadership’s horizons (literally!). You can of course segment this by other elements. Social is a big part for every charity. To avoid Smile Train peanut-buttering their social strategy, measuring Social Clicks is a really sound way to understand where to put more/less effort.

A quick best practice.

Digital strategy for nonprofits should be more innovative than what you currently see. For example, for me the coolest lesson of Bernie 2016 is the mobile fundraising innovation. So, so, so many clever things done that charities should learn from and implement when it comes to their mobile strategy (to complement their 1961 strategy of text Red Cross to 12347 to donate $10).

Pharmaceutical: Humira 

There are some restrictions on selling prescription drugs in the US. This places some limits in terms of what we can track in web analytics tools. Not just PII, which we can’t track anyway, but the ability to use anonymous cookies for remarketing so on and so forth. Still, we can provide transformative KPIs in our Pharma practice:

Outcomes: Humira Complete Signups | Doctor Lookups 
Behavior: Unique Page Views (Condition) | Visitor Status (Login)
Acquisition: Visits (TV) | Click-Share (Search)

You can get tons of enticing stuff if you sign up for Humira Complete, including a Savings Card, and clearly the brand gets a lot out of it. Hence that’ll be our macro-outcome. There are lots of micro-outcomes, in this case given most Pharma companies are still in the early stages of savvy, I choose something close to making money, Doctor Lookups. I know Pharma companies also value prospective patients downloading the Discussion Guides which could also be a micro-outcome (in this case you get that after you do the Lookup).

The Humira site solves for 10 different conditions. That makes UPVs a great KPI to get deep visibility into what content is being consumed. The site hopes to drive a beyond the prescription connection with patients, with loads of resources behind the login. Hence, we use custom variables to track logged in status and we can analyze a whole host of valuable behavior and optimize our investments.

Humira does not believe in digital (ok, I’m just teasing them) but they love, love, love TV. Analysis that leverages their complete media plan in conjunction with site traffic will help provide one important measure of TV effectiveness. Ditto for any other major offline blitzes that Abbvie is running. Our last piece of the puzzle is AdWords Click-Share. There were 1,592,527 searches for Ankylosing Spondylitis, how many those clicks did you get? 1.2%. Great. Now shoot for 20% if you actually believe your drug is effective!

A quick best practice.

There is only one channel where our ability to discern intent is super-strong: Search. On Yandex. On Baidu. On Google. On Seznam. It is a little silly to think of Search in archaic terms like “Brand” and “Category.”

Think in terms of clusters of intent that you can solve for. See. Think. Do. Care. Search will solve for Think and Do. Sometimes your “Brand” terms will have weak commercial intent – in that case you should have Think Targeting and Think Content marketing strategies. Likewise your “Category” terms might reflect strong commercial intent, in that case Do marketing strategies will allow you to win bigger.

Let your competition be lame and play by a 1997 worldview. You take advantage of them by living in 2017!

As the post is getting long, understatement of the decade, let me just make recommendations for metrics for rest of teh businesses, and let you explore the site to figure out why they make the most sense in each case.

Government: California Department of Motor Vehicles

I love governments!

Outcomes: Online Applications/Renewals | Downloads
Behavior: Visits with Search | Customer Satisfaction (by Primary Purpose)
Acquisition: Visitors (Channels) | Visitors (City)

Task Completion by Primary Purpose is my absolute favorite metric for any website (all the ones above). It made most sense here. It is a part of my simple three questions that make the greatest survey questions ever.

A quick best practice.

A much more detailed collection of recommendations I’d written for the Government of Belgium a little while back: Web Analytics Success Measurement For Government Websites.

Stock Photography: Shutterstock

I spend hours looking for inspiration for the stock photos that end up on my LinkedIn Influencer channel posts.

Outcomes: Lifetime Value (Revenue Per User) |  Contributor Signups
Behavior: Cohort Analysis | Top Event (by Category) 
Acquisition: Visitors | Assisted Conversions

For someone as savvy as Shutterstock, Cohort Analysis at the intersection of incredible behavior analysis and optimizing acquisition across media channels.

Movie Studio: The Fate of the Furious

I hear it is Oscar-worthy. : )

Outcomes: Ticket Purchases | Completed Trailers 
Behavior: Unique Page Views | Outbound Clicks (All Access+) 
Acquisition: Visits | CTR (Paid)

One shift in movie sites is that the metrics and strategy have distinct phases, per-release, post-release, off-theaters (DVD, digital sales). You’ll have to have three sets of metrics as outcomes and marketing strategies change.

Mobile Gaming: Jam City 

Raise your hands if you love mobile games!

Outcomes: Downloads (by Store) |  Support Requests
Behavior: Videos Watched | Goal Flow (Source)
Acquisition: Click-Share (Mobile Search) | Visitors (Similar Audiences)

We are only measuring the value the website (mobile and desktop). If we had to measure the Apps itself, there would be an entire new cluster of metrics including 30-day MAUs, Lifetime Value, Sessions/User, so and and so forth.

Automotive Dealer: Nissan Sunnyvale 

Electric cars FTW!

Outcomes: No Brainer Price Requests | Service Appointments 
Behavior: Unique Page Views (Purpose Type) | Sessions With Search 
Acquisition: Visitors | Paid Clicks (by Media)

I have to admit I’m usually pretty torn between tracking online leads (no brainer request in this case) vs. leads via Chat (very prominent on most dealer sites) or Phone (very common). Often Chat and Phone can be more valuable (and numerous) than the online leads.

Food / Beverages: McCormick 

If there is an industry stuck in 1920s, it is the food companies (of all types). Their core value proposition from digital is still recipes – a marketing strategy as old as packed food. And not even interactive digital-first recipes – the same boring presentation and text as you’ll find on the back of the box!

There is so, so, so, so much more that food, beverages and restaurant companies can do. Digital is all pervasive in our lives, food is something we love and adore (and a top five category in content consumption on YouTube!), mobile allows these brands to be ever closer to us… all that’s needed is a pinch of imagination. PopChips and Chobani are two that show imagination with their content strategies, hopefully they inspire others.

Let’s see what we can measure if we had to do it for a great old brand McCormick.

Outcomes: Shopping Lists Created | Reviews Submitted
Behavior: Frequency | Events (Content Type)
Acquisition: Visitors (Referrals) | Clicks (Remarketing)

I came close to using Login Status for behavior, it would provide fascinating insight into the ability of McCormick to create loyalty, even brand evangelists. But, a quick peek at the competitive intelligence data shows that it is seems it is not all that important (barely any people login). If I were at McCormick I would look at the GA data and double-validate that. If it seems to be a big enough number, we can use Login Status as a segmentation strategy.

Tech Support: Dell US

Digital analytics for a tech support site tends to be a lot of fun, primarily because you can directly drive costs down and increase repurchase rate (loyalty) – thus hitting both sides of the balance sheet causing your CFO to give you a thousand kisses. 

Outcomes: Task Completion Rate (split by Primary Purpose, and Direct vs. Community support) | System Updates (Drivers, Diagnostics etc.)
Behavior: Page Views per Visit | Visits to Resolution 
Acquisition: Visits | Search Click-Share

A long, long time ago, when I was but a youth, I had a view on this topic… Measuring Success for a Support Website.

Social | YouTube: Prudential

In case your primary digital existence consists of a YouTube channel (I hope that is not the case, you want to have a solid owned AND rent platform strategies).

Outcomes: Subscribers | Brand Consideration
Behavior: Views (by Content Type) | Conversation Rate 
Acquisition: Views | Sources

I have a detailed primer on comprehensive YouTube success. It has more metrics you can use, if indeed you are a YouTube only existence.

Social | Facebook: Priceline

Priceline is a typical brand, and their page illustrates why an organic strategy is worth almost nothing on Facebook. You can easily validate that statement. Go ahead and click on the link above. As you scroll, you’ll notice that the numbers you see for each post are less than tiny. This applies for all companies, not just Priceline.

Facebook is an important strategy for your company, just let your focus be on a Paid Media strategy and measure success as you would any paid strategy.

But, if like Priceline you continue to have your organic content strategy on Facebook (or Twitter)…

Outcomes: Page Likes | Brand Consideration 
Behavior: Amplification Rate | Conversation Rate 
Acquisition: Visits | Paid Likes

You can do a lot more of course, if Facebook is your only digital outpost (though, again, I hope that is not the case as you need to have an owned and rented platform strategy)…

More here: Facebook Advertising / Marketing: Best Metrics, ROI, Business Value.

There you are. Fifteen completely different types of digital businesses that we can measure immensely effectively, usually uniquely, with the rich collection of data we have in any free/paid digital analytics solution.

I hope that you discovered new valuable metrics that will become KPIs to measure your Acquisition, Behavior and Outcome efforts. But, what I hope you’ll take away more is the application of critical thinking, to be more comfortable operating in ambiguity and bring ruthless focus and prioritization what is most likely to drive big action. You don’t have to get it all right the first time. Implement. Evaluate. Kill/Keep. Improve. Rinse. Repeat.

Carpe diem!

As always, it is your turn now.

If you picked six metrics (two each for A, B, O) for any site above, will you please share them via comments below? Is there a metric above that you particularly love/hate, why? Is there a metric you would use instead of something I used? Is there a type of site you have had a hard time picking metrics that matter the most? You’ve surely noticed some patterns in what I tend to like and don’t (notice, no time metrics above!), will you share your thoughts if you feel there is a sub-optimal bias there?

I look forward to your guidance to improve what I know, fill in gaps in my knowledge and the wisdom you have that I completely overlooked. Please share via comments.

Thank you.

The Very Best Digital Metrics For 15 Different Companies! is a post from: Occam’s Razor by Avinash Kaushik

Source: Avinash

Be Real-World Smart: A Beginner's Advanced Google Analytics Guide

NectarBeing book smart is good. The outcome of book smart is rarely better for analytics practitioners then folks trying to learn how to fly an airplane from how-to books.

Hence, I have been obsessed with encouraging you to get actual data to learn from. This is all the way from Aug 2009: Web Analytics Career Advice: Play In The Real World! Or a subsequent post about how to build a successful career: Web Analytics Career Guide: From Zero To Hero In Five Steps. Or compressing my experience into custom reports and advanced segments I’ve shared.

The problem for many new or experienced analysts has been that they either don’t have access to any dataset (newbies) or the data they have access to is finite or from an incomplete or incorrect implementation (experienced). For our Market Motive Analytics training course, we provide students with access to one ecommerce and one non-ecommerce site because they simply can’t learn well enough from my magnificent videos. The problem of course is that not everyone is enrolling our course! 🙂

All this context is the reason that I am really, really excited the team at Google has decided to make a real-world dataset available to everyone on planet Earth (and to all intelligent life forms in the universe that would like to learn digital analytics).

The data belongs to the Google Merchandise Store, where incredibly people buy Google branded stuff for large sums of money (average order value: $115.67, eat your heart out Amazon!). And, happily, it has almost all of the Google Analytics features implemented correctly. This gives Earth’s residents almost all the reports we would like to look at, and hence do almost all the analysis you might want to do in your quest to become an Analysis Ninja. (Deepak, would you kindly add Goal Values for the Goals. Merci!) You’ll also be able to create your own custom reports, advanced segments, filters, share with the world everything you create, and all kinds of fun stuff.

For consultants and opinion makers you no longer have to accept any baloney peddled to you about what analytics tool is the best or better fit for your company/client. Just get access to this data and play with the actual GA account along with Adobe and IBM and WebTrends et. al. and suddenly your voices/words will have 10x more confidence informed by real-world usage. No NDA’s to sign, no software to install, no IT resources required. Awesome, right?

In this post I’ll highlight some of my favourite things you can do, and learn from, in the Store dataset. Along the way I’ll share some of my favourite metrics and analytics best practices that should accelerate your path to becoming a true Analysis Ninja. I’ve broken the post into these sections:

I’m sure you are as excited as I am to just get going. Let’s go!

How to get Store Dataset Access?

It is brilliantly easy.

Go to the Analytics Help Demo Account page. Read the bit in the gray box titled Important. Digest it.

Then click on this text: ––>ACCESS DEMO ACCOUNT<––

Looks scary in the all caps, right? That is just how the Google Analytics team rolls. 🙂

You’ll see a tab open, urls will flip around, in two seconds you’ll see something like this on your Accounts page…

google analytics accounts view

Click on 1 Master View and you are in business.

If you ever want to remove access to this real-world data, just go back to the page above and follow the five simple steps to self-remove access.

Jump-Start Your Learning.

You can start with all the standard reports, but perhaps the fastest way for you to start exploring the best features is to download some of the wonderful solutions in the Google Analytics Solutions Gallery.

You’ll find my Occam’s Razor Awesomeness bundle there as well.

It is a collection of advanced segments, custom reports, and dashboards. You’ll have lots of features incorporated in them. You can customize them to suit your needs, or as you learn more, but you won’t have to start with a blank slate.

You can also search for other stuff, like custom reports or attribution models.

Another tip. If you are a complete newbie (welcome to our world!), you probably want to start your journey by reading about each type of report, and then looking at the Overview report in each section in Google Analytics. At this point you’ll be a little confused about some metric or the other. That’s ok. Go, read one of the best pages in the Analytics help center: Understanding Dimensions and Metrics. Go back into GA, you’ll understand a whole lot more.

This is a beginner’s advanced guide, so I’m going to do something different. Through my favourite reports, often hard to find in your company’s GA dataset, I’m going to push you beyond other beginner’s guides. I’ll also highlight frameworks, metrics, custom reports, and other elements I feel most Analyst’s don’t poke around enough.

1. Play with Enhanced Ecommerce Reports.

It is a source of great sadness for me that every single site is not taking advantage of Enhanced Ecommerce tracking and analysis . It is a complete rethink of ecommerce analysis. The kind of reports and metrics you’ll get straight out of the box are really amazing.

Go to the Reporting section of our Store Demo account, click on Conversions in the left nav, then Ecommerce, and now Overview. You’ll see in an instant the very cool things you can track and analyze…

ecommerce overview

With a little bit of smart tagging you can track your internal promotions (buy one Make America Great Again hat and get one Stronger Together hat free!), transactions with coupon codes, affiliate sales and more. Very nicely summarized above.

Next go to the report with new things that will help you drive smarter merchandizing on your mobile and desktop websites. Go to Shopping Analysis and click on Shopping Behavior…

shopping behavior analysis google analytics

I adore this report.

Most of the time when we do funnel analysis we start at the Cart stage (third bar above). We rarely hold people responsible for Traffic Acquisition accountable, we rarely hold people responsible for Site Design and Merchandizing accountable. The former are promoted on silly metrics like Visits or Visitors or (worse) Clicks. The latter are promoted based on silly metrics like PageViews.

The first bar to the second shows the number of visits during which people went from general pages on your website to product pages (places were there is stuff to be sold, add to cart buttons). A lame 26%. See what I mean. Insightful. How are you going to make money if 74% of the visits don’t even see a product page!

The second bar the third is even more heart-breaking, as if that were possible. Of the sessions with pages with product views, how many added something to cart. A lousy 17%. One. Seven. Percent! On a site were you can do nothing except buy things.

See what I mean? Question time for your Acquisition, Design and Merchandizing team.

Do you know answers like these for your website? That is why you need Enhanced Ecommerce.

I won’t cover the last two bars, most of you are likely over indexing on funnel analysis.

Practice segmentation while you are here. Click on + Add Segment on top of this report, choose Google (or whatever interests you)…

google traffic segment

And you can analyze acquisition performance with a unique lens (remember you can’t segment the funnel that exists in the old ecommerce reports which is still in your GA account!)…

shopping behavior analysis google traffic

A little better. Still. You spend money on SEO and PPC. It should be a lot better than this. If this were your data, start with questioning your PPC landing page strategy and then move to looking at your top SEO landing pages, and then look at bounce rates and next page analysis for those that stay.

I can honestly spend hours on just this report digging using segmentation (geo, media, new and loyal customers, all kinds of traffic, product page types and so on). It has been a great way to immediately influence revenue for my ecommerce engagements.

While you are here, you can play and learn to use the new funnel report… it is called Checkout Behavior Analysis…

checkout behavior analysis google analytics

Much simpler, so much easier to understand.

You can also, FINALLY, segment this report as well. Try it when you are in the Store demo account.

Take a break. A couple days later come back and checkout the new Product Performance and Product List Performance reports. The latter is particularly useful as an aggregated view for senior executives. In case of the Store data, the first report has 500 rows of data, the second just 45. Nice.

I wanted to flag three metrics to look at in the Product Performance report.

Product Refund Amount is $0.00 in this dataset, but for your company this is a great way to track refunds you might have issued and track were more of that is happening.

I love Cart-To-Detail Rate (product adds divided by views of product details) and Buy-to-Detail Rate (unique purchases divided by views of product-detail pages). Remember I was so upset above about the poor merchandizing. Using the sorting option on these two columns I identify where the problem is worse and where I can learn lessons from. Very cool, try it.

I could keep going on about more lovely things you’ll find in the Enhanced Ecommerce reports, but let me stop here and have you bump into those cool things as, and I can say this now, you have access to this data as well!

Bonus: If you are a newbie, in your interview you’ll be expected to know a lot about Goals (I call the micro-outcomes). Explore that section. Look the Overview, Goal URLs and Smart Goals. Ignore the eminently useless Reverse Goal Path report (I don’t even know why this is still in GA after years of uselessness) and Funnel Visualization (almost totally useless in context of almost all Goals).

2. Gain Attribution Modeling Savvy.

My profound disdain for last-click reporting/analysis is well known. If you are using last-click anything, you want your company to make bad decisions. See. Strong feelings.

Yet, many don’t have access to a well set-up account to build attribution modeling savvy and take their company’s analytics the year 2013. Now, you can!

I am big believer in evolution (hence my marketing and analytics ladders of awesomeness). Hence, start by looking at the Assisted Conversions report (Conversions > Multi-Channel Funnels)…

assisted conversions google analytics

Then metric you want to get your company used to first, to get them ready for savvier attribution anything, is the metric Assisted Conversions. The last column.

Here’s the official definition: A value close to 0 indicates that this channel functioned primarily as the final conversion interaction. A value close to 1 indicates that this channel functioned equally in an assist role and as the final conversion interaction. The more this value exceeds 1, the more this channel functioned in an assist role .

Now scroll just a bit back up, stare at that column, what would your strategy be for Organic Search if it is at 0.46? What about Display advertising driving which plays primarily an “upper funnel” introducing your brand to prospects 1.58?

The change required based on this data is not just your marketing portfolio re-allocation, that is almost trivial, what’ bigger, huger, crazy-harder is changing how your company thinks. It is painful. Largely because it quickly becomes about how people’s budgets/egos/bonuses. But, hundreds of conversions are on the line as well on insights you’ll get from this data. Learn how to use this metric to drive those two changes: marketing portfolio – people thinking.

Couple bonus learnings on this report.

On top of the table you’ll see text called Primary Dimension. In that row click on Source/Medium. This is such a simple step, yet brings you next layer of actionable insights so quickly. You’ll see some surprises there.

Second, look at the top of the report, you’ll see a graph. On to top right of the graph you’ll see three buttons, click on the one called Days before Conversion…

assisted conversions days before conversion

I love this report because it helps me understand the distribution of purchase behavior much better. I profoundly dislike averages, they hide insights. This report is the only place you can see distribution of days to purchase for Assisted Conversions.

If you’ve changed the think in your company with Assisted Conversions… You are ready for the thing that gets a lot of press… Attribution Modeling!

You’ll find the report here: Conversions > Attribution > Model Comparison.

You’ll see text called Select Model next to Last Interaction. Click on the drop down, ignore all the other models, they are all value deficient, click on the only one with decent-enough value, Time Decay, this is what you’ll see…

attribution modeling last click vs time decay

Half of you reading this post are wondering why I don’t like your bff First-Interaction (it is likely the worst one on the list btw) or your bff Linear (the laziest one on the list)… worry not, checkout this post: Multi-Channel Attribution Modeling: The Good, Bad and Ugly Models .

The column you are of course looking at is % Change in Conversions. The GA team is also helping you out by helping you understand where the results are significant, green and red arrows, and where it is directional, up or down gray arrows.

This is the data you’ll use to drive discussions about a change in your marketing $$$ allocations.

Where you have CPA, it is is an even more valuable signal. And, such a blessing that the Store demo account has that data for you.

You’ll need all your brain power to understand the report above (make sure you read the models post above), and then some more to drive the change in how your company thinks. Attribution model is not a software or math problem, it is an entrenched human minds problem.

And because I’m the author of the quote all data in aggregate is crap I recommend scrolling up a bit in the attribution modeling report and clicking on the down arrow under the word Conversion….

attribution modeling goals analysis

This is admittedly an advanced thing to learn because even understanding marketing dollars plus user behavior overall is hard, this just makes it a bit more complicated because you can actually understand those two things for every goal you have individually or just ecommerce all by itself.

It is incredibly awesome to be able to do that because now you are this super-data-intelligent-genius that can move every variable in a complex regression equation very finely to have max impact on your company.

If you can master this, and IF you can evolve how your company does marketing portfolio allocation and how it thinks, then you are ready for the max you can do in Google Analytics when it comes to attribution… custom attribution modeling.

On top of the table, click on Select Model, then Create New Custom Model.

To get you going, here’s one of my models for a client…

custom attribution model

Custom attribution models are called custom because they are custom to every company. It requires an understanding for everything I’ve requested you to do above, business priorities (what the business values), and business strategy.

Creating a couple different custom attribution models, seeing how it affects the data, what decisions GA recommends, helps you have an intelligent argument with all your stake holders. Again, the decisions from this analysis will flow into changes to your marketing portfolio and how people in your company think.

Once you get into custom attribution modeling, and you spend serious amount of money on marketing online (a few million dollars at least), you are ready for the thing that actually will drive the best changes: Controlled Experiments (aka media mix modeling). Hence, it is critical that you approach your learnings in the precise steps above, don’t jump steps if at one of them you have not changed how your company thinks.

Bonus 1: You might think the above is plenty advanced. It is not. For the higher order bits, when you are all grown up, read this post and internalize the implications of it: Multi-Channel Attribution: Definitions, Models and a Reality Check

Bonus 2: The Time Lag and Path Length reports in your Multi-Channel Funnels folder are extremely worth learning about. I like Path Length more, more insightful. When you analyze the data, be sure to play with the options under Conversion, Type (click AdWords), Interaction Type and Lookback Window. With each step absorb the patterns that’ll emerge in the data. Priceless.

3. Learn Event Tracking’s Immense Value

I’m very fond of Event Tracking for one simple reason. You have to create it from scratch. When you open GA, there is no data in these reports. It can only get there if you spend time trying to understand what’s important to the business (Digital Marketing and Measurement Model FTW!), what is really worth tracking, and then through intelligent thought implementing the tracking.

I love the fact that you have to literally create data from scratch. For any beginner who is trying to get to advanced, Event Tracking will teach you a lot not just about Event Tracking but creating smart data.

Lucky for us the GA team has created some data for us to play with. Go to Behavior in the left nav, then Events, and then Top Events… This is what you’ll see…

event tracking top events

The Store team is capturing four events, you can drill down into any one of them to get a deeper peek into user behavior.

I choose Contact Us to analyze the Event Labels, I get all these strategies that people…

event tracking event lables

It would be valuable if the Event Value had been populated, which would also give us Avg. Value in the table above. Still. Understand that data, how it is collected, what it implies about user behavior is incredibly valuable.

You can also create an advanced segment for any of the events above, example Email. Then, you can apply that segment to any of other reports in Google Analytics and really get deep insights. What cities originate people who call is on the phone? What sites did they come from? How many visits have they made to the site before calling? So on and so forth.

The event tracking reports have three options on top of the report. Event, Site Usage, Ecommerce.

Try the Ecommerce tab…

event tracking ecommerce drilldown

While we did not see any event values, you can tie the sessions where the events were fired with outcomes on the site. Really useful in so many cases where you invest in special content, rich media, interactive elements, outbound links, merchandizing strategies etc. This report, in those cases, will have data you need to make smarter decisions faster.

Bonus: While you are in the Behavior section of Analytics, familiarize yourself with the Site Speed report. Start with the scorecard in the overview report. Move on to Page Timings to find the pages that might be having issues. One cool and helpful visual is Map Overlap, click the link on top of the graph on the Page Timings report. Close with the Speed Suggestions report. Your IT team needs this data for getting things fixed. Your SEO team can do the begging, if required. 🙂

4. Obsess, Absolutely Obsess, About Content

It is a source of intense distress for me that there’s an extraordinary obsession about traffic acquisition (PPC! Affiliates! Cheat Sheet for Video Ads!), and there is huge obsession with outcomes (Conversion Rate! Revenue!), there is such little attention paid to the thing that sits in the middle of those two things: Content!!

Very few people deeply look at content. Yes, there will be a top pages report or top landing pages report. But, that is barely scratching the surface.

Look. If you suck at content, the greatest acquisition strategy will deliver no outcomes.

Obsess about content dimensions and content metrics.

Since you know some of the normal reports already, let me share with you a report that works on many sites (sadly not all), that not many of you are using.

The Content Drilldown report uses the natural folder structure you are using on your website (if you are) and then aggregates content on those folders to show you performance. Here is what you’ll see in the Store demo account you are using…

content drilldown report google analytics

Nice, right? You are pretty much seeing all of the content consumption behavior in the top ten rows!

A pause though. This report is sub-optimally constructed. It shows Pageviews (good), Unique Pageviews (great) and then three metrics that don’t quite work as well: Average Time on Page, Bounce Rate, % Exit (worst metric in GA btw if anyone asks in an interview)…

content drilldown report google analytics 2

At a folder level these really help provide any decent insights, and might not even make any sense. Think about it. Bounce Rate for a folder?

Good time for you to learn simple custom reporting.

On top of the report, right under the report title, you’ll see a button called Customize. Press it. Choose more optimal metrics, and in a few seconds you’ll have a report that you like.

This is the one I created for my use with valu-added content metrics that work better: Average Session Duration, Cart-to-Detail Rate (as it is an ecommerce site) and Page Value (to capture both ecom and goal values at a page level)…

content drilldown custom report google analytics

Much better, right? Would you choose a different metric? Please share it via comments below.

Ok. Unpause.

Even a quick eyeballing of the report above already raises great questions related to overall content consumption (Unique Pageviews), merchandizing (Cart-to-Detail Rate) and of course money.

You can now easily drill-down to other more valuable bits of content and user experience.

I click on the first one, most content consumption, to reveal the next level of detail. I can see that Apparel is the biggest cluster of content, with pretty decent Cart-to-Detail Rate…

content drilldown 2 custom report google analytics

Depending on the business priorities I can ask questions like how come the summer olympic games stuff no one seems to want (and we spent $140 mil on an Olympics sponsorship, kidding).

At the moment the company has a huge investment in Google Maps branding, so we can look at how various brands are doing… YouTube FTW!

content drilldown 3 custom report google analytics

Maps is not doing so well. You can see how this data might make you curious if this list is what your business strategy is expecting will happen? Or, is this how we prioritize content creation? I mean, Go! People are interested in something esoteric like Go (programming language in case you are curious) rather than Nest! What a surprise.

That is what this type of content analysis is so good at.

You can continue to follow the rabbit hole by the way and get down to the individual pages in any folder, like so…

content drilldown 4 custom report google analytics

Ten percent Cart-to-Detail Rate is pretty poor, compared to some of the others above. Time to rethink if we should even be selling this combo! If not that, definitely time to look at the page and rethink copy, images, design, and other elements to improve this key metric.

The above custom report is really easy to create, for Subscribers of my newsletter I’ll also email a downloadable link for this and other custom reports below.

Bonus: Most people stop at what the reports show in the default view. The GA team does a great job of adding good think and express it all over the standard reports. For example, in context of our discussion here, try the Content Grouping primary dimension. Here you see what happens to the report when I switch to Brands (Content Group)…

all pages report content groupings

Even more useful than what was there before, right? So, how does GA get this data? As in the case of Event Tracking above, the Analyst and business decision making combination are thoughtfully manufacturing data. In this case using the immensely valuable Content Groupings feature. Invest in learning how to use it in the Store demo account, learn how to create content groupings to manufacture useful data. When you interview for higher level Analytics role, or for a first time Analyst role, you’ll stand out in the interview because this is hard and requires a lot of business savvy (ironic right, you stand out because of your business savvy in a Data Analyst interview!).

5. SEO & PPC, Because You Should!

Ok, you’ve waited long enough, time to talk about the thing you likely spend a ton of time on: Acquisition.

Since you likely already know how to report Traffic Source and how to find the Referring URLs and Sessions and… all the normal stuff. Let me focus on two things that are a bit more advanced, and will encourage you to learn things most people likely ignoring.

The first one I want you to immerse yourself in when you are in the Store data is Search Engine Optimization. You know that this is hard because when you go to Acquisition > Campaigns (what!) > Organic Keywords you will see that 95% are labeled “(not provided)”. This report is completely useless.

You do have other options to analyze SEO performance. Here’s the advanced, advanced, lesson: Search: Not Provided: What Remains, Keyword Data Options, the Future.

But, you also have some ability in Google Analytics itself to do keyword level analysis for Google’s organic search traffic. Go to Acquisition > Search Console > Queries. This report shows you the top thousands of keywords (4,974 precisely today in the Store report today). The data is available because the team has configured the Search Console data to connect with GA.

Here’s what you’ll see…

organic search queries report google analytics

I sort the data by Clicks, because Impressions is a lot less valuable, and with Clicks I get something closer to Sessions (though they are very different metrics). I immediately value CTR as a metric in this context, you can see the variations above. This is perfect immediate data for SEO discussions.

Average Position is also interesting, perhaps more so for my peers in the SEO team. As a Business Analyst I value Average Position a lot less in a world of hyper-personalized search.

My next data analysis step is to take this data out of GA (click Export on top of the report) and play with it to find macro patterns in the data. I’ll start with something simple as creating tag clouds, using Clicks or CTR as contextual metrics. I’ll classify each keyword by intent or other clusters to look for insights.

Try these strategies, can you find weaknesses in the Google Store’s SEO strategy? How do your insights compare to what you just discovered in the content analysis in terms of what site visitors actually want? Really valuable stuff.

What you cannot do with this data is tie it to the rest of the data in GA for these visitors. You cannot get conversions for example, or Page Depth etc. This is heart-breaking. But, see the not provided post I’ve linked to above for more strategies and meanwhile you can do some cool things in Google Analytics when it comes to SEO.

Bonus: In the Search Console reports, I also find the Landing Pages report is also helpful because you can flip the center of universe, for the same metrics as above, to landing pages rather than keywords. The insights you get will be helpful for your SEO team but more than that it will be critical for your site content team.

A quick note on the above… for the current data you’ll see the Landing Pages report looks a little weird with no data in the Behavior and Conversion columns. Something weird is going on, on my other accounts there is data. The team can fix this in the very near future.

Next, spend a lot of time in the AdWords section.

Both because Paid Search if often a very important part of any company’s acquisition strategy, and because at the moment there are few digital acquisition channels as sophisticated and complex as AdWords. When you are getting ready for your interviews, being good at this, really good, is a great way to blow your interviewer away because most people will know only superficial stuff about AdWords.

As if those reasons were not enough, in Google Analytics AdWords is a great place to get used to the complexity that naturally arises from mixing two data sources. In almost all GA AdWords reports the first cluster of data (pink below) will come from AdWords and the second cluster (green brace) is the normal collection of metrics you see in GA…

adwords plus google analyitcs

This will naturally prod you into trying to understand why are Clicks different from Sessions? After-all it is a click that kicks off a session in GA when the person arrives. It is internalizing these subtle nuances that separate a Reporting Squirrel from an Analysis Ninja.

Above view is from the Campaigns report. I usually start there as it gives me great insights into the overall PPC strategy for the company.

While you are learning from this report, here’s a little smart tip… Click on the Clicks link on top of the graph you see (you’ll see it along with Summary, Site Usage, Goal Set 1, and Ecommerce), you’ll get a different set of metrics you should know intimately as well…

camapign clicks deeper outcomes

The combination of CPC and RPC is very important. It is nice that they are right next to each other in this view.

When you look at Store data I also want you to live-see why ROAS not even remotely a useful metric. It looks alluring. Return On Ad Spend. That sounds so awesome, surely it is in some holy books! No. It is not.

For now, invest in understanding what is is measuring, what the data shows, is that good or bad, and what’s missing. When you already to move to advanced-advanced stage, read this post: Excellent Analytics Tip #24: Obsess About Real Business Profitability

Once I’ve exhausted the value in Campaign reports (drilling-up, drilling-down, drilling-around), it is time to shift into detail. While it might seem that the very next step will be the AdWords Keyword report, it is not. I like going to the Search Query report first.

In AdWords context, Keyword is what you buy from Google. Search Query on the other hand is what people are actually typing into Google when your search ad shows up (triggered by the Keyword of course).

Here are the two reports from the Store account, you can clearly see why I like starting with the Search Query report….

search keywords vs search queires reports

I would much rather learn to anchor on what people are typing and then go into the Keyword view to see what I can learn there. The Search Query performance report helps me re-think my AdGroups, Match Types, bidding strategies and more. It also helps me optimize the landing pages, both from a content they contain and what ads I recommend send traffic there.

You could spend three months in these reports just learning and finessing your PPS savvy, so I’ll leave you to that. 🙂

Bonus: Shopping Campaigns are incredibly successful for most ecommerce properties. Spend time in that report in the AdWords section, drilling-down and segmenting, to learn what makes these campaigns distinct and if you were tasked to identify insights how would you go about it.

6. Develop a Smarter Understanding of Your Audiences

Having grown up on cookies, we have typically have had a finite understanding of our audiences. This has slowly changed over time, most recently with the awesomeness of User-ID override empowering us to understand a person. Still, most of the time we are not great at digging into Audiences, and their associated behavior.

Hence, to assist with your evolution from beginner to advanced, three often hidden areas of Google Analytics for you to explore now that you have access to real data.

Go to Audience > Interests > In-Market Segments.

Here’s the official definition of what you are looking at: Users in these segments are more likely to be ready to purchase products or services in the specified category. These are users lower in the purchase funnel, near the end of the process.

I’ve developed an appreciation of this report as I think of my performance marketing strategies, especially the ones tied to Display advertising. Far too often we rely on just PPC or email and don’t use Display in all of the clever ways possible. This repor, leveraging insights from my users, help me understand how to do smarter Display.

in-market segements google analytics

You can drill down to Age by clicking on the in-market segment you are interested in, and from there for each Age group you can drill-down to gender.

Per normal your goal is to identify the most valuable ones using micro and macro-outcomes for your business.

After I’ve mastered in-market segments by adding near term revenue to my company and helping shift the thinking about Display in my company, I move to leverage the data in the Affinity Categories. Also a report in this section. Affinity categories are great for any display or video advertising strategies you have to build audiences around See Intent (See – Think – Do – Care Business Framework). A bit more advanced from a marketing perspective (you would have had to master strategy #2, attribution, above).

For the second hidden area, go to Audience > User Explorer.

This lovely beast shows something you think you are dying to see. It is also something I really don’t want you to obsess about (except if you are a tech support representative). But you want it. So. Here it is…

user explorer report google analytics

What you are looking at is a report that shows you the behavior of an individual user on your website, as identified by an anonymous Client-ID. You can loosely think of it as a person, though it is more complicated that. If you have implemented User-ID override (congratulations, you deserve a gold star!), then you areas close to a person as you’ll ever be.

Because this is everyone on your website, there is no wrong place to start and a hundred thousand terrible places to waste time. You can literally watch each person! See, what I mean when I say I don’t want you to get obsessed about this?

On the rarest of rare occasions I look at this report, my strategy is to understand the behavior of “Whales”, people who spend loads of money on our website (why!). I sort the above report by Revenue, and then look over the users who form the first few rows. The data, fi you do it in the Store account for the person who’s at the top at the moment, looks like this…

user explorer report google analytics detail

The report is sorted from the last hit (08:16 above) to the first hit (which you don’t see above, the person browsed a lot!). You can quite literally watch the behavior, over just five minutes, that lead to an order of $2,211.38! You surely want to know what this person purchased (Men’s Cotton Shifts FTW!), what pages did they see, where did they come from, how did they go back and forth (this person did) and so on and so forth.

Looking at the top few of these Whales might help know something about a product merchandizing strategy, a unique source, or how to change your influence with your acquisition strategy to get a few more of these people. There will always only be handful of folks.

The higher order bit is that the best analytical strategy is to analyze micro-segments rather than individuals. Small groups with shared attributes. You can action these, at scale. Nothing in your marketing, site content delivery, servicing at the moment has the capacity to react to an individual’s behavior in real time. And if you can, you don’t have enough visitors. Hence, obsess about micro-segments. That is a profitable strategy.

The spirit above is also the reason why I don’t mention real-time reporting in this guide. Simply not worth it. (For more, see #4: A Big Data Imperative: Driving Big Action)

For the third hidden area, ok, not so hidden but to expose all your analytical talent, go to Audience > Mobile > Devices.

With greater than 50% of your site traffic coming from mobile platforms, this audience report obviously deserves a lot of attention (in addition to segmenting every single report for Mobile, Desktop, Tablet).

The problem is that the report actually looks like this…

mobile analytics

It is poorly constructed with repetitive metrics, and an under-appreciation for mobile user behavior (why the emphasis on Do outcomes when Mobile has primarily a See-Think intent clusters?). It makes for poor decision making.

So. Time to practice your custom reporting skills. (Oh, if you as an Analyst only use custom reports, you are closer to being an Analysis Ninja.)

Scroll back to the top of the Mobile Devices report and click on the Customize button. On the subsequent page, pick the metrics you best feel will give you insights into Acquisition, Behavior and Outcomes. While you are at it, you’ll see just one dimension in this report, Mobile Device Info, you can add other drill-down dimensions you might find to be of value. I added Screen Resolution (matters so much) and then Page (to analyze each Page’s performance by resolution).

Here’s what the report’s Summary view looks like for me…

smart mobile analytics

Nice, right? Smarter, tighter, more powerful.

My obsession is with people on mobile devices and not just the visits. Hence Users come first. Then, paying homage to See and Think intent, my focus is on Pages/Session. For the same reason, my choice for success is goals and Per Session Value (ideally I would use Per Session Goal Value, but as you saw in the opening this account does not have Goal Values). I would delete the Revenue, it is there mostly in case your boss harassed you. Delete it later.

Depending on the role, Acquisition, Behavior or Outcomes, I have everything I need to start my mobile analysis journey.

As I recommended with AdWords analysis above, the tabs on top of the report hold more analytical insights for you…

smart mobile analytics site usage

You will discover that you’ll have to go and practice your custom reporting skills on all these tabs as there are sub-optimal elements on all three of them. For example with Site Usage, I added Think intent metrics. For Goals and Ecommerce tabs there are fewer and more focused metrics. Now almost all of the stuff I need to make smarter decisions from my mobile data is in one place.

This exercise requires a lot of introspection and understanding business needs as well as what analysis makes sense. That is how we all move from Reporting Squirrels to Analysis Ninjas! 🙂

As with the above custom report, I’ll email a downloadable link to the Subscribers of my newsletter The Marketing – analytics Intersect. You can contrast your choices with my choice of metrics and dimensions.

Bonus: If you present screenshots from GA to your management team, make sure you take advantage of the option to show two BFF trends. In my case above you can see I choose to pair mobile Sessions with Goal Completions (again to put the stress on See – Think intent).

7. Icing on the Cake: Benchmarking!

One final beginner’s advanced recommendation.

You just finished looking at a whole bunch of mobile metrics. How do you know if the performance of the Google Merchandizing Store is good or bad? Yes, you do see trends of past performance. But, how about with others in your industry? Others who have your type and size of website?

I’ve convinced that most of the time without that competitive / ecosystem context, Analysis Ninjas are making incomplete decisions.

The cool thing is, you can get benchmarking data in Google Analytics.

Audience > Benchmarking > Devices.

And now you have a really strong sense for what is good performance and what is non-good performance…

benchmarketing report device category

You might have come to one set of conclusions doing the analysis in the mobile section above, and I suspect that now you have very different priorities with the lens pulled back to how the ecosystem is doing.

And, that’s the beauty.

There’s a lot more you can do with benchmarking. You can explore the advanced-advanced version here when you are ready: Benchmarking Performance: Your Options, Dos, Don’ts and To-Die-Fors!

I hope you have fun.

That is it. A beginner’s advanced guide that hopefully accelerates your journey to become an Analysis Ninja.

As always, it is your turn now.

Have already gotten access to the Store demo account? What elements recommended above had you not explored yet? Which ones do you find most easy/frustrating to get actionable insights from? Are there strategies that you use as an Analysis Ninja that are not covered above?

Please share your recommendations, frustrations, :), joyous strategies and guidance with all of us via comments below.

Thank you.

Be Real-World Smart: A Beginner’s Advanced Google Analytics Guide is a post from: Occam’s Razor by Avinash Kaushik

Source: Avinash

Ad Block Tracking With Google Analytics: Code, Metrics, Reports

PartialYou don’t use an ad blocker, right? Of course not! You would never want to take away the opportunity a content creator has online to monetize their work via ads.

I know that at least some of you think I’m being sarcastic. I am not, and this post is all about getting the data to show you that I am indeed not being sarcastic.

I am insanely excited that we can track ad blocking behavior in Google Analytics, so easily. This post covers these key elements:

Here’s how this post unfolds…

While you could call on your favorite IT BFF to do this for you, let me encourage you by saying that if I can do this all by myself…. You can do it too! Honestly, it is that easy.

Excited? Let’s go!

1. Ad block: #wth

The reason you might think I was being sarcastic above is that there is such venom in the media (of course the media!) about people who use ad blockers, and an incredible amount of hoopla around how the only reason media is dying is the awful people using ad blockers in their web browsers.

The reality is not quite that cut and dry.

First, plant me firmly in the column of people who believe that using an ad blocker is a personal choice, each person makes the moral decision they are most comfortable with. Second, I believe that the let me make cheap money by spraying and praying some of the most awful intelligent-deficient ads in large numbers is a contributing factors to users wanting to use ad blockers. Third, the profound lack of empathy for the user experience, especially on mobile, is another huge contributing factor.

If you are getting the feeling that I’m holding publishers, large and medium companies with large people, platforms and budgets to do more in this debate, you would be right. I am not excusing the users (see above, and more below).

Let me make this real for you, by looking at two specific examples.

Here’s a tweet by my wonderful friend Mitch Joel.

mitch joel adblocking tweet

Can you blame him for wanting to install an ad blocker?

And, now, whose fault is it? Both the non-intelligent advertiser and the non-intelligent publisher. Neither wants to grow up and consider using the data available for Mitch to be smarter about advertising. Both simply want cheap let me not work all that hard for it money.

Take thi second example from Forbes magazine on mobile… They are absolutely well within their rights to create a firewall around their site for people who use ad blockers…

Forbes Ad-Light

But think about their text in green for a moment.

On a mobile platform should Forbes not have pity on its users and load the unwanted ads as fast as it can? On a mobile device, which we use more often in deeply private (beds) and openly public (subway) situations should they not auto-play videos?

They should. They can block their site, they can ask everyone to pay for content, they can ask people to pay for no-ads. It is their right. But, the above is close to a ransom note from a corporation to exhibit basic human decency.

In all the discussions for inherent awfulness of users of ad blocking solutions, this perspective never gets as much play. After all the people with the ink are the ones with the non-intelligent cheap money seeking existences.

I hope in the discussion of ad blocking, this gets some play. Relevance in advertising is possible, it is even exciting. Consider the See-Think-Do-Care business framework, discern the intent of your audience and ensure that you ad content, ad targeting and ad landing page are aligned with your audience’s intent. You will be rich. They will be happier.

Speaking for me. I simply pay to get rid of advertising wherever I find it is awful (including at my employer, or powered by my employer’s platforms). I love YouTube Red (and get Google Play Music for free!!). I’m happy to pay for Google Contributor. I’m curious to see the evolution of Optimal, a startup working on a similar solution. I actively control my Google Ads (sadly other platforms are not this kind), I spend a lot of time on The New York Times and The New Yorker, pay for both. And, of course I would not be as smart about digital marketing as I am without paying for Baekdal Plus.

You see different models people use to make money there. You can make money with content. You just need to create something incredible of value and want to make intelligent money.

Conversely if your strategy is to not change, not think about the value exchange carefully enough, not innovate, then blocking off access to content of an entire country will still fail. I give you Sweden.

Let me get off my high horse, and let’s get some tracking going!

2. Technical how-to implement enhanced code guidance (Google Tag Manager or direct)

Tracking ad blocking behavior is quite simple.

If you have implemented analytics.js, via the standard recommended approaches, you can use the strategy below to simply update the code on your website manually. The code defines a simple plugin and then requires that plugin, passing it the custom dimension index that you’ll create to capture ad blocking status.

All you need to do is make sure you replace the two bits in the red…

adblock analyticsjs tracking avinash

I don’t trust WordPress to render code cleanly, always mucks something up. Please right click and save this text file: adblock_analyticsjs_tracking_avinash.txt

If you want to see a working example of this, just do View Source in your browser and check out my implementation of the above code. You’ll notice my UA id as well as the fact that I’ve set the dimensionIndex as 1 (which will also be true for you if you are not using Custom Dimensions yet).

So, what’s the code above doing? For security reasons, JavaScript code is not allowed to know what extensions are running on a user’s browser. This means we can’t be 100% sure if the user has an ad blocker installed, but we can make a pretty good guess. The way this code works is it creates an HTML element with the class name “AdSense” and temporarily adds it to the page. If the user has an ad blocker installed, the element will be invisible, so if that’s true after the code inspects the element, then we can be reasonably sure the user has some sort of ad blocker installed.

If you’re using GTM and the Universal Analytics tag, you can configure the tag to set the custom dimension via a user-defined custom JavaScript variable. The following function can be passed as that JavaScript and it will share whether ad block is enabled in the browser…

adblock gtm tracking avinash

Please right click and save this text file for your use: adblock_gtm_tracking_avinash.txt

Honestly, that is all you need to do when it comes to things that touch your site.

Let now go and configure the Google Analytics front-end.

3. Setting Google Analytics front end elements (custom dimensions, segments)

Reporting for the ad blocking behavior of your users won’t automatically show up in Google Analytics. We’ll have to do two things to get set up.

Setup the custom dimension.

You need to have Admin privileges to do this step (if you don’t have it, beg someone for it! :)).

Click on the Admin link in the top navigation.

On the resulting page, in the middle pane, called PROPERTY, you’ll see a link called Custom Definitions (weirdly marked with a Dd), click on it.

Then, click on Custom Dimensions.

Then, the beautiful red button called + New Custom Dimension.

Here’s the configuration…

ads blocked custom dimension

Hit Save, and you are done with this part.

ads blocked custom dimension final

Now you also know where the ZZ value of 1 in {dimensionIndex: ZZ} came from. Above.

Setup an advanced segment.

Go to any report in Google Analytics. On top of the main graph, you’ll see a button called + Add Segment, click on it.

Now, click on the red button named + New Segment.

On the left-side of the create segment window, you’ll see a list of choices, under Advanced click on Conditions.

In the box named Filter, in all likelihood the first button you’ll see will read Ad Content, click on it.

You’ll see a search box, type in Ads (of whatever you named your custom dimension above) and you’ll see a Custom Dimension called Ads Blocked. Click. If your boss prohibits you from searching, you can also scroll to the Custom Dimensions category and choose from there.

The next choice you’ll make is to change Contains to Exactly Matches, and finally in the box just type in 1. And, here’s the end result…

ads blocked advanced segment

With this quick step… you are ready to rock and roll with data.

Before we go further, want to guess how many users of this blog, a self-described tech-savvy audience, use ad blockers?

Do I hear 80%?

Do I hear a 70%?

The answer will surprise you, it surprised me!

4. Five Reports and KPIs that deliver critical insights from ad blocking behavior

One caveat… This blog does not have any advertising on it. My books and my startup have links in the right nav, but most people won’t think of them as pimpy ads as they are both mine and the books are inspired by the content from this blog. Hence, when I analyze the data below I might not find the type of insights between folks who use ad blocker and people who don’t use ad blockers because on this site…. there is no advertising.

I’m going to teach you what types of reports and things to look for once you implement the above code. You are going to find fantastic insights from this analysis (like I do when I do this on sites that have lots of ads). But, you might not necessarily see them in the pictures I’m going to show you below – the pictures are just to teach you.

The very first simplest thing you’ll do is figure out:

Q1. How many Users are blocking ads?

You can go to the first report you see when you log into Google and choose your Ads Blocked advanced segment (from above), and you’ll be in business.

I LOVE custom reports [Five Smart Downloadable Custom Reports ]. I used one of my simpler acquisition custom report, and after I apply the segment, this is what it looks like…

google analytics ad block reporting overview

Roughly 14% is the answer.

I have to admit I was pretty darn shocked. Most of my experience suggested that the minimum would be 50%, and perhaps even as high as 75% because of the attributes of the audience that reads this blog.

So much for experience!

This the the fun part about data. It beats experience / opinion / hot air / gut feelings etc.

Go get your own data. Don’t wait for a newspaper, guru, pontificator-in-chief give you a “best practice.”

Also above, you can see bounce rates (I expect that it will be much more different on your site, remember I have no ads here so it would not really dirve big differences). And, you can see the all important metric of Conversion Rate.

Nice report right? Acquisition, behavior, outcomes!

Q2. What is the difference in content consumption between people who block ads and those that don’t?

Simple. Go to the Behavior folder, click on Overview, and bada bing, bada boom…

ads blocked content consumption

There seems to be slight difference between the time that people stay on the site if they use ad blockers. On your site, if you have loads of ads, I suspect you’ll see a much larger difference.

Also look at the contrasts between Pageviews and Unique Pageviews.

Q3. Given the difference in privacy concerns across countries, is the ads blocking rate materially different across the world?

Go to Audience, Geo, Location…. In the bread crumbs on top of the table in this report, I choose Continent (simply to show you the whole world in a small table in the space I have available here)…

google analytics ads blocked location

As you might have expected, Europe is the highest (but not by all that much). This was really fascinating for me because regardless of if I have ads on my site or note, this data is unaffected by the behavior things I was concerned about above. I would have expected Europe or Germany to have way, way higher than ad blocking then I saw in my blog’s data.

Q4. Money! Do I have higher Per Session Goal Value from people who block ads?

Here’s the theory behind this question: If the users are blocking ads they are having a better experience. And, if they are having a better experience, then it is more likely they deliver more goal value per session.

I created a quick and simple custom report for this (standard Google Analytics reports are so cluttered!).

Here’s the main graph that allows me to reflect on long term trends…

ads blocked acquisition overview

For me at least, I would call it a wash.

Your mileage might wary because you’ll actually have ads.

I consider this metric, Per Session Goal Value, to be critical for publishers and hence likely the best one you can use to measure the various implications on you from people’s use of ad blockers.

Next, you’ll look at the scorecard in the table, it gives you three simple metrics that will give context to PSGV…

ads blocked acquisition scorecard

And, finally of course you’ll look to see if our KPI, PSGV, is influenced by the traffic source…

ads blocked acquisition detail

You can see the obvious differences above, it will give you a peek into the heads of the people coming to your site and it will also help you optimize your ad targeting and ad content strategies for Paid Media and even your Earned Media.

Q5. Do people who use ad blocking technologies end up being more loyal customers?

This is a very intriguing question to ask if you are a publisher. Does the recency and frequency change for people who use ad blockers?

Again, that is based on the hypothesis that if you are using ad blockers then supposedly you are having the best experience on the site, it should make your recency and frequency have a different (better!) profile.

I end up using this data to figure out, if the difference is material, to figure out how to consider monetizing these folks (“$5 for an ad-free experience, and you support us and keep us alive!”).

There are other reports you can look at as well, but the collection of KPIs and reports above help you get pointed in the right direction.

And, that’s a wrap!

As always, it is your turn now.

Do you track ad blocking behavior on your website today? If you use a different coding strategy, would you care to share it with us? How many people use ad blockers website, and what type of site is it? Do you see material differences in how people with ad blockers behave (bounce rates, depth of visit, per session goal value etc.) when compared to people who don’t use ad blockers? Loaded question, do you block ads in your default browser?

Please share your strategies, successes, failures, lessons and advice via comments below.

Thank you.

PS: If you have not signed up for my pithy and insightful newsletter, I would love to have you as a subscriber. Sign up here: The Marketing-Analytics Intersect.

Ad Block Tracking With Google Analytics: Code, Metrics, Reports is a post from: Occam’s Razor by Avinash Kaushik

Source: Avinash

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