Customer cohort analysis: How it helps in customer retention and new acquisition?

What is Cohort Analysis?

Cohort analysis is a kind of behavioral analytics that breaks the data in a data set into related groups before analysis. These groups, or cohorts, usually share common characteristics or experiences within a defined time-span.

A cohort is a group of people who share a common characteristic over a certain period of time.

An actionable metric is one that ties specific and repeatable actions to observed results [like user registration, or checkout]. The opposite of actionable metrics are vanity metrics (like web hits or number of downloads) which only serve to document the current state of the product but offer no insight into how we got here or what to do next.

Cohort Analysis Example

One way to visualize this information is to chart out a retention curve, showing the retention of these cohorts over time. The chart makes incredibly easy to infer when users are leaving your product.

Cohort analysis can get answers to the questions like:

• When is the best time to re-engage with your users? When is the best time for remarketing?
• What is the rate of acquisition of new users to maintain (if not increase) your app conversion rate?

From the above retention tables, you can conclude that majority of the users who had abandoned the shopping cart did not engage with the app again, not even 1 day after the acquisition date. So, you have less than 24 hours to re-target them with the new offer and increase the chances of getting revenue.

From this data, you can develop a systematic, quantitative approach to know how users can fall in love with your app – and then make it happen again and again. Also, you can make strategies to increase your retention after ascertaining what works and what doesn’t.