Understanding retention metrics

What are retention metrics?

Retention metrics measure how well a business retains its users or customers over time. These metrics provide insights into customer loyalty, engagement, and the overall health of your business. Key retention metrics include Return On retention, Return On or After retention, and Return On (Custom) retention.

Key types of retention metrics

What is Return On retention?

Return On retention measures how many customers return to your app on a particular day. This metric is ideal for businesses aiming to build daily habits among users. For example, tracking how many users return on Day 1, Day 2, or Day 7 after their initial interaction. To gain deeper insights, you can use a Retention Chart to visualize the data, monitor long-term user engagement, and understand user behavior over time.

What is Return On or After retention?

Return On or After retention tracks the percentage of customers who return on a specific day or any time after that day. This metric suits products not requiring daily engagement, like grocery delivery services. It helps understand long-term user engagement. Utilizing tools such as a Retention Graph can help visualize the rate at which users disengage over time, and identify cohort-specific behaviors.

What is Return On (Custom) retention?

Return On (Custom) retention allows defining custom timeframes and intervals for measuring retention. This flexibility tailors the analysis to specific usage patterns and business goals. It’s perfect for businesses with unique user engagement timelines. You can create and customize these metrics using Retention Table (Triangle Chart) for detailed analysis. Additionally, you can explore different ID types to match your specific business needs.

Examples of retention metrics in action

• Gaming apps: A mobile game might use Return On retention to monitor how many players return on Day 1, Day 7, and Day 30. This shows the game's ability to engage users daily. It helps identify patterns in user engagement. Learn more about retention charts, long-term user engagement tracking, and understanding retention patterns.

• Subscription services: A news publisher could use Return On or After retention to track how many subscribers return to read articles on Day 7 or any day after their subscription starts. This measures long-term engagement. It highlights content that keeps readers coming back. Check out retention graphs, stickiness of specific features, and cohort analysis.

• E-commerce platforms: An online retailer might use Return On (Custom) retention to observe user engagement over specific intervals, like Day 0-3, Day 4-10, and Day 11-30. This helps pinpoint critical periods for user retention. It aids in optimizing marketing efforts. Explore sub-population analysis, customizing DAU definitions, and retention metrics.