Overview

Retention Analysis allows you to measure how often users are successfully returning to a page or action. By tracking user retention over time, you can gain insights into overall user satisfaction.

User retention is measured within a given cohort of users that you define. A cohort is a group of users who participate in an initial event, such as clicking a link. A user in the cohort is considered retained if they subsequently complete a return event, such as clicking the same link again or clicking a Proceed to Payment button. Only views and actions can act as events.

The retention graph displays the percentage of users who completed the return event each week.

Prerequisites

In order for User Retention data to populate, you must set the usr.id attribute in your SDK. See the instructions for sending unique user attributes.

Build a graph

To build a retention graph, navigate to Digital Experience > Product Analytics > Retention Analysis, which takes you to the User Retention page, then follow the steps below.

1. Define the initial event

1. Select the view or action to act as the initial event for defining a group of users.
2. Optionally, add filters such as the device used or the country of origin.
   • If your initial event is a view, you can add any view facets or context facets.
   • If your initial event is an action, you can add any action facets or context facets.

2. Optionally, define the return event

The return event defaults to a repeat of the original event. To use a different return event:

1. Change Repeated the original event to Experienced a different event.
2. Select the view or action to act as the return event.
3. Optionally, add any desired filter criteria, such as the user’s operating system.

Analyze the graph

For insights on user retention week over week, read each row of the graph horizontally from left to right.

You can click on an individual diagram cell to view a list of users, and export the list as a CSV:

The graph displays slightly different information depending on whether the initial and return events match.

Matching events

If the events match:

• Week 0 is always 100%, since it represents all of the users who completed the initial event.
• The other cells compare the viewers in a given week to Week 0, displaying the percentage of the cohort who completed the event in that week.

Reading the Dec 04 2023 row of the above graph from left to right:

• 94% of the people who completed the event in Week 0 came back and completed it again in Week 1.
• 92% of the people who completed the event in Week 0 came back and completed it again in Week 2.

Differing events

If the events differ:

• Week 0 represents users who completed both the initial and return events.
• After Week 0, each cell displays the percentage of the Users column who completed the return event in that week.

Reading the Dec 04 2023 row of the above graph from left to right:

• 144 users completed the initial event.
• In Week 0, 94% of those 144 users completed the return event.
• In Week 1, 92% of the 144 users completed the return event.

Further reading

Más enlaces, artículos y documentación útiles:

Product AnalyticsDOCUMENTATION