If the idea of cohorts in marketing feels familiar, it is. It's been around for a long time — I even explained cohort analysis in Google Analytics back in 2015. The application for cohort analysis has grown among marketers, and Google had to keep up, particularly with the recent redesign of Google Analytics, GA4. Enter the updated cohort analysis in GA4.
A cohort is a group of people, things or events that share statistical factor — like age, class and time periods. In marketing, cohorts are meant to identify a demographic.
One of the reasons cohorts are vital to advanced marketing is because of the capability they give to sort the traffic arriving to your website and the type of traffic your content and marketing ads create. Reviewing general visitor metrics like returning visitors can provide a broad overview of traffic type.
But an aggregate view conceals segments that may be consistently converting, and thus are worth further engagement. The statistical means in cohort analysis yields a clearer signal of a trend.
A good cohort can help a marketing team identify which types of customers are responding to campaign tactics. You can look at an aggregate of visits and tell if a particular portion of people are more likely to download a white paper or watch a video.
Thus cohorts can be a useful tool to focus campaign budgets to the activity (or activities) that will likely yield more results.
Accessing Cohorts Analysis in GA4
The cohort analysis in Google Analytics was originally a stand-alone beta report created from four parameters: cohort type, size, metrics and date range. With GA4, analysts have gained more flexibility in how the data is selected. This leads to more presentation options to fit the analyst's needs.
To access the cohort, you select "Analysis" in the main menu of your Google Analytics profile. You would next select "Cohorts," which takes you to the analytics hub. Analytics hub is a new feature in GA4 that consolidates many of the stand-alone reports into selection menus. The selection menu displays the choices for dimensions, metrics and associated features.
Once in the hub, analysts can enter two condition settings that act as bookends for setting the cohort type. "Configuration" establishes the condition in which visits to a website or app are included in a cohort. A second setting, "return," establishes a second criteria in which visits to a website or app are considered part of a cohort. Both settings include selections for first touch (the date on which a customers arrives on a site or app), any transaction on the site or app, and any conversion from that transaction.
The cohort size is controlled with cohort granularity. The user can define the initial and returned cohort period of time by day, week or month. There is also a breakdown feature that further divides subgroups based on a selected dimension. Values determine the metrics to be displayed.
Related Article: What Marketers Need to Know About Google Analytics 4
Google Adds 3 New Cohort Calculation Capabilities
Three new cohost calculations join the standard cohort module of Google Analytics 4.
Standard calculation lets you identify the cohort users that return in each specific period. Standard calculation is similar to the cohort report I mentioned in the previous Google Analytics version. It displays a standard cohort chart with weeks along the top horizontal axis and aggregate users by cohort dates along the vertical axis.
Then there is rolling calculation. A rolling calculation lets you identify users who return in every period after being included in the cohort.
Google offers an example. The standard calculation for the example image below indicates 35 users were acquired on Nov. 23 and they also returned to your site three days later. If you switch to a rolling calculation, you would see a different number, six, indicating these users came back every day from Nov. 23 to Nov. 26. In other words, they had exposure to your site on a rolling basis.
The second new selection, cumulative calculation, allows you to gather a specified metric for users who have returned in any period after being included in the cohort. So using our example, this setting displays a sum for a metric like spend for the users who came back over that three day period.
Finally there is a per cohort size metric calculation. It displays the results relative to the size of each cohort, allowing for an easy behavior comparison of cohorts of different sizes.
Once everything is selected, analysts can monitor how user behavior changes over time by examining the cohorts with varying dates according to campaign influences.
Understanding the Limitations of Cohort Analysis
There are limits in the cohort analysis, however. Google Analytics can show a maximum of 60 cohorts, which should be sufficient for many digital campaigns, but the limit can be a hindrance if you have complex cohort inputs. In addition, when applying a breakdown dimension to a cohort, only the top 15 values of that dimension are shown.
Cohorts isolate data to guide you to where your marketing is having the greatest impact. The new cohort analysis features in Google Analytics 4 provide more nuanced guidance to the activity customers find valuable on your website or in your app.