Jul 19, 2026 · 8 min read
Repeat Purchase Rate: The Customer-Level Formula Most Brands Get Wrong
First-hand guidance from the Daymark team on analytics workflows, growth reporting, and the operational metrics teams use to make decisions.
Two brands both do $200,000 a month. One acquires 4,000 fresh customers every month and watches almost all of them vanish. The other acquires 1,200 and the rest of the revenue comes from people buying again. On the surface the top line is identical. Underneath, the second brand is a machine and the first is a treadmill. Repeat purchase rate is the metric that separates them, and it is the number that decides whether your acquisition spend compounds or just replaces churn.
There is one trap that quietly corrupts this metric for most brands: counting orders instead of customers. Get that wrong and the number you report has nothing to do with loyalty.
Below: the customer-level formula and the order-level trap, a worked example, benchmarks by category, the ~27% Shopify baseline in context, and how repeat rate connects to LTV and retention.
Repeat purchase rate in one sentence
Repeat purchase rate is the percentage of your customers who have placed more than one order, calculated as customers with 2 or more orders divided by total customers. It is a customer-level measure of whether people come back, and it is the earliest, cleanest signal of retention you have, long before you can compute a reliable lifetime value.
The customer-level vs order-level trap
Here is the mistake that makes the metric meaningless. There are two things you could divide, and only one of them measures loyalty:
- Customer-level (correct): of all your customers, what share placed a second order? This tells you whether people come back.
- Order-level (a different metric entirely): of all your orders, what share were placed by returning customers? This is really a repeat order share, and it is inflated by your best customers.
They give wildly different answers. Imagine 100 customers. Ninety bought once. Ten are superfans who bought ten times each.
Customer-level repeat rate = 10 returning customers / 100 = 10%
Order-level repeat share = 190 repeat orders / 280 total orders = 68%
Same brand, same customers. The customer-level number (10%) says almost nobody comes back. The order-level number (68%) says most of your volume is repeat business. Both are "true," but only the customer-level figure answers "do customers return?" The order-level figure is dominated by a tiny group of heavy buyers and will make a fragile, one-and-done brand look loyal.
The formula and a worked example
Repeat Purchase Rate (%) = Customers with 2+ orders / Total customers × 100
Take a store's full customer base over a defined window:
| Metric | Count |
|---|---|
| Total unique customers | 8,000 |
| Customers with exactly 1 order | 5,840 |
| Customers with 2+ orders | 2,160 |
Repeat Purchase Rate = 2,160 / 8,000 × 100 = 27%
Twenty-seven percent of this store's customers came back for at least a second order. The remaining 73% bought once and, so far, have not returned. Note the window matters: measured over a customer's entire history the rate is higher than measured over a single quarter, because a "one-time" customer this quarter may reorder next quarter. Always state the window.
Benchmarks by category
Repeat rate is driven almost entirely by how often a category is naturally consumed. Consumables get reordered; durables do not. Rough directional ranges on a customer-level basis:
| Category | Typical repeat rate | Why |
|---|---|---|
| Consumables (coffee, supplements, skincare refills) | 40–60%+ | Product runs out; reorder is built in |
| Food & beverage | 30–50% | Frequent, habitual consumption |
| Beauty & cosmetics | 25–40% | Replenishment plus discovery |
| Apparel | 20–35% | Repeat driven by brand affinity, not need |
| Electronics & durables | 5–15% | Long replacement cycles; little to reorder |
| Furniture & big-ticket | Under 10% | Bought rarely by nature |
A supplements brand at 25% has a retention problem; a furniture brand at 25% is doing extraordinarily well. The category sets the ceiling, so benchmark against your own vertical.
The ~27% Shopify baseline, in context
A widely cited figure is that the average Shopify store sees roughly a 27–28% repeat customer rate. Treat it as directional, not a target. It is a blended average across every category, store size, and age on the platform, which means it lumps consumables brands running at 55% together with furniture brands at 8%. Your relevant benchmark is your category and your cohort maturity, not a platform-wide mean. Use the 27% number to sanity-check that you are in a plausible range, then throw it away and compare to peers who sell what you sell.
How repeat purchase rate feeds LTV and retention
Repeat rate is the leading indicator that everything downstream depends on:
- Lifetime value is essentially repeat rate multiplied by average order value and margin, extended over time. A brand cannot have high LTV and a low repeat rate; the two move together by definition. If you want to forecast LTV before you have years of data, repeat rate is the fastest proxy.
- Customer churn rate is the mirror image: a low repeat rate is a high churn rate wearing different clothes. Watching repeat rate by cohort is often a cleaner early-warning system than churn, because you see the second-order signal months before a cohort's churn stabilizes.
- Customer acquisition cost only makes economic sense against repeat behavior. If customers never come back, you must recover your entire CAC on the first order, which for most brands is impossible at a profit. Repeat purchases are what let you acquire at a first-order loss and win over the customer's lifetime.
The strategic point: raising repeat rate is usually cheaper than lowering CAC. A five-point improvement in repeat rate compounds into LTV across your entire base, while a five-point cut in CAC only helps the customers you acquire next.
When repeat purchase rate misleads
- The window drives the number. A short window undercounts repeat customers who simply have not reordered yet; a lifetime window overcounts by giving everyone maximum time. Compare like windows only.
- New-customer surges deflate it. A big acquisition month floods the base with one-time buyers, mechanically dropping the blended rate even if loyalty is unchanged. Read it by cohort, not blended.
- It says nothing about value. A customer who reorders a $12 item is counted the same as one who reorders a $200 order. Pair repeat rate with AOV and margin.
- Order-basis contamination. As above, quoting the order-share version overstates loyalty. Keep it customer-level.
Frequently asked questions
How do you calculate repeat purchase rate?
Divide the number of customers who have placed 2 or more orders by your total number of customers, then multiply by 100. It is a customer-level metric: count customers, not orders. If 2,160 of 8,000 customers have ordered more than once, the repeat purchase rate is 27%.
What is the difference between customer-level and order-level repeat rate?
Customer-level divides returning customers by total customers and measures whether people come back. Order-level divides repeat orders by total orders and measures what share of your volume is repeat business. The order-level version is inflated by a small number of heavy buyers and can read several times higher, so use customer-level to gauge loyalty.
What is a good repeat purchase rate?
It is category-dependent. Consumables like coffee and supplements often run 40-60%+; food and beverage 30-50%; apparel 20-35%; durables and furniture under 15%. Benchmark against your own vertical, because the natural reorder frequency of the product sets the ceiling.
Is 27% a good repeat purchase rate?
The ~27% figure is the blended average across all Shopify stores, so it is directional, not a target. It mixes high-repeat consumables brands with low-repeat furniture brands. Use it only to check you are in a plausible range, then compare to peers in your category, where a good number could be 50% or 10%.
How does repeat purchase rate relate to LTV?
Lifetime value is essentially repeat rate multiplied by average order value and margin over time, so the two move together by definition. A high repeat rate is the fastest proxy for LTV when you do not yet have years of purchase history, and improving repeat rate raises LTV across your entire customer base.
Why did my repeat purchase rate drop after a big sales month?
A large acquisition or promotional month floods your base with first-time buyers who have not had a chance to reorder yet, which mechanically lowers the blended rate even when underlying loyalty is unchanged. Read repeat rate by cohort rather than blended to avoid this distortion.
How is repeat purchase rate different from repeat customer rate?
They are usually the same metric under different names: the share of customers who have purchased more than once. Confusion arises only when someone quotes an order-based 'repeat rate,' which measures repeat orders as a share of all orders and is a different, higher number. Confirm whether a figure is customer-based or order-based before comparing.
Summary
Repeat purchase rate is the earliest honest read on retention: the share of customers who came back for a second order, counted at the customer level, not the order level. The order-level version is a superfan-inflated impostor that makes fragile brands look loyal, so always divide customers with 2+ orders by total customers. Benchmark against your category rather than the ~27% Shopify blended average, and treat repeat rate as the leading indicator that drives LTV, mirrors churn, and determines whether your acquisition spend compounds. Raising it is usually the cheapest growth lever you have.
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