Repeat Purchase Rate
Repeat Purchase Rate is the share of customers who come back for a second order — the cleanest early proxy for LTV and product-market fit in online retail.
Repeat Purchase Rate
The percentage of customers who place a second order within a defined window — the cleanest early proxy for retention strength.
Repeat Purchase Rate (RPR) is the share of all customers who return to buy at least a second time, usually measured within a 90-day or 365-day window. It strips retention down to a single yes/no question per customer, which makes it the fastest signal you have before lifetime value matures.
For an online store, RPR is the metric that tells you whether you sell a product or a habit. A 30-40% rate signals genuine product-market fit and a working retention motion. Below 20% and you're effectively running a paid-acquisition treadmill — every euro of growth has to come from a new customer.
RPR sits in the family of ecommerce metrics that measure retention health alongside customer lifetime value, churn rate, and purchase frequency. It's the earliest of these to stabilise — you get a usable read within a single quarter of order data, long before LTV cohorts mature.
The window matters. A 90-day RPR rewards fast-consumable categories like beauty and supplements; a 365-day RPR is fairer to considered purchases like apparel or home goods. Pick one window, document it, and don't quietly change it between board decks.
RPR = (Customers with 2+ orders / Total unique customers) × 100
C₂₊
Repeat customers
Unique customers who placed two or more orders in the measurement window.
Cₜ
Total customers
All unique customers who placed at least one order in the same window.
A Shopify apparel store reviews the trailing 12 months: 18,400 unique customers ordered, and 4,232 of them placed at least one additional order in the same window.
Repeat customers (C₂₊): 4,232
Total customers (Cₜ): 18,400
→ 23.0%
At 23%, the brand is above the one-shot danger zone but well short of the 35-40% you'd expect from a category-leading apparel store with strong email/SMS flows. The retention motion — not acquisition — is the binding constraint on growth.
Healthy RPR varies sharply by category. Replenishable goods compound faster than considered purchases, so benchmark against your vertical — not against a blended cross-industry average that flatters or punishes you for the wrong reasons.
Typical 12-month Repeat Purchase Rate by vertical
| Vertical | Weak (<P25) | Median | Strong (>P75) |
|---|---|---|---|
| Beauty & skincare | 18% | 32% | 48% |
| Supplements & wellness | 22% | 40% | 58% |
| Apparel & accessories | 15% | 27% | 40% |
| Home & decor | 10% | 20% | 32% |
| Food & beverage (DTC) | 25% | 42% | 60% |
| Consumer electronics | 8% | 15% | 25% |
If your RPR is stuck below the median for your vertical, the diagnosis usually lives in one of three places: the post-purchase experience (slow shipping, confusing returns), the second-order trigger (no replenishment reminder, no cross-sell flow), or the product itself (a one-time gift, a durable that doesn't need re-buying). Fix order matters — there's no point optimising a Klaviyo win-back if the unboxing experience is sour.
Repeat Purchase Rate FAQ
For most online stores, 25-30% on a 12-month window is solid and 35%+ is strong. Replenishable categories (beauty, supplements, food) should aim higher — 40%+ is the working target. Considered-purchase categories like electronics will sit far lower without that being a problem.
Retention rate measures whether existing customers stay active across a period (often used in subscription contexts). RPR is binary and order-based: did this customer ever come back for a second order? It's simpler and works for non-subscription stores where there's no recurring entitlement to retain.
90 days for fast-replenishment categories, 365 days for everything else. Shorter windows give you a faster signal but penalise categories with long natural repurchase cycles. Pick one window, keep it consistent across reports, and segment cohorts inside it.
RPR is the earliest predictor of LTV you have. Until cohorts mature (12-24 months), LTV is mostly a forecast — RPR is observed. If RPR jumps from 22% to 30%, you can model LTV uplift before the revenue actually lands.
No. Exclude refunded and cancelled orders from both the numerator and denominator. A customer who ordered, refunded, and never came back isn't a churned repeat buyer — they were never really a first buyer.
It can, but report it both ways. Subscription auto-renewals inflate RPR in a way that masks one-time-buyer health. Track 'RPR (all orders)' alongside 'RPR (one-time buyers only)' to see whether your subscription wrapper is hiding a leaky funnel underneath.
A focused post-purchase programme — email/SMS flows, replenishment reminders, second-order discount — typically moves RPR 3-6 points in a quarter. Bigger jumps usually require product-mix changes (introducing a consumable, a refill SKU, or a complementary cross-sell).
RPR counts customers; Repeat Customer Revenue Share measures the percentage of revenue coming from repeat buyers. The two can diverge: high-AOV repeat customers can drive 60% of revenue even at a 25% RPR. Both matter — RPR for retention health, revenue share for revenue concentration.
Almost always paid acquisition. A surge of new customers from Meta or Google inflates the denominator faster than repeat orders accumulate, so RPR drops mechanically. Look at RPR by acquisition cohort, not blended — the underlying retention may be fine.
Yes, and you should. Tighter shipping promises, a useful first-order insert (size guide, how-to-use card), and behavioural email triggers around expected reorder timing all move RPR without margin erosion. Reserve discounts for genuine win-back at 90+ days of inactivity.
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