Measuring Retention

If you care about growth then you should care about retention.

Retention is the number of people who continue to use your product.

Without retention, all you have is a leaky bucket.

You can pour as much time and money into marketing as you like, but no retention means zero long-term users. The long-term growth of a product and the overall health of a business depends on how well you retain your users.

If you don’t show people the real value of your product early and often, it will die.

Even the best products lose the majority of their users in a few days. Amplitude wrote an amazing book called Mastering Retention and in it, they estimate 80% of new users stop using the average app three days after downloading it.

If you make retention your primary growth metric, you can change the trajectory of your company from one that loses users over time, to one that sustains true growth.

The most common way to track retention is by plotting a retention curve.

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This line graph shows you the average percentage of people that come back and use your app after they sign up.

To construct a retention curve, you must define what “using your app” means. One way to measure relevant use is by focusing on a single critical event. Your critical event is the thing you want people to do for them to count as truly active. It must align with the change your product seeks to make.

Next, you must determine your product usage interval. This is how often you expect users to come back to your product. In the retention curve above, the x-axis is measured in days. Based on the kind of product you have, you could measure this weekly, monthly, quarterly, etc.

Once you’re tracking your critical event and you have a usage interval you can construct your retention curve.

There are a few different types of retention curves but we’re going to focus on unbounded retention since its the easiest to understand.

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This graph shows 38% of the people who signed up to your app came back on or after 2 days.

Put another way, measuring the inverse of your unbounded retention, tells you how many people used your product and then never came back. In this case, 62% of your users tried your app once and then disappeared.

One of the problems with a retention curve like this is that it lumps together a lot of different types of people in a single curve. In order to make meaningful improvements, you need to understand people as they flow through different stages of retention. But that’s a topic for a different post.


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