The very best analysts distill, rather than dilute. The very best analysts focus, when most will tend to gather. The very best analysts are display critical thinking, rather than giving into what’s asked. The very best analysts are comfortable operating with ambiguity and incompleteness, while all others chase perfection in implementation / processing / reports. The very best analysts are know what matter’s the most are not the insights from big data but clear actions and compelling business impact from usually a smaller subset of key data.
The very best analysts practice the above principles every day in every dimension of their jobs. It is that practice that I try to discern when I do job interviews. When I see evidence of them 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 them back: What are you trying to get done with your digital strategies?
There is no golden metric for everyone, we are all unique snowflakes! 🙂
That then takes us down the very best way to answer that question, to use the 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
Being 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
You 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…
1. Ad block: #wth
2. Technical how-to implement enhanced code guidance (Google Tag Manager or direct)
3. Setting Google Analytics front end elements (custom dimensions, advanced segments)
4. Five Reports and KPIs that deliver critical insights from ad blocking behavior
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
I want you to sign up for something very, very special I’m doing: Writing short stories from the intersection of marketing and analytics.
My goal is to get you promoted, you are going to love it. So. Please do sign up. But, first, as you’ve come to expect from this blog… Context…
Should you own or rent?
The logic we are taught from when we were babies is that it is better to own than rent. Reality is actually a bit more complicated.
In our context, let’s consider two applications of own and rent.
In the past I’ve spoken about own vs. rent in context of platforms. Facebook, YouTube, LinkedIn are platforms where you rent your existences. Mobile and desktop websites, mobile applications are platforms you own. You own the content, you set your own creativity limits (no 140 characters or videos of only xx resolution), and you own the data on platforms you own.
I’ve also spoken about own vs. rent in context of audiences. You rent audiences on TV, Magazines, Search, Display, etc. You own audiences on your email lists, on forums you host etc.
Audiences and platforms, two places to bring our own and rent lens.
Before we go on, a quick word on the word own. It does feel odd to say you own anyone/thing. Own in this context is like as much ownership as you can apply to a seed you plant in your front yard. You need to protect it, you need to nurture it, you need to champion on its behalf, and you need to be unselfish for a long, long, long time, and maybe some day you get flowers. And, here’s the most amazing thing, if
If you don’t have goals, you are not doing digital analytics. You are doing i am wasting earth’s precious oxygenalytics.
Let’s back up. Let me start with a story.
We were brain storming about the next cluster of coolness for Analytics, the conversation quickly went to what Analysts need to look at on a daily, weekly and monthly basis. I started to outline a simple framework that stated that no one should look at anything daily (that should all be automated and run off automated or custom set thresholds – things don’t really change materially on a daily basis), weekly should be based on stuff that borders reporting squirrel work and pinches of analysis ninja work, and monthly…. well super analysis ninja stuff. And, then I started to redefine what daily, weekly and monthly even means. From there, it is only a hop, skip and jump to the most deadly question in analytics….
What’s the business solving for?
Everything came to a screeching halt. This beautiful daily, weekly, monthly blog post I was drafting in my head to share my excitement with you about thinking analysis differently went poof.
It pains me how critical it is to know what the heck we are solving for with our analytics, and how few people identify goals for their website (mobile or desktop). The reason is simple: If you don’t know where you are going, you’ll get somewhere and you’ll be miserable.
We see this everyday. “Analysts” spewing data out left right and center, after spending so much time tagging and re-tagging and Google Tag Managering. Yet, few Marketers or executives take them seriously (because they don’t know what the heck all that means to the business
For the last decade (#omg!), I’ve consistently complained about a fundamental flaw in Web Analytics tools: They incentivize one night stands, rather than engagements matching customer-intent.
This leads to owners of digital experiences (insanely) expecting all visitors to their websites to convert right away – anything less than that is a failure. Damn the intent the customer is expressing.
It also results in Marketers obsess about awful things like last-click conversions (die last-click attribution die!). They make silly user experience decisions (Searching for car insurance options? We will remove every single thing from the page except a GET QUOTE button. Ha! Sucks to be you Visitor!). They never consider Think or Care intent, all they obsess about is Do intent (See-Think-Do-Care business framework). Not even all of the Do, just the strongest of commercial intent. The very bottom of the Do! It really is quite crazy.
You’ll agree all of this sounds quite insane. Not just insane, so visibly insane that everyone should see through it and fix their minds/reports/strategies. So, why are we still so obviously wrong and still on the insane path?
Simple. It is just how all of the Digital Analytics tools are configured at their very core.
Every standard report in every standard tool is configured off Visits (or in Google Analytics language, Sessions), rather than Visitors (GA language, Users). The specific metric I’ve been mad about since day one of this blog (May 14th, 2006!) is Conversion Rate. It is measured as Orders/Visits. [Or, its variation Outcomes/Sessions]
Built into that is the mental model that if you visit a website, then every Visit has to result in money for the site owner. Else, it is a failed visit. Scroll
Standard reports stink. Custom reports rock!
If you are a regular reader of this blog, you are quite familiar with this sentiment. I’ve expressed it often. 🙂
The primary reason is simple: You are unique. Your business is unique. Why would a report created for everyone work for the special someone that you are?
There are other great reasons as well.
Custom reports allow you to deeply focus (by eliminating the rif-raf metrics and dimensions, they save time and show just what you want). When shared, custom reports allow you to deliver deeper relevance. Custom reports allow you to package up entire datasets for deeper analysis.
I’ve shared a whole bunch of custom reports in the past. You can download them into your Google Analytics account via one click (along with some lovely Advanced Segments and a Dashboard). Just go to the GA Solutions Gallery and click Import: Occam’s Razor Awesomeness.
You can download a bunch more, that are not yet in the bundle above, by following the links at the end of this post. Seven more! The include single custom reports that replace all/most current standard reports in GA on Mobile, Content, Paid Search and Acquisition. Your life will be simpler. Grab the above, then grab the ones at the end of this post.
Today, I want to share a few of my recent favorites that solve day-to-day challenges in clever ways.
But, before we go there I want to share an important concept. Many custom reports are wrong because we mess up the fundamental data model in analytics. We mis-align metrics and dimensions across Users, Session, Hits. If you want to create accurate custom reports (or apply advanced segments), this post is mandatory reading:
The 80/20 rule applies to our use of web analytics tools as well. Most of us use just a small amount of power our tools contain.
This hurts my feelings! Ok, not so much hurts my feelings and more that I’m sad you are not taking advantage of all of the features at your disposal to drive smarter decisions by your leadership teams.
Regardless of the tool you have, it is always prudent to take a fresh look at a familiar tool every once in a while and see what you’ve been missing. I recommend that periodically you gather folks around you for lunch, pull up Adobe Analytics on the big screen in the conference room, let each person expose one hidden report or feature. You’ll be surprised at how much you learn, and, like an Easter egg hunt, the whole thing is fun all by itself.
As many of you already have access to Google Analytics, in this post I want to re-introduce some of the features/reports/concepts that most likely fall outside of the normal 20% you use regularly. My hope is to aid in your persistent quest to deliver more impactful IABIs (Insights, Actions the leadership should take, Business Impact).
Some of these hidden gems are small, some big, some you might know and have ignored, and some never crossed your radar. Pop open your GA account in a different tab, or your WebTrends or your WebTrekk or IBM Analytics accounts, and follow along.
But, first… It is important to point out that some things are a bit hidden and not used as much, like the Real Time reports in Google Analytics but I’m not quite filled with grief about them….
In a Q&A after a keynote a couple of years ago, I was asked: “When will traditional business analysis subsume the web analytics silo?”
My reply: “All business will ultimately be digital, so, if anything, web analytics will subsume business analysis!”
That was a half-cheeky reply. But, if you reflect upon the developments in analytics over the last couple of years it is incredible to see that we, web analytics, have moved so quickly towards the aforementioned outcome.
In fact, even the term digital analytics is too stifling. It is all just business analysis – with digital being a dominant factor in influence (marketing, advertising, experiences, connections, relationships et. al.), digital plus real world owning outcomes (of the commerce type) and some facets of influence.
Business analysis. No digital. No web. No offline. No just this or that silo.
And, 15 years later I get to go back to my first job title after graduating from MBA school. Senior Business Analyst! : )
So, in our world, web analytics, what is helping us embrace to this change? Moving us away from our digital only silo? A little something, that Google Analytics calls, Universal Analytics.
It was announced to the world perhaps 24 months ago – in classic Google fashion, with a bold vision that was not fully baked. Gotta love those betas! The team at Google, thanks to that bold vision, has continued to invest time and people, and execute quickly. Universal analytics has been out, in proper fully baked production release, for a little while. It has exciting new features, an exciting cluster of new analyses you can do, and a lot that was impossible before. It allows you to be a full-blooded Business
Half-way through this post, you’ll seriously wonder why you’ve spent so much time obsessing with Adobe/Google Analytics/Chartbeat or other web analytics tool. When you are done reading the post, you’ll be super mad that your marketing strategy is not more influenced by your competitor’s data!
Such is the power of being able to proactively identify which of your competitor’s strategies are working well, where their current customers come from, and what specific tactics you should experiment with to create and advantage for yourself.
Regular readers of the blog know of my deep love for competitive intelligence analysis. My first blog post on the topic of CIA was on 14th Aug 2006! Competitive Intelligence Analysis: Why, What & How to Choose. CIA also formed one of five foundational elements in my best-selling book Web Analytics 2.0.
Since then, as luck would have it, we have more tools, they are smarter, and have richer data-sets.
In this post we’ll go back to the wondrous world of competitive intelligence analysis. We’ll look at an incredible cluster of examples, from the simple to the sublime, that will help you learn practical strategies you can immediately go back and apply in your role as a Marketer, Analyst, or the Boss of all Things Digital.
Here are the key elements we will explore in our quest to become CI Analysis Ninjas:
+ Foundational Concepts/Caveats
How is competitive intelligence data collected?
Competitive intelligence data will never match your site’s analytics tool
Competitive intelligence tools will never match each other!
Small sites are out-of-luck
Small countries are out-of-luck
Site-centric CI vs. Ecosystem-centric CI
Tools used in this post
+ Traffic Trends Key Metrics Analysis
+ Visitor/Audience Type Profile Analysis