How do you define “analysis” to assess a Web site’s performance?
That question was a key topic at the recent eMetrics Marketing Optimization Summit in San Jose, CA.
Jim Sterne, conference chairman, did a great job of pulling together solid content covering a number of industry trends. He organized a day called the Analytics Symposium and asked a handful of people to prepare short presentations (10 minutes max) on what they felt “analysis” meant with regard to analyzing site performance. After a few people presented, attendees discussed the presentations, what resonated mainly with them, what else they would like to hear about, and more.
He asked me to be a presenter, giving me a great reason to pull some of our agency’s 40-plus Web analytics professionals together to discuss what analysis meant to them. It was a great opportunity to step back and visit what analysis means, why so many companies struggle with analysis, and why so many fail within Web analytics in general.
If you’ve read the book I co-authored or the columns I’ve written over the past few years, you may have heard me state ad nauseam that the ROI (define) on Web analytics is 0.0 if you aren’t taking action on the insight generated from the data. And far too many companies are investing considerably in tools and simply reporting the data — not doing the analysis that drives insight and change! That’s what analysis is all about: moving from data to insight to action.
Chris Kerns, who runs the Web analytics team at my agency, asked the team to provide their description of analysis in one or two sentences. Below are some of those responses that resonated with me and I shared at eMetrics (I’ve highlighted some keywords that jumped out at me):
- Analysis takes you from data to a decision and action based on business goals.
- Provide recommendations based on multiple factors that include data — making your decisions smarter!
- Analysis to me means using data online and off- to inform and educate meaningful, accountable, and optimizable insights, which in turn help drive actions to provide our clients with the greatest value for their money.
- I believe successful analysis means evolving from simply reporting on the behavior of customers to guiding how to the change the behavior. (To do this you need more than just analytics; you need user experience, creative, optimization, etc.)
- Analysis within our space is the art and science of identifying trends and placing them in context so that meaningful insights can be made and actionable next steps identified.
In addition, Kerns asked his team to put together a list of the top 10 terms they use to describe analysis. We analyzed them and found some of the most popular used terms were:
This covers a lot of different things but touches on the most important aspects of what analysis means, what it means to be successful, and, critically, how to deliver that ROI (greater than 0.0) that most companies are still searching for in Web analytics.
There were many other great ideas and comments that came from other presenters, as well as in follow-up discussions. They include:
- Predictive models can only predict predictable behavior.
- Your opinions, though interesting, are irrelevant. [I loved this one and is a great reminder of the importance of testing ideas rather than just going with gut feelings.]
- People make better decisions when they are not emotionally attached to the decision.
- Don’t be myopic about online. [This is a common problem in Web analytics: people not only focus just on online but also only on behavioral data versus other valuable data around the Web channel.]
- Analysis is a continuous process — something true today may not be tomorrow. [Too often people forget this; they move on after analysis and don’t visit it again.]
- Do outside research to provide relative performance.
In the next part of this column, I’ll go deeper into what analysis is and what it is not, which should help expose why so many companies fail to reach the potential Web analytics offers. I’ll also cover the most important five things to do to transition from lack of analysis to true insight and action to improve the Web channel.
Share with me: What do you think of when you think of “analysis”? What am I missing in my descriptions that you consider important without your organization?
Marketers create personas to better understand their target audience and what it looks like. If marketers can understand potential buyer behaviors, and where they spend their time online, then content can be targeted more effectively.
What’s behind a successful data-driven marketing strategy?
One of the major challenges in the martech industry is getting the attention of prospects in a world where they are bombarded by content and emails on all sides.
Facebook is addressing one of the biggest missing pieces of its chatbot offering: analytics.