Returning Customer Rate on Shopify: What It Tells You

Returning customer rate is the share of customers who ordered in a period and had already ordered from you before. It describes the make-up of this period's buyers, not how loyal your customers are in general, and it falls whenever you acquire new customers faster than old ones come back. This guide covers the definition, the two things that move it most, how it differs from repeat purchase rate, why time to second order matters, and what to do with all three.

How is returning customer rate defined?

Take everyone who placed an order in the period. Count those with at least one earlier order. Divide that count by the total.

Three details shape the result:

• It counts customers, not orders. Someone who buys three times in the month is one returning customer.
• It depends on the period. Over a week, few people have had the chance to buy twice. Over a year, many more have. A rate is only comparable with another rate for a period of the same length.
• It relies on recognising the customer. A returning shopper who checks out with a different email address looks new. This pushes the rate down a little.

Why does fast growth lower the rate?

Because new customers enlarge the bottom of the fraction straight away, while the top can only grow as fast as existing customers reorder.

An example with made-up round figures. Say a store has 1,000 customers ordering in a month, 300 of whom have bought before. The returning customer rate is 30%. The next month the store doubles its ad spend and wins 1,700 new customers, and the same 300 loyal customers order again. Now 300 out of 2,000 is 15%.

The rate halved, yet the same people came back, and the store now has 1,700 more customers who might reorder later.

The reverse also holds. Cut acquisition and the rate climbs, because returning customers make up more of a shrinking total. A rising returning customer rate with falling sales is a warning sign, not a success.

So read the rate together with the two counts behind it: the number of returning customers and the number of new customers, each over time. Those two lines tell you more than their ratio.

How much does product category matter?

A great deal, which is why comparing your rate with another store's is rarely useful.

The rate follows from how often the product is needed. Coffee, skincare and pet food run out and are rebought on a rhythm. A mattress, a wedding dress or a piece of furniture may be bought once in many years, and a healthy store selling them can run with a low rate indefinitely.

The useful comparison is your own rate for the same period a year ago, with the growth caveat above kept in mind.

What is the difference from repeat purchase rate?

They answer different questions because they are divided by different things.

• Returning customer rate looks at one period's buyers and asks how many were not new. The bottom of the fraction is this period's customers.
• Repeat purchase rate looks at a group of customers and asks how many ever bought a second time, usually within a window. The bottom of the fraction is the group, for example everyone who first ordered in March.

Repeat purchase rate does not drop when you acquire faster, because each group is measured against itself. That makes it the better measure of whether customers actually come back. Calculated month by month for each first-order group, it becomes a cohort table, which our guide on how to read a cohort analysis explains.

Use the returning customer rate to understand the mix of today's revenue. Use repeat purchase rate by cohort to judge retention.

Why track time to second order?

Because it tells you when to act. Time to second order is the gap between a customer's first and second purchase, summarised across everyone who has made a second purchase.

Use the median, since a few customers who return after two years would drag a mean upwards. Then put it to work:

• Timing reminders. If the median gap is around six weeks, a reorder email in week five reaches people as they are about to run out. One sent in week two is early, and one in week ten is late.
• Setting the window. A customer who has gone well past the typical gap without ordering is slipping away. That is the moment for a win-back message, not a year later.

You can calculate this from an order export: for each customer with two or more orders, subtract the first order date from the second, then take the median.

What should you do with the number?

Decide where the next unit of effort goes.

1. If returning customers are growing in number, retention is working. Keep doing what you do and look at acquisition.
2. If the number of returning customers is flat while new customers grow, the first purchase is not leading to a second. Look at the post-purchase experience: delivery, the product itself, and whether you ask for the reorder at the right time.
3. If one product or channel brings customers who never return, rethink what you spend there. A first order that never repeats has to pay for its own acquisition.
4. If a small group returns again and again, treat them as a segment with their own messages. Our guide to RFM segmentation for Shopify customers shows one way to define that group.

The value of a returning customer over time is the subject of our piece on calculating customer lifetime value.

Shopify's built-in reports give you new versus returning customer counts, as the guide to Shopify's built-in analytics describes. For the cohort view, Marka Metrics includes customer dashboards on its free plan and adds customer segments and retention cohorts on paid plans.

A short checklist

1. State the period whenever you quote the rate.
2. Look at the counts of new and returning customers, not only the ratio.
3. Expect the rate to fall when acquisition speeds up.
4. Measure repeat purchase rate by first-order month to judge retention.
5. Find your median time to second order and time reminders to it.
6. Compare with your own past periods, not with other stores.

Returning customer rate is a description of your customer mix, and it only becomes useful beside cohorts and counts. If you want those drawn from your Shopify orders, Marka Metrics is where we would point you.