Cohort Analysis & Google Analytics: The Basics

In early 2015, Google Analytics quietly rolled out Cohort Analysis reports. If you aren’t a frequent user of GA (or tend to steer clear of beta reports), you may not be familiar with this powerful tool. In a nutshell, cohort analysis reports give you insight into user behavior on a much more granular level than otherwise found within Google Analytics. Are your messages resonating with users over time? At what point do users drop-off and trigger you to re-engage? Cohort analyses can help.

What is cohort analysis?

Think of a cohort like your graduating class (Go Heels!). You all entered college and graduated four years later. The cohort analysis comes into play a year out of school: how many of you have full-time jobs? How many of you worked for a year and then switched jobs? How many went back to graduate school? The answers to these questions may vary based on the year of your graduating class: how was the economy when you graduated? What about the job market? Cohort analysis reports provide this insight into a particular segment of users and their behavior.

Cohort analysis is especially helpful in identifying both micro and macro trends from your web analytics data. How did a new email marketing campaign impact customer sales? Did those users return after three months or just take action as a result of that single campaign? That’s where cohort analysis reports come into play.

Cohort analysis groups users by a similar dimension and measures a particular activity over a set amount of time. Let’s look at an example. Below we’ve grouped users into cohorts by acquisition date (when they first visited the website). The resulting graph, segmented out by month, measures user retention (whether that user returned to the website in subsequent months).

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From this report, we can see that roughly 4% of our visitors returned to the site after one month. It’s interesting to note, however, that of those who visited the site in April, 6% came back to the site in Month 1 (May). Why such an increase in April? What channels drove April users back in Month 1, that didn’t happen in Month 1 for February and March users?

Cohort analysis by channel

To dig deeper into your data, add segments to your cohort analysis report. Below you can see the same data broken out by channel.

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Rather than just looking at the traffic as a whole, we can now see that email is by far the best channel for user retention. Email drove an average of almost 17% of traffic back in Month 1 compared to just 3% that returned as a result of organic search.

From the above metrics, we can deduce that email is the best channel for user retention, but what exactly are those users doing on the site? Are they converting into leads? Did they make an online purchase? How does this match up to the brand’s customer journey?

Cohort analysis & goals 

By changing the metric to goal completions, we can now see which channels are driving the most conversions over time for each cohort of users.

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This is where things get interesting – in the last report, we saw that email drove the most returning visitors. Now we can see that although email is great for user retention, almost twice as many users are converted in Month 1 from organic search (28 conversions from email compared to 65 from organic search).

Cohort analysis & PR

For marketers involved in each stage of the marketing funnel, cohort analyses can be incredibly helpful to show exactly where your users are coming from and what they’re doing over time. For PR professionals, focus your cohort analyses on the various channels you work with most for your clients or brand. As you mix and match segments and timeframes, the data begins to tell a story. What channel helps users get back to your website? Are those customers converting? How can you adjust messaging for returning visitors to get them to convert? All these questions (and more!) can be answered with cohort analysis.

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