What?
Cohort analysis is a subset of behavioral analytics that takes the data from a given platform (e.g. eCommerce site, web app, game etc’) and rather than looking at all users as one unit, it breaks them into related groups for analysis. These related groups (=cohorts), usually share common characteristics or experiences within a defined time-span.
See it in action
In the charts below you can see a popular cohort analysis: It groups customers based on the date when they made their first purchase. Studying the spending trends of cohorts from different periods in time can indicate if the quality of the average customer being acquired is increasing or decreasing in over time. You can also see if your marketing efforts at the time made a difference. In the case below, we can see during 2013 (the circles) it was a slow start, but after a new campaign, that took the first two weeks of March, things got better. As for 2014 (the triangles), we had a good start, but between March and May, there was no growth, later during May major improvements in the product boost the spending to a new record.
Use cases
By now, we got the point that cohort analysis helps you understand the behavior of component groups of users apart from your user population as a whole. So let’s see what are some common use cases:
- Examine individual cohorts to gauge response to short-term marketing efforts like single-day email campaigns. If you run marketing campaigns on specific days, see how effective they are are generating loyal users, and compare which campaign performed best.
- Users’ value base on their acquired dates — See how the behavior and performance of individual groups of users change day to day, week to week, and month to month, relative to when you acquired those users. Think on metrics like User Retention or Revenue.
So remember, the way to look at a cohort is as a group of people who share a common characteristic over a certain period of time.
Good luck!
Originally published on Ido Green
