- The blog is back! Had some technical issues
As a practitioner of Web Analytics and Optimization, I’ve spent a fair amount of the last seven years of my career focused on tracking and improving Conversion Rates.This is a noble pursuit for any business, but intense focus on the conversion rate metric can have negative implications – people in your organization (or your clients) may obsess about changes in conversion rate, pester you about them, and even blame you for them!
To avoid this risk and/or annoyance, it helps to have simple, educational “sound bites” for stakeholders explaining why they are maybe/possibly freaking out for no good reason. This is NOT to say that you shouldn’t diligently investigate what you believe to be causes for concern to your business or client, however. Strike a balance, as in all things.
Let’s say someone in your company comes to you with some data about a change in conversion rate. That is a good thing (coming to you with data), right? So, first off, don’t brush them off. Encourage data-driven behavior, even when it might be off-base!
They’re concerned because in a week-over-week report, conversion rate has dropped by 25%. That’s usually a bad thing, so it’s worth some respectful, diligent investigation. Assuming you’ve looked at various data points, and are of the opinion that it’s not a cause for immediate concern, here’s how you might frame the conversation as it continues.
Hi, [Stakeholder], thanks for bringing this to my attention. I’ve dug into the data, looking at YoY behavior, key segments, etc. and I recommend we take a “wait and see” approach. I’m attaching a trended report, so you can see beyond the week-over-week view.
The Stakeholder will almost inevitably ask some follow-up questions about why conversion rate is down. While you will likely have some data points and explanation of your own, here are 9 of my favorite reminders of why your conversion rate may fluctuate from time to time, instead of the constant “up and to the right” trend that we all strive for: Continue reading
I want to discuss a framework that’s new to me, but not that new: It’s called the Data > Information > Knowledge > Wisdom Hierarchy, or the “DIKW Pyramid.”
I was turned on to it very recently, but it’s been around since at least 1982. It, or variants of it, have been used in fields as diverse as Information Science, Engineering, and Geography.
Different academics in different fields of study seem to disagree about how useful or smart the framework is, but I’ve been thinking about DIKW in terms of Web Analytics and Optimization (natch). And, it’s working just fine for me! 🙂
This framework helps explain the kinds of work I’ve been focused on for the last 10 years or so in Digital Marketing. Kindly allow me to explain…
A lunchtime topic came up today regarding Web Analysts and Conversion Optimization specialists. We started debating what each job was all about, what the similarities were, what the differences were, and whether you could be good at both.
Before I dive into my own thoughts and observations on this topic, let me try to answer a crucial question:
Why should I read this post? What’s in it for me?
Fair enough. I respect your time, so IMO you should read this post if:
We good? Onward! Continue reading
On December 6 of last year, I presented a session at the BestPractices conference in Seattle, WA. BestPractices is a conference and webinar series presented by Analytics Pros and focused on, you guessed it, “best practices” around digital analytics and optimization.
The session was titled “Building a Successful Optimization Program” and the slides have been posted for public consumption.
I will be presenting a follow up webinar, “Testing & Optimization: A Deeper Look” on Wednesday, January 16th at 10am PST. Seats are still available, so feel free to put your name on the list here »
We all know that Optimization and testing efforts should be “data driven.” Quantitative and qualitative data should lead you to the problems that testing attempts to solve for your prospects.
But how, exactly, should quantitative web analytics data be used to power your Optimization efforts? How does analysis differ when you’re looking for insights and testing opportunities? Great questions, if I do say so myself 😉
I’m going to answer both in this post as I lay out a basic framework for how to “do” web analytics in the context of Optimization. I compare web data analysis to looking with different “lenses” at the same set of data depending on the context. For example, if I’m doing analysis on “site performance,” I would take a different view of the data than if I were doing “campaign analysis” or “content performance analysis.”
It’s the same for Optimization. You look at the same data as always, but you look through a different, contextual “lens” to suit your needs. Continue reading
As we all know, there is now more web data, and more web analytics reports, than there are hours in the day. One could literally do nothing but stare at web analytics reports all day every day. Unfortunately, that approach would be well beyond the point of diminishing returns.
The fact is that web analysts aren’t paid to stare at web analytics reports all day. They’re paid to provide data-driven insights to drive the business. In the absence of insights, they are paid to ask thought-provoking questions that have the potential to become marketing insights.
Given the scarcity of time to come up with insights and the overabundance of reports, I believe it’s important to have your own “short list” of super-powerful reports or analyses that can quickly give you insights or things to talk about with your marketing colleagues.
I’m going to share one of mine with you. It consistently either a) gives me insights about the prospects of a given website or b) gets my mind buzzing with questions that can be further investigated. Continue reading
Is social media a big part of your online marketing strategy? Is it a huge “question mark” in your strategy? Either way, you can benefit from spending some time with some new social reports recently added to Google Analytics. Continue reading