How cohort repeat rate is calculated
Cohort repeat rate follows one group of customers, everyone whose first ever order fell in the same period, usually a month. It asks a single question about them. How many have come back for a second order since?
| Number | How it is worked out |
|---|---|
| First-time customers | Customers whose first order falls in the dates you pick |
| Ordered again since | Of those, customers with two or more orders |
| Cohort repeat rate | Ordered again ÷ first-time customers |
| Bought once so far | First-time customers − ordered again |
| Days since their first order | From your end date to today, and from your start date to today |
The count is cumulative. Each customer counts once, from their first repeat order, however many times they reorder after that. So the rate for any set of dates can only rise as time passes, as more of those customers come back.
A worked example
A jewellery brand won 900 first-time customers in July. By October, 189 of them had ordered again. Its cohort repeat rate for July is 189 ÷ 900 = 21%, about 2 in every 10. The other 711 have bought once so far. At an average order value of ₹1,500, getting 5 more in every 100 to come back once is 45 more orders, worth ₹67,500, from customers the brand has already paid to acquire.
Why cohort, not Shopify’s returning rate
Shopify’s dashboard shows a returning customer rate. It is the share of everyone who ordered in a period who had ordered before. That number isn’t wrong. It answers a different question. How much of this month’s buying came from people who already knew you?
The trouble is what it mixes together. A loyal customer on their eighth order and a new customer coming back for their second both count as returning. So a strong base of old regulars can make the number look healthy while the customers you acquired last month never come back. For a brand spending on ads, that second group is the one that decides whether acquisition pays.
Cohort repeat rate looks only at first-time customers. It follows everyone whose first order fell in the same period and asks how many came back. Repeat customers buying again are left out, so the number tells you one thing clearly. Are the people you paid to acquire returning?
The dashboard number also moves with ad spend. Here is the same brand over two months. August was a sale with heavy ad spend. In September, ads were cut back. The numbers are illustrative.
| Month | Returning | New | Rate |
|---|---|---|---|
| Aug (sale) | 300 | 1,600 | 15.8% |
| Sep | 280 | 400 | 41.2% |
The rate jumps from 16% to 41%, yet almost the same number of loyal customers bought in both months. Only ad spend changed. Cohort repeat rate isn’t affected, because it only compares customers who first bought in the same month. If the August sale customers come back less than July’s, the cohort rate shows it.
Use both. The dashboard rate is a quick read on how much of your revenue comes from people who know you. Cohort repeat rate tells you whether new customers are turning into repeat customers.
Where to find each number
| Number | Where to find it |
|---|---|
| First-time customers | A Shopify customer segment with the first query in the calculator |
| Ordered again since | The same segment with the second query, which adds two or more orders |
| Average order value (optional) | The Average order value card on your Shopify Analytics dashboard, with the date range set to the last 12 months |
Shopify’s customer cohort analysis report, if your plan includes it, shows the same customers month by month. Each of its columns counts only that month, so a customer who orders in two different months appears in both. That is useful for seeing when customers come back. This calculator gives the single cumulative number.
Which period to pick
Pick dates old enough for customers to have needed you again. If your product runs out in about 30 days, a month from three months ago gives most customers two or three chances to reorder. For slower categories like jewellery or home goods, go back six months or more. The calculator shows how many days the customers have had, and warns you when the dates are too recent to read.
For the long view, pick a full year, from 1 January to 31 December, such as your first year of trading. A year mixes customers who have had very different amounts of time to come back, so read it as a lifetime figure, not a like-for-like comparison. Older years will naturally read higher.
To judge a sale or a campaign, pick its dates, such as a Diwali week. That shows whether the customers it brought in came back, which a good sales week on its own can’t tell you.
For a trend, run the same calculation for three or four months in a row. If newer months come back less than older ones did at the same age, something in the first-order experience or the follow-up has slipped.
How to raise repeat rate
- Time a second-order message to when the product runs out, not to your campaign calendar.
- Cross-sell the natural next product, as in the Healthify Store case study.
- Bring back customers who drifted with their own history, not a bigger discount. See win-back campaigns that work.
- Make sure the messages arrive. Delivery is often the cheapest fix, as covered in why WhatsApp delivery drops.
To see what a higher repeat rate does to what each customer is worth, use the customer lifetime value calculator.
To see what a good repeat rate looks like for your category, read what is a good repeat purchase rate.
Questions about repeat rate
What is repeat purchase rate?
Repeat purchase rate is the share of customers who come back to buy again. Measured by cohort, it is the share of customers whose first order fell in a given period, usually a month, who have since placed a second order.
How do you calculate repeat purchase rate?
Take every customer whose first order fell in one period, such as a month. Count how many of them have placed two or more orders since. Divide that by the number of first-time customers in the period and multiply by 100.
Is repeat purchase rate the same as returning customer rate?
No. Shopify’s returning customer rate is the share of everyone who ordered in a period who had ordered before, so it rises and falls with how many new customers you acquire. Cohort repeat rate follows one group of new customers, so it shows whether they actually come back.
What is a good repeat purchase rate?
It depends on how often your product runs out. Consumables reorder far more often than jewellery or furniture. Rather than an industry average, compare your own cohorts at the same age. If newer months come back less than older ones did, retention is slipping.
How do I find repeat customers on Shopify?
Create a customer segment with first_order_date set to the dates you want and number_of_orders >= 2. The segment shows how many customers match. The calculator on this page writes both queries for the dates you pick.
How long should I wait before measuring repeat rate?
At least as long as it takes a customer to need you again. For products that run out in a month, wait two to three months. For slower categories, six months or more.
How can I increase my repeat purchase rate?
Time a second-order message to when the product runs out, cross-sell the natural next product, win back lapsed customers with their own purchase history, and make sure your WhatsApp and email messages are actually delivered.
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