Repeat purchase rate: how to calculate and grow it

How many of the customers who bought from your store last year came back to buy again? If that answer took more than ten seconds, you are in good company. Most online stores can recite yesterday's campaign ROAS and have no idea how many customers have ordered twice.

That matters right now. Black Friday is about to bring in a wave of new customers, many of them drawn by discounts. If the store can't measure how many of them return, it will celebrate November revenue and find out in March that it paid for one-time buyers.

Quick answer: repeat purchase rate is the percentage of customers who placed two or more orders in a given period. To calculate it, divide the number of customers with 2+ orders by the total number of customers who bought in that same period, then multiply by 100. Example: 760 repeat buyers out of 4,000 customers in a year is a 19% repeat purchase rate.

How to calculate repeat purchase rate, step by step

The formula is simple:

Repeat purchase rate = (customers with 2 or more orders in the period ÷ customers who bought in the period) × 100

What breaks the math is the unit. You count customers, not orders. A customer who bought five times counts as one in the numerator, not five. Count orders instead and you get a different metric (purchase frequency), with a number that looks better than reality.

In practice there are four steps:

1. Pick the period. Twelve months is the standard for most stores. Short windows, like a single month, almost always look bad because customers haven't had time to come back.
2. Export orders with a unique customer ID. Email or tax ID, never the name. Remove cancelled and refunded orders.
3. Count orders per customer. In a spreadsheet, a pivot table with the customer ID in rows and order count in values does the job. Then count how many customers have 2 or more.
4. Divide by total unique customers in the same period.

A round-number example: a beauty store had 4,000 unique customers between October 2025 and September 2026. Of those, 760 placed at least two orders. The repeat purchase rate is 760 ÷ 4,000 = 19%.

The cohort version, which is the one you should decide with

The annual rate mixes long-standing customers with people who arrived in August and haven't had time to return. For decisions, the more useful version is by cohort: of the customers who made their first purchase in a given month, how many came back within 90 days?

Example: in March the store gained 1,200 new customers. By the end of June, 168 of them had placed a second order. That cohort's 90-day repeat rate is 14%. Repeat for every month and you can see whether the store is getting better or worse at bringing customers back. If the table looks intimidating, our post on cohort analysis walks through it row by row.

Repeat purchase rate, retention and churn: what's the difference?

These three show up together and get mixed up constantly. The difference is the question each one answers.

Metric	Question it answers	Best fit
Repeat purchase rate	How many customers bought more than once in the period?	Ecommerce and retail without subscriptions
Retention rate	Of the customers at the start of the period, how many are still active at the end?	Businesses with an ongoing relationship
Churn	How many customers stopped buying or cancelled?	Subscriptions and SaaS
Purchase frequency	How many orders did each customer place on average?	A complement to the three above

In ecommerce, repeat rate tends to be the most honest metric, because there is no "cancellation": the customer just disappears. Retention rate works better when there is a defined cycle, and churn only fully makes sense in subscription models.

Why repeat purchases move LTV so much

A store's LTV is, roughly, average order value × orders per customer × margin. Repeat purchase is the middle lever, and usually the cheapest to pull, because you've already paid to acquire the customer.

A simulation: average order value of $36, contribution margin of 40% and an average of 1.25 orders per customer per year. LTV on margin is 36 × 0.40 × 1.25 = $18. If the store pushes the average to 1.40 orders, LTV rises to $20.16, a 12% gain without spending an extra dollar on acquisition. With a $15 CAC, the LTV/CAC ratio goes from 1.2 to 1.34.

It sounds small, but it's exactly the gap between an operation that breaks even and one with room to scale paid media. The full math is in our post on how to calculate LTV.

What is a good repeat purchase rate?

It depends heavily on the category, and any single number is misleading. A study by the agency BS&Co published in February 2026, covering more than 156,000 customers of DTC brands, found an average of 18.8%, ranging from 7.1% to 44.2% across brands. Consumables landed between 22% and 44%, fashion between 10% and 17%, and durable goods between 7% and 18% (BS&Co, 2026).

In Brazil, the most recent read comes from the consumer side. In the E-Consumidor 2026 survey by Nuvemshop and Opinion Box, run with more than a thousand consumers in August and September 2025, 46.5% said they come back to buy on brands' own websites, versus 30% on marketplaces (Nuvemshop and Opinion Box, 2025). That's stated behavior, not order data, but it points to something you see in practice: your own channel is where the relationship gets built.

The most useful benchmark, though, is your own. Compare the 90-day repeat rate of this year's cohorts with last year's. If it's going up, your relationship work is paying off, whatever the industry average says.

When the second purchase happens (and why it shapes the strategy)

The same BS&Co study shows a pattern that changes how you plan: half of repeat purchases happen in the first 30 days, and three out of four within 90 days.

The practical consequence is blunt: if a customer hasn't returned in three months, the odds of coming back on their own drop sharply. Retention effort should be concentrated in that window, not spread across generic newsletters all year. The pattern varies by category, so calculate your own curve from your own orders before setting contact cadences.

How to increase repeat purchase rate before (and after) Black Friday

Raising repeat purchases isn't about sending more emails. It's about getting the timing, the reason and the channel of the second purchase right.

1. Build the second-purchase sequence around the product cycle

Shampoo runs out in 45 days; sneakers last a year. Calculate the median gap between first and second purchase by category and trigger contact a few days before it. A well-timed replenishment reminder converts far better than a generic coupon.

2. Treat Black Friday customers as a separate cohort

Someone who arrived with a 40% discount is a different customer from someone who paid full price. Isolate that cohort and measure its repeat rate at 30, 60 and 90 days. If they only return with a discount, that belongs in the campaign's margin math, not hidden inside an average. Our post on preparing your store for Black Friday with data covers the acquisition side.

3. Give customers a reason to come back to your own channel

In the same Nuvemshop and Opinion Box survey, 60% of consumers said they want stores to offer reward programs. Points or cashback redeemable only on your own site pull the second purchase into the channel with the best margin.

4. Test subscriptions where consumption repeats

In the E-consumidor 2027 edition, released in October 2026, 16% of respondents said they already subscribe to a physical-product club and another 29% said they were interested (Inforchannel, 2026). For coffee, pet food, supplements or cosmetics, a subscription turns repeat purchases into predictable revenue.

5. Fix post-purchase before investing in retention

Late deliveries and painful returns kill the second purchase more than any missing coupon. Cross reviews and support tickets with the list of customers who didn't return. The reason is often right there, in writing.

Common mistakes that distort repeat purchase rate

• Duplicate customers. The same person with two emails becomes two one-time buyers. Use a stable ID whenever possible.
• Exchanges recorded as new orders. They inflate repeat rate, especially in fashion.
• Marketplaces without customer IDs. Marketplace sales often don't carry the end customer. Calculate repeat rate for your own channel only, or split channels.
• Windows that are too short. Comparing one month's repeat rate with another's, without cohorts, mixes customers of different ages and produces false conclusions.

If your data has these issues, read up on data quality before you present the number in a meeting.

Frequently asked questions

What is the repeat purchase rate formula?

Repeat purchase rate = (customers with two or more orders in the period ÷ total customers who bought in the period) × 100. Count unique customers, not orders, and remove cancellations and refunds before calculating.

What is a good repeat purchase rate in ecommerce?

It varies by category. A 2026 study of 156,000 customers of DTC brands found an average of 18.8%, with consumables above 22% and fashion between 10% and 17%. More important than the benchmark is comparing your own cohorts over time.

What's the difference between repeat purchase rate and retention rate?

Repeat rate measures how many customers bought more than once in a period. Retention measures how many customers from the start of the period are still active at the end. For ecommerce without subscriptions, repeat rate is usually easier to calculate and interpret.

How do I calculate repeat purchase rate in Excel?

Export orders with the customer's email or ID, build a pivot table with customers in rows and order count in values. Use COUNTIF to count how many customers have 2 or more orders and divide by the number of rows in the pivot table.

How can I increase repeat purchase rate?

Focus effort on the first 90 days after the first purchase, with contact paced to the product cycle. Loyalty points on your own channel, subscriptions for recurring items and friction-free post-purchase usually do more than generic coupons.

The metric that separates growth from churn

A store that grows only on new customers is renting revenue: it pays for every sale again, every month. Repeat purchase rate is the indicator that shows whether a store is building a customer base or just spinning a revolving door. After Black Friday, it will tell you whether November's spend brought in customers or just orders.

The catch is that calculating it properly means crossing orders, channels and cohorts, and almost nobody has time to rebuild that spreadsheet every week. With Sherlok, you connect your store, CRM and spreadsheets and ask in plain language, for example "what was the 90-day repeat rate of last Black Friday's customers?", and get the analysis ready.