Retention Analysis Overview

Retention Analysis is a powerful feature that allows you to analyze user behavior over a specified period of time, for any number of cohorts and segments. That way, you can begin to identify factors that contribute to retention, test the impact of product changes, and make data-driven decisions that improve the user experience and drive product growth.

Each analysis consists of a certain number of cohorts and buckets, which enables a more granular view of user behavior. To help you gain a better understanding of this analysis, let’s answer a few basic questions and explore some common use cases.

To learn how to set the parameters for this analysis, see How to run a cohort retention analysis.

What is retention?

Retention means that a user has performed a particular event or group of events that have been pre-defined in the Loops platform – indicating that the user has been “retained”.

At its most basic level, this analysis shows the retention rate for each cohort (or segment) during the time period of each bucket in your analysis.

Take note that within Loops, retention has no regard to past engagement. So, for example, if a user was active during Week 5, but wasn’t active during Week 3, they’ll still be considered as retained during Week 5. (For this reason, it is also known as “bounded retention”.)

What is a cohort?

The best way to examine retention over time is through the use of cohorts. A cohort is a group of users who share a common characteristic or experience, and can be studied as a unit over a period of time. In Loops, cohorts are defined on the basis of a particular reference date, such as when they joined your product or service (this is an example of a Starting Point).

Each cohort may have a daily, weekly or monthly time range. For example, say you want to define cohorts on a weekly basis; in this case, you may have a cohort of users who joined your product between June 5 and 11, 2023.

What is a bucket?

A “bucket” is the time period during which user engagement is measured. Specifically, it measures the rate of retention of all cohort members during that period. It may be defined on a daily, weekly, monthly or custom basis.

Among Loops users, a common practice is to use weekly buckets. Let’s say you defined joining your product as the Starting Point of your analysis. In such a case, the “Week 0” bucket would measure a cohort’s retention within their first week of joining your product, “Week 1” would measure the cohort’s second week of engagement, and so on.

Common use cases

Loop’s retention analysis can help you understand and drive greater engagement with your product or services. For example, you can:

• Identify stable retention rates and where they occur, thus indicating successful areas of your product.
• Identify cohorts and user segments that are most likely to continue using your product long-term.
• Identify where engagement is more likely to drop off, and at what point in the user lifecycle, so you can strategize retention initiatives.

To give you a better idea of the insights you can gain, here are some examples of product/business questions you could answer through retention analysis: