Repeat purchase rate is the percentage of your customers who have made more than one purchase from your store within a given time period. It is calculated by dividing the number of customers who have purchased at least twice by your total number of customers. If you have 10,000 customers and 3,200 have purchased more than once, your repeat purchase rate is 32%.
Repeat purchase rate is one of the clearest signals of brand health available to an e-commerce operator. A high rate means customers are finding enough value to return without being re-acquired through paid advertising. A low rate means the brand is effectively running a one-time-sale business, paying full CAC for every revenue dollar, with no compounding return on its customer base. The difference between a 20% and a 40% repeat purchase rate, at scale, is the difference between a brand that requires ever-increasing ad spend to grow and one that generates a meaningful base of organic returning revenue.
Benchmarks vary significantly by category. Consumable products - supplements, coffee, skincare, pet food - naturally command higher repeat rates (40-60%+) because the product runs out and needs replacing. Considered purchases like furniture or electronics will sit much lower (5-15%) by nature. Comparing your repeat purchase rate to category benchmarks rather than cross-industry averages gives a more actionable picture of where you stand.
For growth marketers, repeat purchase rate is most useful as a diagnostic that surfaces where in the customer lifecycle retention is breaking down. Segmenting it by acquisition channel reveals whether certain channels attract higher-loyalty customers. Tracking it by first product purchased shows which SKUs create the best long-term customers - that information should feed directly into acquisition creative and landing page strategy. Post-purchase flows, loyalty programs, and winback campaigns are the primary levers for improving repeat purchase rate, and cohort analysis is the correct framework for measuring whether those improvements are sticking over time.
One subtlety worth flagging: a repeat purchase rate measured since a store’s founding drifts upward every year simply because more customers have had time to buy again, independent of whether retention is actually improving. A rolling 12-month window is a fairer basis for tracking whether retention programs are working and for comparing performance year over year. Building that windowed view usually means pulling the calculation into analytics and reporting rather than relying on the all-time figure Shopify surfaces by default, so it can be tracked alongside the retention and loyalty initiatives meant to move it.
Repeat purchase rate is a lagging measurement of retention, not a lever on its own, so moving the number means acting on what happens between the first and second order — the email, loyalty, and subscription tactics that actually turn a one-time buyer into a repeat customer are laid out in turning first-time buyers into repeat customers.
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