Like you, I consume a whole lot of reports every day – company data, public data.
Many are acceptable, some are very good and all the rest leave me extremely frustrated with both the ink and the think.
People make so many obvious mistakes. Sometimes repeatedly.
Just yesterday I was quietly seething because none of visuals included in the report contained any context to understand if the performance I was looking at was good or bad.
The graph could be going up, down, all around and I as a consumer had the job of figuring if something was good, bad or worth ignoring.
The heartbreaking part is that most executives will take a look, realize the difficulty in interpretation in 15 – 20 seconds, and go back to shooting from the gut. Even if the report has hidden gold.
In a move that might not surprise you, I sat down with the person for 90 minutes going visual by visual, table by table, directing changes that would ensure everything had context.
A report usually has a hard time explaining why something is going awry or going really well. (That is why you have job security as an Analyst!)
A report can usually be very good at clearly highlighting what is going well or badly.
Your #1 job is to make sure your reports don’t fail at this straightforward responsibility.
So today a simple collection of tips that you can use to up-level your reports – to allow them to speak with a clear, and influential, voice.
For many of you a reminder of what you might have let slip, for others a set of new things to implement as you aim for your next promotion.
#1. Context, Context,
Today’s post comes from a source of deep pain. Analysis Ninjas are valued less than I would prefer for them to be.
The post is also sourced from a recent edition of my newsletter, The Marketing – Analytics Intersect. I send it once a week, and it contains my insights and recommendations on those two topics. Like this blog, the newsletter is geared towards being instantly actionable (rather than just theory-smart, which is pretty cool too). Do sign up if you want to deliver a small electric shock of simulation to your brain each week.
TMAI #41 covered a graph that resulted from a survey done by Econsultancy and Lynchpin. I received a ton of responses for it, and great discussion ensued. It prompted me to write this post, essentially an expanded version of TMAI #41. I’ve added new insights, recommendations, and two bonus lessons on how to do surveys better and a direct challenge to your company’s current analytics strategy.
If your heart is weak, you can stop reading now. I promise, I won’t mind one bit. I heart you. If you are open to being challenged… then here are the short-stories inside this post…
The World Needs Reporting Squirrels. Wait. What!
Three thoughts that explain the Econsultancy/Lynchpin graph.
Bonus #1: Lessons from Econsultancy/Lynchpin Survey Strategy.
Bonus #2: The Askers-Pukers Business Model.
Let’s go and challenge our collective thinking!
The World Needs Reporting Squirrels. Wait. What!
Some of you know that I created the phrases Reporting Squirrels and Analysis Ninjas to emphasize the difference between those that puke data and those that puke insights with actions attached to them.
Here is my slide the first time I presented the concept in a
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
Analysts, honestly, make the world go round when it comes to any successful business – yes, data is that important. As you might expect from any role, they also make a handful of important mistakes. I’ve written about the biggest mistake web analysts make.
Today’s post is an adjacent mistake: The cardinal sin of spending too much time with data and in reports!The Marketing-Analytics Intersect. Thanks. [/sidebar]
BUT I Want Data-First!
For some in our audience here, it is hard to leave analytics and data behind no matter how desperately I want you to. I understand the pain of trying to let go of years of accumulated comfort from never having to experience your business, and only living through data. I’ve done it.
You can use data as a starting point, if you really want to.
It is possible that the HTC team could have found their heartbreaking Pre-Order page via the fabulous Shopping Behavior Analysis report that is part of the magnificent Enhanced Ecommerce Reporting in Google Analytics.
The above data does not belong to HTC (15% also might be a bit too high!). But, the first column is what we would be looking for. That could trigger a visit to the website to try the user experience.
I do want to caution that not everything broken will be so easy to find, hence I want you to complement your data skills and analysis efforts with just going to the site/app and trying to emulate a normal person (you!).
Another source of starting points, if you insist on using the data, is to leverage the Behavior Flow report that automatically helps you unpack the complexity of the user experience on your website or
An off-topic post this week, to celebrate this incredible outpost you’ve helped create on the web, Occam’s Razor.
This month my beloved blog is ten years old. T. E. N!
It feels more like five. But, I’ve already celebrated the blog being five years old!
I have to admit life has been a tad bit busy lately, and it took a note from a reader to remind me of the birthday. Her note read: “…. and it is pretty impressive that you’ve managed to stay relevant for a decade, it is a very long time in digital years…”
It gave me a pause. I had to go check how long I’ve been at this.
My very first post, audaciously, was titled Traditional Web Analytics is Dead (05/15/06). Given that title, it is amazing that the whole thing has lasted a decade! 🙂
What is frankly shocking is how topical the content seems to be. Five minutes ago, 05/30/06, in my stream I saw a tweet by Christian Bartens referencing a post I’d written on 05/19/06! The 10 / 90 Rule for Magnificent Web Analytics Success.
So today, a little bit of reporting back to you how things have been, a little reflecting my sense of pride on the journey, and an invitation to you to contribute a little story about your experience with my beloved blog. Would you please add it to the comment below? Where are you, how long have you been reading it, what value have you found in it?
The Story In Numbers.
You’ll see in a moment just how much you have been a part of my success, I have actual numbers! 🙂 I’ll share below my journey over the last decade, what
The difference between a Reporting Squirrel and Analysis Ninja? Insights.
As in, the former is in the business of providing data, the latter in the business of understanding the performance implied by the data. That understanding leads to insights about why the performance occurred, which leads to so what we should do.
Do you see how far away a Reporting Squirrel’s job is from that of an Analysis Ninja?
For one, I hope you see the massive investment in self-development of business skills required to have the foundation required to get to the why and, even more, the so what.
Pause. Reflect on the implication of that why and so what on your current skills/career.
I’m sure you came up with a set of actions you can take to evolve from a squirrel to a ninja, or, if you are already a ninja, how to become even more awesome at ninja’ness.
One of the actions that both clusters will come up with is the ability to communicate the insights you discover. Even if you have really amazing why and so what, I’ve observed many Analysts die at the last mile: Presenting their whys and the so whats, in the form of stories.
In fact 86.4% of all Analyst careers fail due to a lack of this critical last mile skill!
Ok, ok. I kid. I kid.
It is really 88%. : )
Tom Fishburne’s wonderful cartoon is here for another purpose.
We send out our multi-tab spreadsheets, our best Google Analytics custom reports, our great dashboards full of data , and more to the tactical layer of data clients. The Directors, the Marketers, the Optimization employees and our resident social media gurus. The valiant hope is that they will
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:
In a recent set of keynotes and consulting engagements in the US, UK and Canada, I’ve had an overwhelming feeling that in very fundamental ways some companies make imprecise choices when it comes to their digital strategy. Not because they don’t have enough money or opportunity or people. But, simply because their broader framing of what the problem was, and what their chosen solution would deliver.
The heartbreaking part of these, often innocently made, choices is any lack of meaningful progress in digitizing their companies. It saddens me deeply that they are not being able to take full advantage of all the new product, marketing, customer relationship opportunities in front of them. Because, I’m sure like you, I’m humbled by the immense opportunity digital presents.
This post covers five of these heartbreaking misses in the broader framing. My hope is that 1. You’ll understand what’s wrong in terms of the strategic choice being made and 2. Get an extremely clear sense for what the right choice is in each case. I’ve suffered enough bruises on the front-lines from trying to re-imagine the current and revolutionize the future across multiple industry verticals, countries, opportunity sizes. Consider this to be a collection of wisdom from those tough lessons – from wins and losses.
Since in almost every case the imprecise framing is strategic, the true consumer of this post is your boss’s boss’s boss. Sadly, we can’t get to them here. But, at least you and I can get on the same page and perhaps I can convince you to take our message to her/him.
Here are the digital myths that are leading us down a profoundly sub-optimal path:
1. Programmatic platforms are a
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