Repeat purchase rate

Repeat purchase rate is the percentage of customers who make more than one purchase in a defined period. If 5,000 customers bought from you this year and 1,500 of them placed a second order or more, the repeat purchase rate is 30 percent. It tells you whether a first sale tends to become a relationship.

The metric matters because repeat customers are the cheapest revenue a business has. You have already paid to acquire them, so a second order carries no fresh acquisition cost. A healthy repeat purchase rate means customer acquisition cost is recovered across many orders rather than one, which is what makes growth efficient. It is closely related to repeat customer rate, and the two terms are often used interchangeably.

Divide the number of customers who purchased more than once in the period by the total number of customers who purchased at all, then multiply by 100. The decision that shapes the answer is the period. A short window understates the rate because recent first-time buyers have not had a chance to come back; a long window flatters it.

For a worked example, take a cohort of 2,000 customers who all placed their first order in January. By the end of the period, 540 of them have placed a second order. The repeat purchase rate for that cohort is 540 divided by 2,000, which is 27 percent. Tracking it by acquisition cohort shows whether the customers you are bringing in now come back at the same rate as those you brought in last year.

1. 1

   Total customers

   Every customer who made at least one purchase in the period or cohort. This is the denominator.

2. 2

   Repeat customers

   Customers from that same group who placed two or more orders. This is the numerator.

3. 3

   Measurement period

   The fixed window over which a second purchase counts, ideally measured from each customer first order rather than a calendar boundary.

4. 4

   Cohort anchor

   The point each customer is grouped by, usually the date of their first purchase, so newer and older buyers are compared fairly.

A flat repeat purchase rate is the symptom, but the cause sits in the experience between the first order and the second. A metric tree decomposes the rate into the drivers that make a customer come back: whether the first order met expectations, whether anything brought them back, and whether buying again was easy. That turns a vague retention worry into a specific branch to fix.

If first-order satisfaction is high but the rate is low, the problem is re-engagement, not the product. If satisfaction is the weak branch, no amount of remarketing will fix it. KPI Tree connects each branch to the team and the action that influences it, so the operations team sees the fulfilment branch and the lifecycle team sees the re-engagement branch. When the rate moves, the accountable owner is the one who is notified, and the verified impact loop checks whether the campaign or change they shipped actually moved the number rather than just assuming it did.

Repeat purchase rate depends heavily on category, because purchase frequency differs by nature. Consumables and groceries are bought often, so a high repeat rate is expected. Considered, one-off purchases like furniture or electronics naturally have a lower rate. The ranges below give rough orientation by category type measured over a twelve-month window.

Lifting the rate means earning the second order, then making it easy. The first order has to satisfy, something has to bring the customer back at the right moment, and reordering has to be frictionless. The cards below map to the branches of the tree.

1. 1

   Mixing tenures in one number

   Counting brand-new buyers alongside long-tenured ones drags the rate down artificially, because new buyers have not had time to return. Measure by cohort.

2. 2

   Ignoring the time window

   A repeat rate with no period is uninterpretable. Always state the window, ideally measured from each customer first order.

3. 3

   Treating all categories alike

   Comparing a consumables rate to a durable-goods rate is meaningless. Benchmark within category and purchase frequency.

4. 4

   Optimising re-engagement over the product

   Pushing harder on lifecycle marketing while the first-order experience is weak just recycles unhappy customers and erodes trust.