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March 5, 2015

Google Analytics Cohort Analysis; Overview and Offline Conversion Tracking

You may have noticed the new Cohort Analysis report in Google Analytics recently. Most of our clients have access to the new feature, but it looks like Google is still rolling it out to all users. We always get excited for shiny new charts, but this one could have a much bigger impact on your reporting and Google Analytics’ overall reporting power.

Google Analytics Cohort Analysis

So what is cohort analysis? It’s not just a report that Google invented. It’s been used in marketing analytics for a while as a way to look beyond sessions and conversions, which can sometimes be one-dimensional, and see trends in how a user interacts overtime. The standard, textbook definition you’ll commonly read is: the behavior of a group of users defined by a common attribute and represented by a common metric.

So what can we do with that? The cohort analysis report defaults to user retention (metric) by day (size). Right now the only “Cohort Type” is “Acquisition Date,” which is a fancy way of saying the date of the first visit. This chart and graph show the percentage of users who return to your site one day after the acquisition date, two days after, three days after, etc., etc. This can be a very valuable report if your website is heavily content driven. How many people are coming back for new blog posts, webinars and white papers? You can change the metric to see how session duration and pages per session change with visits over time. This version of the report also makes a lot of sense if you’re a SaaS provider, tracking an app or generally provide a web-based solution. How many people come back, reengage and continue using the service? You can filter these users by specific channels or content types (using advanced segments) to get a measure of where your best customers originate.

But there are also some pretty interesting ways you can use the tool to uncover new info on your conversion funnel.

Shed light on offline conversions

We work with a non-ecommerce site that uses a free sample request as a primary call to action. Users get the sample and then go to a dealer to make the final purchase. Because most of the resulting steps happen offline, it’s difficult to tell which users are purchasing and which drop out after receiving a sample. This is where cohort analysis comes in. We can filter our cohorts by converters (by adding an advanced segment) to see when and how often these converters come back to the site and reengage. In other words, this can tell us how long it takes a user to research and narrow their consideration set.

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We found found large clusters of users returning to the site after three to five weeks. It may seem like a long time, but the product is a relatively significant and expensive B2B purchase with multiple SKU options and several internal and external audiences who consult in the final decision. When you add all these factors to the shipping time, it’s not unreasonable to assume it takes roughly a month to narrow a consideration set or make a decision.

Cohort analysis alone is not the solution. We need to combine this info with other Google Analytics reports to tell the whole story, but it uncovers part of an ongoing mystery about our offline conversions. Now, we can take a deeper look at how converters come back to the site, what pages they view and what indicates they’re moving closer to purchase. More importantly, this can inform other parts of our marketing. We can find the best time to email users who requested samples or adapt our remarketing program to ensure we’re displaying the right message (based on pages users view when they return) at the right time (when they return). We can even redesign sample packaging to provide more relevant information when the package arrives, shortening the overall time to purchase.

What does this say about Google Analytics?

When Google made the switch to Universal Analytics, we knew the user-based approach would have a lot of benefits. Cohort analysis is one of the first reports to lean heavily on the tool’s ability to accurately track users. As the tool moves out of beta, we hope to see more cohort types and other user-based reports. So be on the lookout for new reports and tools!

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