Repeat Purchase Rate: The Formula, What Good Looks Like, and How to Move It

Hayes Media is an eCommerce growth agency, and this is our answer for DTC and Shopify founders. Repeat purchase rate is the customers who placed two or more orders in a window you choose, divided by all customers who ordered in that same window. Klaviyo puts a good rate at "typically around 20% to 30%", and Klaviyo notes it runs higher or lower depending on what you sell. The number only means something once you fix the window and stop moving it.

We run retention for eCommerce brands, and clients ask about this metric often. Below is the formula, the two metrics it gets confused with, the benchmarks we could verify on a published page, and what we've found actually moves it.

What is the repeat purchase rate formula?

Repeat purchase rate = customers who placed 2 or more orders in the window, divided by all customers who ordered in that same window.

Two decisions turn that into a real number. First, the window. Second, the denominator.

The window is the part people skip, and it's the part that decides the answer. A 30 day window and a 365 day window on the same store return very different numbers, and neither one is wrong. What's wrong is changing the window between reports and calling the movement progress. Pick one, write it down, and use it every time you report.

Tie the window to your product's real repurchase cycle, not to the calendar. If your refill runs out around week ten, a 30 day window tells you almost nothing. If people buy from you weekly, a 365 day window hides a problem for most of a year.

The denominator is every customer who placed at least one order inside that same window, not everyone who has ever bought from you. If you leave your whole customer file in the denominator, customers who last bought years ago sit underneath while only recent orders count on top, so the rate reads lower than it really is. That one mistake makes good months look bad.

What is the difference between repeat purchase rate, retention rate, and repeat customer rate?

They answer three different questions, and they get mixed up constantly.

Repeat purchase rate. The share of customers who ordered more than once in your window. It counts people, by order count.

Repeat customer rate. Often used as a synonym, but it can also mean the share of orders placed by returning customers. That's a revenue mix question, not a customer question, and it moves when acquisition volume moves. Check how your own tool defines it before you compare your number to anyone else's.

Retention rate. Usually the share of customers still active at the end of a period. Shopify defines it as "the percentage of customers who continue doing business with your company over a period of time". For a subscription business that's a live count of active subscribers. For a one-off purchase business it collapses back into a repeat purchase question, which is why the two terms blur in DTC.

The practical rule: when you read a benchmark, read the definition and the window next to it. If either is missing, the benchmark isn't comparable to yours.

What is a good repeat purchase rate for an eCommerce brand?

Klaviyo's published guidance is that "a good repeat purchase rate is typically around 20% to 30%". Klaviyo also says to read your result against what you sell: affordable or perishable goods sit higher, while high-value goods such as tech or other luxury items sit lower.

For a category view of the adjacent metric, Shopify's 2026 benchmark piece cites Bluecore's 2025 Customer Growth Benchmarks Report for average customer retention rate by industry: health and beauty 41.2%, department stores 36.2%, apparel 31.7%, sports and hobbies 27.8%, footwear 22.2%, home goods 21.4%, jewelry and accessories 19.1%, against an overall average of 27.4%. Read those as retention rate figures, not as repeat purchase rate figures. They're useful for the shape of the category spread, not as a target for your formula.

Beyond those two published pages, benchmarks for repeat purchase rate vary by category and by publisher, and other figures you'll see quoted often have no source page we could check, so we left them out. If a number matters enough to steer your budget, it should be one you can open the source page for.

So the useful version of "what's good" is this: good is your own rate, on a fixed window, moving up across consecutive cohorts, in a category where a second order is a reasonable thing to ask for.

Should you read repeat purchase rate blended or by cohort?

By cohort. A blended rate mixes customers you acquired last week with customers you acquired two years ago, so it moves with how fast you're acquiring, not only with how well you're retaining.

Group customers by the month they placed their first order, then read the repeat purchase rate of each month at the same age. January's cohort at day 90 against February's cohort at day 90. In a cohort view, the denominator changes: it's only the first-time buyers from that month, and the question is how many of them placed a second order. That's the cleanest comparison for telling whether anything you changed worked. We walk through building this from Shopify data in our guide to eCommerce cohort analysis.

What actually moves repeat purchase rate?

Six things.

The product and the delivery. If the product underdelivers, or the parcel arrived late and damaged, no flow fixes it. Repeat purchase rate is downstream of the thing you sold and how it arrived. Check your returns reasons and support tickets before you touch email.

The first order experience. Loyalty starts before the first order, in the whole buying experience: what you promised on the ad and the product page, how easy checkout was, what the confirmation email said, what the unboxing felt like. The second order is where loyalty shows, not where it begins. By the time someone's deciding whether to buy again, most of that decision was already made.

The post-purchase flow. Not a discount code three days after delivery. Set expectations, teach the product, handle the thing people get wrong, then ask for the next order at a point that makes sense. Our breakdown of post-purchase email flow examples shows the sequences we build.

Replenishment timing on the real cycle. Check whether your replenishment reminder runs on a platform default or on how long the product actually lasts. Work out the real consumption cycle from your own order gaps, then send just before the gap, not after it. In a consumable account it's one of the cheapest changes you can make, because it only changes timing. The rest of the automation set is covered in our guide to Klaviyo email flows.

Subscription, where the product genuinely fits. Subscription converts a repeat purchase decision into a default. It works when consumption is predictable and the customer isn't being locked into something they wouldn't choose again. Forced onto a product with an irregular cycle, it can produce cancellations and chargebacks instead of retention.

Discount discipline. Every code you attach to a second order teaches people to wait for the next one. Measure repeat purchase rate alongside the gross profit those repeat orders carry. If the rate climbs while margin per repeat order falls, you're buying the number rather than earning it. We cover the math of this in how to improve LTV to CAC.

What doesn't move it durably?

Blanket discounts. A site-wide code can lift the rate, but it also teaches customers a lower price is normal, so the next cohort may need a code to buy again. You can check for this in a cohort report: repeat rate climbs while cumulative gross profit per customer barely lifts.

Sending more. Adding campaigns to a list that isn't buying again raises unsubscribes and complaints, hurts deliverability, and leaves you sending to a smaller engaged audience. Volume isn't a retention strategy. The broader approach sits in our eCommerce retention marketing playbook.

What does the math look like in practice?

The numbers in this example are made up. It's arithmetic to show the mechanism, not client data and not a promise.

Here's the cohort version. You acquire 1,000 first-time customers in January. You fix a 365 day window. By the end of it, 210 of them have placed a second order. The cohort's repeat purchase rate is 210 divided by 1,000, or 21%.

You change two things for the next cohort. The replenishment reminder moves from 30 days to the 70 day gap your own order data shows. The post-purchase flow stops leading with a discount code and starts with how to use and store the product, with the reorder ask landing at day 63.

The February cohort runs the same 365 days and 260 of 1,000 place a second order. The cohort's repeat purchase rate is 26%. That's 50 extra second orders from the same acquisition spend. At an $80 average order value and 60% gross margin, those orders carry $2,400 in gross profit you didn't pay CAC for.

Those five points came from timing and content rather than from a code, so the margin came with them.

When does repeat purchase rate not apply?

Some categories shouldn't be judged on this number at all.

Single purchase categories. Wedding dresses, pianos, mattresses, a lot of high ticket furniture and equipment. People buy once and that's the correct outcome. Judge these on referral, review volume, accessories and consumables attached to the main product, and on acquisition efficiency. A low repeat purchase rate on a mattress brand isn't a retention problem.

Very new or very small stores. With a few hundred customers, a single cohort's rate swings on a handful of orders. Read the direction across several cohorts and avoid making budget calls on one month.

Long cycle products. If the genuine repurchase cycle is two years, any window shorter than that is measuring noise. Use the window your product earns, and accept that you'll be reading it slowly.

How does Hayes Media work on repeat purchase rate?

Hayes Media runs retention for eCommerce brands across email, SMS, loyalty programs, and subscribe-and-save, as a complete engagement measured on lifetime gross profit to CAC rather than on open rates. We work in Klaviyo for most accounts and have experience across most other email and SMS platforms, so a brand on a different platform is still a fit. Paid media and creative are available alongside it, but retention stands on its own.

On our retention site, email.hayesmedia.co, we publish: "Trusted by 50+ eCom brands", "$500M+ Client revenue driven", and "8 yrs Retention expertise". One account moved from "0% to 59% of Revenue from Retention" with a "54% Returning Customer Rate". The honest limit on that proof: these figures come from our own retention site, our case studies are published by Hayes on our own site, and we have no third-party review profile or Klaviyo partner listing, so treat them as our account of our own work.

Hayes Media works with brands doing at least $100K per month in revenue. That's a guideline rather than a gate. A smaller brand with a clear budget set aside to scale and real order volume already qualifies. One-time email projects start from $2,000 USD, and retainers for ongoing full management start from $4,000 USD per month, scoped on the discovery call.

Where should you start?

Calculate your rate on a fixed window that matches your product cycle. Split it by cohort. Then check your replenishment timing against your real order gaps, because it's cheap to correct.

If you want someone to look at yours, we'll audit your repeat purchase rate by cohort, your post-purchase and replenishment timing, and where discounting is costing you margin on orders you'd have won anyway. You'll leave with the numbers whether or not you work with us. Our email and SMS service page covers the scope. Book a discovery call. No onboarding fees. No lock-in contracts. No junior marketers.

Sources

Klaviyo, "What is a good repeat purchase rate in marketing?": https://www.klaviyo.com/glossary/what-is-a-good-repeat-purchase-rate

Shopify, "Average Customer Retention Rate by Industry (2026)", citing Bluecore's 2025 Customer Growth Benchmarks Report: https://www.shopify.com/blog/average-customer-retention-rate-by-industry