Reorder Rate: How to See Which Products Actually Earn a Second Order

You sell products that get used up, and new customer acquisition is working, but too few of those customers come back. Your dashboard shows one repeat customer rate for the whole store, and it does not say which product earns the second order or how long that takes. Reorder rate is the share of a product's buyers who buy that same product again within a set number of days, so it tells you which products earn a second order and when the reorder tends to happen.

For merchants selling replenishable products, and for agencies reporting retention to clients, that changes what you do next: when to send replenishment reminders, which buyers are late for a reorder, and where a win-back campaign has the best chance.

Key takeaways

• Reorder rate is the share of a product's buyers who bought the same product again within a set number of days. Repeat purchase rate counts any second order, of anything.

• The formula needs a window: buyers of X who ordered X again within N days, divided by buyers of X whose first order is at least N days old.

• Leaving out the window, or counting buyers who have not had N days yet, makes every product look worse than it is.

• Time to second purchase is the number of days between a customer's first and second order of the product. Use the median, not the average.

• A low-reorder product and a slow-reorder product need different fixes. Measure at two windows to tell them apart.

What is reorder rate, and how is it different from repeat purchase rate?

Reorder rate is the share of customers who bought a specific product and then bought the same product again within a set window. Repeat purchase rate, sometimes called repurchase rate, is the share of all unique customers who placed any second order, whatever they bought. Unlike a general retention rate, reorder rate tracks completed repeat purchases of the same product. A high reorder rate is a sign of product satisfaction and customer loyalty: people came back for the same thing. Measured per product, it tells you which retention work to do first.

A coffee customer who buys a bag of beans and comes back for a mug counts toward your repeat purchase rate, but not toward the reorder rate of those beans. The mug is a cross sell. Only a second order of the same beans counts. In stores that sell consumables, a large share of second purchases are reorders of the same product, which is why reorder rate explains so much of the store-wide number.

The store-wide number is still worth tracking; the repeat purchase rate guide covers it. But it cannot tell you which product is doing the work. Reorder rate can, which is why it is the number to look at for supplements, pet food, coffee, skincare and anything else customers run out of.

Reorder rate versus reorder point

If you searched for reorder rate and found inventory formulas, those describe a different number. A reorder point is the stock level at which you reorder inventory from a supplier. The reorder point formula is lead time demand plus safety stock, where lead time demand is average daily sales multiplied by the lead time in days. Its job is to keep the inventory level between a stockout and overstock.

Reorder rate is about customers, not stock. The two meet in inventory management and forecasting: if you know how many existing customers are due to reorder a product next month, you know part of the demand your safety stock has to cover, and you avoid lost sales when repeat buyers arrive.

How do I calculate reorder rate?

Count the buyers of a product who bought it again within N days, and divide by the buyers of that product whose first purchase was at least N days ago. The store-level shortcut, repeat customers divided by total customers, ignores both the product and the window.

Reorder rate for product X within N days = customers whose first purchase of X was at least N days ago and who bought X again within N days, divided by all customers whose first purchase of X was at least N days ago.

Pick N to match how long the product lasts (pack size divided by average daily usage), plus a margin. A 30-day supply might get a 45-day window. A product that lasts two months might get 90. You will refine N once you see the actual time to second purchase, below.

Always write the time window next to the number. A reorder rate on its own means little. A reorder rate "within 45 days" can be compared month to month and product to product.

Why the window matters

Without the "at least N days ago" rule, the denominator includes customers who bought last week and could not have reordered yet. They count as failures, and the rate drops for no real reason.

This hits hardest where it misleads most: a product with many recent first-time buyers, such as one you just launched or promoted. The more recent buyers it has, the worse it looks. Excluding immature buyers from the denominator until they reach N days fixes it.

Two rates, across stores or periods, are only comparable with the same window, time period and eligibility rule.

How do I measure time to second purchase?

For each customer who bought the product twice, count the days between the first and the second purchase of it. Then take the median across those customers, per product.

The median matters because a few customers who come back after a year drag the average far to the right. The purchase frequency guide explains why the average misleads.

Look at the spread as well as the middle. For fast consumables, many repeat purchases come within the first month, so measure before you set any reminder. If most second orders of a coffee bag land between day 25 and day 35, that range is your reminder window. It tells you when to send the replenishment email, and the replenishment email timing guide covers how to set it from that number. It also tells you what N should be for the reorder rate: somewhere past the end of that range.

How do I calculate reorder rate per product from an order export?

Export orders with customer id, order date and product. For each customer, find their first purchase of the product, check whether they bought it again within N days, and divide those who did by all eligible customers.

Columns needed: customer id or email, order date, product id or SKU. Order id and quantity help but are optional.

1. Export at least a year of orders, long enough to cover seasonality. Remove test orders, cancellations and full refunds.

2. Filter to one product.

3. Sort by customer id, then by order date.

4. For each customer, mark their first purchase of the product.

5. Find their next purchase of the same product, if any, and compute the days between the two.

6. Mark the customer as eligible if their first purchase is at least N days before the last date in the export.

7. Among eligible customers, mark "reordered" if the gap is N days or less.

8. Divide reordered by eligible.

9. Take the median of the gaps from step 5 for the time to second purchase.

Repeat for your top five to ten replenishable products. Save the sheet as a template so you can paste in a fresh sales data export each month.

Worked example: three products, two windows

An illustration with round numbers, not a benchmark.

A store sells three replenishable products. Every customer counted below made their first purchase of the product at least 90 days before the end of the export, so all of them are eligible for both windows.

The vitamin is fast and high. Most reorders arrive around day 32, and half of all buyers are back within 90 days.

The face serum looks weak at 45 days and healthy at 90. It is not failing; it simply lasts longer. Judged on the vitamin's window, it would have been flagged for no reason.

The coffee is low at both windows, yet the customers who do reorder come back quickly. The product gets used up fast, and most buyers do not return for it. That is a different problem from the serum's.

The immature-buyer trap: suppose 600 more customers bought the vitamin for the first time in the last three weeks. Put them in the denominator and the 45-day rate falls from 400 of 1,000 (40%) to 400 of 1,600 (25%), although nothing about the product changed.

What to do with a low-reorder product versus a slow-reorder product

A low-reorder product has few buyers coming back at any window. A slow-reorder product has plenty of repeat buyers, just later than you assumed. The first needs a diagnosis, the second only needs the timing adjusted.

Low-reorder (the coffee in the example):

• Read reviews, returns and support tickets for the product. A quality or fit problem, or any other hit to customer satisfaction, shows up there first. A review request a week after delivery surfaces problems early.

• Check what the buyers who did not reorder bought instead, and look at their customer segments and past purchases before changing the offer. If they moved to another of your products, it is a substitution, not a loss.

• Test whether a usage email or a different pack size helps the first purchase get used up.

• Check delivery and fulfillment. Delivery delays or a damaged first order are a common reason the second one never comes.

• Simplify the reordering process. A one-click reorder link in the email removes friction from the customer experience. If you run a loyalty program, reward customers for the reorder itself.

• Use personalized post purchase follow-ups to re-engage customers: their own product, at their own timing, rather than a store-wide promotion.

• Think twice before leading acquisition with it. The products that drive repeat purchases article shows how to find the first products that do bring customers back.

Slow-reorder (the serum):

• Move the reminder in your post purchase flows later, to just before the median.

• Use the longer window when you report on it.

• Do not send a discount at day 45 to customers who are simply not out yet. Automated post-purchase communication that lands as the product runs low is the simplest way to remind customers and encourage repeat purchases.

In both cases, customers who pass the product's window without reordering are late, and that list is the starting point for a win-back sequence.

Which tools measure time to second purchase, and what can a spreadsheet do?

A spreadsheet handles reorder rate and time to second purchase for a handful of products from a standard export. It gets slow and error-prone across many products, several stores, or when you want to refresh it every month.

What a spreadsheet does well:

• Reorder rate per product at one or two windows.

• The median days to second purchase and a simple histogram of the gaps.

• A list of customers who are past the window without a reorder.

Where it runs out: dozens of products, keeping the numbers current, and linking reorder timing to what else customers buy or to customer segmentation. Many analytics and email tools show store-wide purchase frequency; fewer show it per product with a window, and fewer still track cohort retention over time next to it. Affinsy computes reorder cadence per product from an uploaded order export, alongside which first products bring customers back and RFM customer segments, and exports customer lists for campaigns.

Next steps

• Export a year of orders and pick your top five replenishable products.

• Compute the median days to second purchase for each, and set N just past the range where most reorders land.

• Calculate reorder rate within N days, counting only eligible buyers.

• Recalculate at a second, longer window to separate low-reorder from slow-reorder products.

• Time each product's reminder to just before its own median, and build the rest of your post purchase strategy around that timing.

• Extend your post purchase email flow past the first two weeks. Many flows stop well before a product that lasts a month or more runs out, and miss the reorders that come later. Start any diagnosis with your best-selling low-reorder product.

If you would rather have reorder rates, reorder timing and due-customer lists worked out for every product, the 48-hour analysis delivers them from your own orders.

FAQ

Is reorder rate the same as repeat customer rate?

No. Customer retention in general measures whether customers stay active. Repeat customer rate counts returning customers, anyone who placed a second order at your store. Reorder rate counts customers who bought the same product again. A store can have a healthy repeat customer rate while its main product has a low reorder rate, because customers come back for other things.

What window should I use if I do not know how long my product lasts?

Base it on actual reorder behavior, not guesses. Measure the time to second purchase first, from customers who bought the product twice. Set the window a little past the range where most of those second orders land. Until you have that, use two windows, one short and one long, and report both.

What is a good reorder rate?

It depends on the category and the window, so compare each product with its own history rather than an outside benchmark. Consumables such as pet food, coffee and supplements reorder more than durable goods because they get used up. For products that do not run out, reorder rate stays small at any window; look at what customers buy next instead. A rising reorder rate on your top products, tracked monthly like any other ecommerce metric, is the direction that matters. What makes a good repeat purchase rate for the whole store is a separate question.

How does reorder rate relate to RFM segments?

Reorder rate describes products; RFM analysis describes customers. Combined, they tell you which customers across your customer base are late for which product, and which of your loyal customers need a tailored follow-up to come back. Your loyal customers usually buy the high-reorder products on time, while customers slipping toward lapsed are often overdue on the product they started with.