Retention (also referred to as “retention rate” or “RR”) is one of any product’s most vital metrics. Good retention means users keep coming back. People use your product again and again because they find sufficient value in it for accomplishing their jobs-to-be-done.
In this article, we will look closely at retention and see why it’s so essential for your product and business.
→ Test your product management and data skills with this free Growth Skills Assessment Test.
→ Learn data-driven product management in Simulator by GoPractice.
→ Learn growth and realize the maximum potential of your product in Product Growth Simulator.
→ Learn to apply generative AI to create products and automate processes in Generative AI for Product Managers – Mini Simulator.
→ Learn AI/ML through practice by completing four projects around the most common AI problems in AI/ML Simulator for Product Managers.
Contents
- Defining retention
- Quick example of how to calculate retention for a mobile app
- Formula for calculating retention
- Daily, weekly, monthly, and quarterly retention
- How retention reflects the product’s value for the user
- How to know a “good” retention rate and make useful comparisons
- Relationship between long-term retention and product/market fit
- How to improve retention
- When long-term retention fails to fully reflect product value
- Further reading on retention
Defining retention
Retention is the metric that answers the question: How many people returned on Day X/Week X/Month X after trying the product for the first time? Retention is expressed as a percentage, indicating the share of people who used the product at Time X out of all the people who had used it previously.
Example of how to calculate retention for a mobile app
Whenever we talk about retention, we have to decide which day we want to use as our starting point. Here’s a simplified example.
Let’s imagine that on August 26, our (fictional) mobile app SuperApp had 1,300 new users try it out. This day, Day 0, will be our point of reference. In the context of retention, Day 0 refers to the day on which a user tries the product for the first time.
For determining how many SuperApp users came back to the app later, a product manager has two main options available:
- A product analytics system that receives events when users perform certain actions. Examples of these systems include Amplitude and Mixpanel.
- A SQL query to the database that stores information about all user actions and in-app events.
After reviewing data about the cohort of 1,300 users who come to the product on August 26, the product manager generates the following table. This table is used to calculate retention and build a graph.
| Day | Day 0 | Day 1 | Day 2 | Day 3 | Day 4 | Day 5 | Day 6 | Day 7 |
| Users | 1300 | 950 | 700 | 600 | 550 | 520 | 510 | 505 |
| Retention | 100% | 73% | 53% | 46% | 42% | 40% | 39% | 38% |
This tells the product manager that Day 7 Retention equals 38%, for example. So 38% of the users who opened the app for the first time on August 26 returned to the app seven days later.
For an example of how this would look in an Amplitude table and graph, check out the developer’s documentation.
Below we will explore how to interpret retention and the important insights it can offer. But we should start with a rock-solid understanding of how to calculate retention in the first place.
