Repeat purchase rate measures the percentage of your customers who come back and buy from you more than once. The formula is straightforward: divide the number of customers who made more than one purchase by your total number of customers, then multiply by 100. The real work is choosing the right time window and pulling clean data, which is where most people get tripped up.
The Formula
Repeat purchase rate uses two numbers:
- Numerator: The number of customers who made more than one purchase during your chosen time period.
- Denominator: The total number of unique customers during that same period.
Written out: (Number of Repeat Customers / Total Number of Customers) × 100
If you had 5,000 unique customers last quarter and 1,200 of them placed two or more orders, your repeat purchase rate is (1,200 / 5,000) × 100 = 24%.
A few details matter here. Count customers, not orders. If one person placed five orders, that person counts once in the numerator and once in the denominator. You’re measuring how many people came back, not how many total transactions occurred. Also make sure you’re working with unique customer identifiers (email addresses, account IDs) rather than names, which can duplicate or vary across orders.
Choosing the Right Time Window
The formula only works when you define “during what period.” A 30-day window, a quarter, and a full year will each give you different numbers for the same business. The right window depends on how often someone would naturally reorder your type of product.
If you sell consumables like supplements or skincare, customers might reorder every four to eight weeks, so a 90-day window captures a realistic repurchase cycle. If you sell furniture or electronics, a 90-day window will look artificially low because nobody needs a new couch every quarter. For those categories, a 12-month or even 18-month window makes more sense.
A good starting point: look at the median time between first and second purchase for customers who do come back. If that gap is around 45 days, a 90-day measurement window gives returning customers enough time to show up in your data. If you set the window too short, you’ll undercount repeat buyers. Too long, and the metric becomes sluggish and slow to reflect changes you’re making to your marketing or product.
Whichever period you pick, keep it consistent. Comparing a 90-day rate from Q1 against a 365-day rate from last year tells you nothing useful.
A Worked Example
Say you run an online store selling pet supplies and you want to calculate your repeat purchase rate for the first quarter of the year. You pull your order data and find 8,200 unique customers placed at least one order between January 1 and March 31. Of those, 2,460 placed two or more orders during that same window.
Repeat purchase rate = (2,460 / 8,200) × 100 = 30%
That means roughly three out of every ten customers who bought from you in Q1 came back for at least one more purchase. If your Q4 rate was 26%, you can investigate what drove the improvement, whether that was a loyalty program launch, better email follow-ups, or seasonal buying patterns.
Where Your Data Comes From
If you’re on an e-commerce platform like Shopify, this metric is often available in your analytics dashboard under loyalty or customer retention reports. The platform counts customers who made more than one purchase and divides by total customers over the period you select. If you see the number labeled “returning customer rate,” it’s typically the same calculation.
If you’re calculating manually, export your order history to a spreadsheet. Create a column that counts orders per unique customer ID. Anyone with a count of two or more is a repeat customer. Divide that group by the total number of unique customer IDs. Multiply by 100.
One thing to watch: refunds and canceled orders. If a customer placed two orders but returned one, counting them as a repeat buyer inflates your rate. Filter out fully refunded or canceled transactions before running the calculation. Partially refunded orders are usually fine to keep, since the customer still received and kept a product.
Industry Benchmarks
Knowing your number is only useful if you know whether it’s good. Repeat purchase rates typically fall between 20% and 40% for e-commerce businesses, with significant variation by product category. Fashion and apparel brands average roughly 25% to 26%. Beauty and cosmetics brands land around 26%. Health and supplement brands tend to run a bit higher, near 29%, likely because consumable products create a natural reorder cycle.
If your rate sits below 20%, it often signals that your product doesn’t encourage repeat buying, your post-purchase communication is weak, or your customer experience has friction points that discourage a second order. Rates above 30% generally indicate strong product-market fit and effective retention efforts.
Repeat Purchase Rate vs. Retention Rate
These two metrics sound similar but measure different things. Repeat purchase rate tells you the share of all customers who bought more than once. It’s a snapshot of purchasing frequency within a defined period.
Retention rate tracks whether customers from a specific starting point (say, everyone who first purchased in January) are still buying in subsequent months. It’s a cohort-based measure, meaning you follow one group of customers over time and watch how many remain active month by month.
Think of repeat purchase rate as a measure of volume (how many people come back at all) and retention rate as a measure of frequency over a longer timeline (how quickly customers drop off after their first purchase). Repeat purchase rate is more common in e-commerce and retail because purchase cycles are short and variable. Retention rate is more practical in subscription-based businesses or SaaS, where contracts and recurring billing make long-term tracking more meaningful.
Both metrics are useful, but they answer different questions. If you want to know “what percentage of my customers are one-and-done buyers,” repeat purchase rate gives you that answer directly.
Using the Metric to Improve Your Business
Calculating repeat purchase rate once gives you a baseline. Tracking it over time tells you whether your retention efforts are working. Here are the levers that typically move the number:
- Post-purchase email sequences: A well-timed follow-up email, sent when a customer is likely running low on a product or ready for a complementary item, directly targets the gap between first and second purchase.
- Loyalty or rewards programs: Giving customers a reason to consolidate purchases with you rather than shopping around increases the likelihood of a second and third order.
- Subscription options: For consumable products, offering auto-replenishment at a small discount converts one-time buyers into recurring customers almost automatically.
- Product quality and experience: No amount of marketing overcomes a disappointing first order. If your repeat purchase rate is low, survey customers who didn’t return before assuming the fix is better emails.
Track the metric monthly or quarterly, and segment it by acquisition channel. You may find that customers from organic search have a 32% repeat purchase rate while customers from paid social sit at 18%. That difference tells you which channels bring buyers who actually stick around, which should influence how you allocate your marketing budget.