Why Does Knowing Your User Retention Rate Matter?

Retention metrics reveal a lot about the quality of user experience and whether you are meeting product goals.

Note: This article covers general information on how to calculate retention, not necessarily supported by Mixpanel. For information on Mixpanel’s Retention report, please visit the help center.

How many customers continue using your app, product or service is what’s known as retention. It’s a key performance indicator (KPI) that indicates how well you are meeting user needs and whether you are providing a good customer experience. Retention is particularly important given that it costs five times more to win over a new customer compared to retaining an existing one, and repeat customers tend to spend more. Even small improvements in retention rate can have a big impact on profitability and sustainability. 

Analytics is needed to give you the metrics for measuring customer retention, but there are a few other pieces of information that need to be defined before you can start calculating.

Retention is a behavioral metric. It’s based on the actions a user takes. Before retention rate can be calculated, you must first define what user behavior is being measured. Someone who simply visits your website may not signal retention, and even people who fill out forms may not fit into the category of user. It can be as broad as purchasing any product or more granular, such as using a specific feature. It may also help to define user cohorts that can be used to calculate retention.

Give the timeframe for measuring retention careful consideration. When choosing a timeframe consider the natural frequency of use. The ideal timeframe will vary from business to business depending on factors like seasonality and the product offering. 

According to a U.S. News and World Report Study, American businesses lose 15% of their customers annually. Are you doing better or worse than average? Calculating user retention will help you find the answer.

There are a number of formulas that measure user retention in different ways:

Calculating user retention rate with the range formula is fairly straightforward. You’ll need to decide on the time range (either number of days or dates) and what kind of user you’re tracking. To get the retention rate users at the end of the timeframe are divided by the number of users at the start of the timeframe. That number is then multiplied by 100 to get the percentage.

The number of users at the end of the specified timeframe

÷

The number of users at the beginning of the timeframe

X

100

EXAMPLE:

Retention of users who had basic membership at a gym from August 1st to August 31st.

475 basic gym members on August 31st

÷

500 basic gym members on August 1st

X

100

In this example the retention rate is 95%. In order to get an accurate number, new users are not included. The userbase for calculating retention is strictly those who were members at the start of the timeframe.

Use this formula if you have a tiered product or service in which users can upgrade to a higher level. It helps to determine how pleased users are and what prompts an upsell. To calculate upgrade retention rate:

Number of users who upgraded during a specified timeframe

÷

Total number of users

X

100

EXAMPLE:

18 basic gym members upgraded to premium membership

÷

600  Total number of basic and premium members

X

100

In this example the upgrade retention rate is 3%.

Here you are gauging customer retention, however the time range is segmented into brackets. Typically Day 0 is the first bracket and establishes the baseline number of users. The next bracket could be Days 1-7, and the second bracket could be Days 8-14.

EXAMPLE:

On Day 0, there were 20 users that signed up for an app.

On Days 1-7, 15 of those original users signed into the app again for a 75% retention rate.

On Days 8-14, 10 of those original users signed into the app again for a 50% retention rate.

This is a more in-depth retention rate measurement that can reveal customer behavior. The formula can then be used to confirm user behavior patterns and the brackets should be adjusted for future retention rate measurements. For instance, you may find for a grocery delivery app customers order groceries once every 10 days on average. To gauge retention over a longer period of time more accurately, the brackets can be set at 1-10 days, 11-20 days, 21-30 days and so on. 

This retention rate formula, sometimes referred to as classic retention, is very basic and more specific than the bracket formula. It tells you the percentage of users that perform a task on a certain day. It’s common for the N day retention formula to use Day 7 as the benchmark, but any day can be used.

EXAMPLE:

On Day 0, 25 customers sign up for a meal prep planner. 

On Day 7, 15 of those customers created or adjusted their meal prep plan. 

On Day 10, 12 of the original customers created or adjusted their meal prep plan.

You can add additional days to track retention and user behavior over a longer range of time. It’s also worth noting that each day is calculated independently, which means the customers who carried out the specified task on Day 7 could be all the same or completely different than the people who were counted on Day 10.

The rolling retention rate formula includes customers that return on a specified day or any day after. Basically, customers that perform a certain action on or after a certain day are considered retained, and more importantly, they are retained over the long-term. It’s a simple measurement that doesn’t require much comparison and it doesn’t matter how many times a user performed an action so long as it happened on or after the selected day. To calculate rolling retention rate:

# of customers on or after the specified date

÷

# of customers on Day 0

X

100

It’s essentially just calculating the date of first use and last use. The formula doesn’t provide insight on frequency of use or behavior patterns.

Knowing your retention rates can tell you where you’re falling short, which features keep customers coming back, how loyal customers are, and if you’re on track with meeting customer needs and expectations. The calculation formula that’s most appropriate depends on your analytics goal. Ideally, your analytics platform should be capable of a wide range of retention calculations that deliver actionable data that can inform business decisions aimed at maintaining users and in turn increasing revenue.