Customer Retention Rate Formula for Retail Loyalty Programs
09/10/2026
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If you search for the customer retention rate formula, you will find the same answer almost everywhere. It works well for subscriptions, where every customer either renews or cancels. Retail is different. A shopper who stops visiting your store never tells you they have left. They simply stop buying.
That is why the formula needs one extra decision before you use it: who counts as a customer in each period. Get that rule right, and the calculation takes minutes. Get it wrong, and your retention rate can look healthy while customers drift away.
Retention is worth measuring carefully. As Harvard Business Review reports, research by Frederick Reichheld of Bain & Company found that increasing customer retention rates by 5% increases profits by 25% to 95%.
This guide walks through the formula step by step, using one retail example from start to finish.
What is the customer retention rate formula?
Customer retention rate is the percentage of customers you had at the start of a period who are still customers at the end of it. The standard formula, as explained in Salesforce’s guide to customer retention rate, is:
Customer retention rate = ((E − N) / S) × 100
Here is what each letter means:
- S is the number of customers at the start of the period.
- E is the number of customers at the end of the period.
- N is the number of new customers gained during the period.
The key idea is the subtraction. E includes everyone you have at the end, including new people. Taking away N leaves only the original customers who stayed. Dividing by S then tells you what share of your starting group you kept.
How to calculate customer retention rate for retail, step by step
We will use one example throughout: a fashion and lifestyle retailer that sells in stores, online and through an app, and runs a points-based loyalty program.
Step 1. Define an active customer
In a subscription business, a customer is anyone with an active plan. In retail, you have to create that rule yourself.
The simplest and most common rule is this: an active customer is someone who made at least one purchase in the period. Under this rule, a shopper who bought in January but not again until July is not counted in the spring quarter.
Write the rule down and keep it the same every time you report. Changing it later, even slightly, makes old and new numbers impossible to compare.
Step 2. Choose the period
The period should match how often your customers normally buy. If it is too short, many loyal customers will look lost simply because they have not needed to shop yet.
- A grocery or coffee chain might measure monthly.
- A fashion or beauty retailer might measure quarterly.
- A furniture or electronics retailer might measure yearly.
Our example retailer measures quarterly, comparing Q1 with Q2.
Step 3. Count S, E and N
Now count three groups from your sales data:
- S: customers who bought in Q1. In our example, 20,000.
- E: customers who bought in Q2. In our example, 21,500.
- N: customers who bought in Q2 but not in Q1. In our example, 6,500.
Two details matter here. First, N includes both brand-new shoppers and lapsed customers who came back. It is worth splitting these. If 1,200 of the 6,500 had bought from you before, that is your reactivation number, and it is useful in its own right.
Second, each shopper needs one ID across every channel. If a customer buys in store with a phone number and online with an email address, they may appear as two people. SupremeTech saw this problem in a project for a Japanese luxury jewelry retailer, where two sales channels had separate customer databases and different point logic. The team built a custom Shopify app and unified point system so loyalty data from online and in-store purchases was processed together.
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Step 4. Calculate retention and churn
Put the numbers into the formula:
Retention rate = ((21,500 − 6,500) / 20,000) × 100 = 75%
So 15,000 of the 20,000 Q1 customers bought again in Q2.
Churn rate is the opposite of retention:
Churn rate = 100% − 75% = 25%
In plain words, 5,000 customers who shopped in Q1 did not shop in Q2. Some may come back later, which is why tracking reactivation helps.
Step 5. Add repeat customer rate
Repeat customer rate answers a different question. Instead of asking “did they come back next period?”, it asks “how many customers bought more than once within this period?”
Repeat customer rate = (customers with two or more purchases in the period / all active customers in the period) × 100
If 8,600 of the 21,500 Q2 customers made two or more purchases, the repeat customer rate is:
(8,600 / 21,500) × 100 = 40%
This metric is useful for brands with short buying cycles, where several visits in one period are normal.
Retention rate vs repeat customer rate vs churn rate
These three retail retention metrics are related, but each one answers its own question.
| Metric | Question it answers | Formula | Example result |
| Customer retention rate | Did last period’s customers buy again this period? | ((E − N) / S) × 100 | 75% |
| Churn rate | How many of last period’s customers did not return? | 100% − retention rate | 25% |
| Repeat customer rate | How many customers bought more than once this period? | Customers with 2+ purchases / active customers × 100 | 40% |
A good habit is to report retention and repeat customer rate side by side. A brand can keep most customers while each one visits less often, and only the second metric will show that.
How to measure retention for a loyalty program
To see how your loyalty program relates to retention, run the same calculation twice: once for members and once for non-members.
In our example, 8,000 of the 20,000 Q1 customers were loyalty members. Of those members, 6,800 bought again in Q2. Of the 12,000 non-members, 8,200 bought again.
- Member retention: (6,800 / 8,000) × 100 = 85%
- Non-member retention: (8,200 / 12,000) × 100 = 68%
A 17-point gap looks like strong proof that the program works. Be careful here. Customers who already shop often are more likely to join a loyalty program in the first place. A study of Dutch grocery shoppers in the International Journal of Research in Marketing (Leenheer et al., 2007) found that loyalty programs had a small but positive effect on share of wallet, and that ignoring this self-selection overstated the effect by about seven times.
To get a fairer view, compare members’ retention before and after they joined, or use a holdout group that does not receive a specific offer.
Read more:
Common mistakes in customer retention calculation
A few errors cause most wrong retention numbers:
- Counting new customers as retained. Always subtract N.
- Using a period shorter than the buying cycle. This makes normal gaps look like churn.
- Duplicate customer records. One shopper with two IDs looks like one lost customer and one new one.
- Reading one overall rate only. Retention often rises the longer a group stays with you, because the least committed customers leave first. Research by Fader and colleagues (2018) shows that this rise usually comes from differences between customers, not from each customer becoming more loyal. Tracking retention by the month or quarter customers first bought gives a clearer picture.
Once retention is measured reliably, you can build on it with metrics such as customer lifetime value and churn prediction.
Read more:
Conclusion
The customer retention rate formula itself is simple: ((E − N) / S) × 100. What makes it accurate in retail is the setup around it: a clear rule for an active customer, a period that fits your buying cycle, and one ID for each shopper across every channel. Add repeat customer rate and a member versus non-member view, and you have a retention report your team can trust.
If your customer data is split across store, online and app systems, SupremeTech’s Omnichannel Retail Solutions can help connect it so your retention numbers reflect real shoppers.
Frequently Asked Questions
Customer retention rate = ((E − N) / S) × 100, where S is customers at the start of the period, E is customers at the end, and N is new customers gained during the period.
First define an active customer, usually someone who bought at least once in the period. Then count customers who bought in the previous period (S), this period (E), and those who bought this period but not last (N), and apply the formula.
Retention rate shows how many of last period’s customers bought again this period. Repeat customer rate shows how many customers bought more than once within the same period.
Churn rate is 100% minus retention rate. If retention is 75%, churn is 25%.
There is no single benchmark, because it depends on the category and the period you measure. Compare your own rate over time, by customer group, and for members versus non-members rather than against a general figure.
