Data Analytics

Repurchase vs. Retention Rate: How to measure and why these metrics are essential for DTC brands

Customer retention is a key metric to define your customer retention strategy. 

Acquiring customers is expensive, so once you have them, you want to retain them and see how they’re impacting your  lifetime customer value and profitability. Depending on your business there are two metrics to look at to give you a glimpse on our customer loyalty - Retention Rate and Repurchase Rate.

What is Customer Retention Rate answering?

The Customer Retention Rate answers the question: how many of your customers are you retaining over time?

The first month is always 100% retention. It’s the amount of people you acquired that month, so these are obviously retained. But after each calendar month, how many customers came back and made yet another purchase? If they came in month 4, Peel considers them not churned in month 1, 2, 3. So the numbers go up to the left as time goes on if people from that cohort come back and repurchase. 

Peel looks at the percentage of customers retained after # of months. As you look to the right horizontally, you’ll see the retention rate across each month. It is a number that changes as each month goes by because you are still retaining or churning people as time goes on. The percentages go down only when customers stop purchasing in the future.

Note: The higher retention, the stronger the business because it means that more people are coming back and purchasing more. 

Check out Peel’s demo to see the Retention Rate metric in action. 

What is Customer Repurchase Rate answering?

How many of your customers are making subsequent purchases 2, 3, 4, 5, 10 more times? This is answering the question; out of customers who originally purchased in each month, how many made another purchase? And when?

It will show you the number or the percentage of customers, per cohort, who made a subsequent purchase, and after which month. The metric is cumulative, so the percentage only increases, but you can see the increase month over month. As time goes on, the repurchase rate of the later months(the right-most columns) should increase or plateau as customers of each cohort have had more time to make new purchases.

In the example below 1.87% of your customers from the May 2020 cohort come back and purchased again within the first month. You can toggle to see what the repurchase rate is for 3+, 4+, 5+ repurchases. 

There is something that you are doing that is enticing 148 people from the May 2020 cohort to come and purchase again in the month of May, and then a month later in June - 3054 people have come back since their original purchase and purchased again - 38.64%. 

Are you sending follow up emails/sms to encourage a repurchase?

Does your product lend itself to multiple purchases during a specific time window?

If you create experiments and test the following month to try to improve those numbers you can then see how those experiments fared. As you can see for the June 2020 cohort, you have a 41.67% repurchase rate by the 2nd month, which is higher than your May 2020 cohort and in subsequent cohorts. Why is that? Did you try something different?

Check out Peel’s demo to see the Repurchase metric in action. 


Knowing which cohorts buy your products frequently and/or have a better retention rate is the key to defining your retention marketing plan while detecting weak elements. Thinking about what you can do to increase that repurchase rate and improve retention are the experiments that you should try often to see the numbers on these metrics change. From creating a customer loyalty program to sending SMS messages at different intervals, to trying new email campaigns, or product recommendations for upsell/cross sell opportunities, this all might increase the repurchase rate and retention for future cohorts. 


Like all of Peel’s metrics you can segment the repurchase rate or retention rate cohort metrics by over 20 segment values - products, vendors, SKU’s, discount codes, locations, non subscriber or subscriber, etc. Doing this can help you determine the success of using a specific discount on a campaign, or whether a specific product in your offering intiaties better loyalty and repurchase. Thinking about the segment values of your business and looking at the analysis can help you better plan for growth opportunities. 

For example:

Does a vendor that we promoted in an email campaign have a better repurchase rate in subsequent months for that cohort?

Does an initial purchase of a product have a stronger retention and/or repurchase rate then other products - is then the one to lead all first purchase promotions with?

Knowing the ways to look at your data through the lens of your segment values can help you use your segment values to your advantage through different applications so you can measure growth.

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