Retention revenue gap calculator
Two inputs, both pre-set to your category. No sign-up or shared data required. Just maths.
What happens when more of your customers come back
Extra annual contribution from lifting your repeat purchase rate.
Book a demo to find the — sitting in your repeat rate.
We’ll show you which customers are about to lapse, what each segment contributes after margin and returns, and where the gap to your category’s strong band actually lives.
Why repeat purchase rate is the number that moves everything
Repeat purchase rate is the share of customers who come back and buy again. It is the least glamorous metric in retail and the one that moves the profit line hardest, because every point of it is revenue you did not have to pay to acquire twice.
The reason it compounds so hard is arithmetic. Expected orders per customer work out to one divided by one minus your repeat rate. At a 16% repeat rate, the average customer places 1.19 orders. At 31%, they place 1.45. That is a 22% lift in revenue per acquired customer, from the same traffic, the same catalogue and the same acquisition spend. Nothing else in retail marketing pays like that.
It also explains why two retailers with identical revenue can have completely different futures. The one at 16% has to keep buying growth. The one at 31% is compounding it. Over three or four years the gap between them stops being a marketing difference and becomes a valuation difference.
What the benchmarks actually say
Bluecore looked at more than 100 retailers across seven categories and found an all-retail first-year repeat purchase rate of 16.5%. Apparel came in at 20.2%, health and beauty at 21.5%, sporting goods and outdoor at 21.2%. Those are lower than most people expect, and worth sitting with: the typical retailer loses roughly four out of every five customers they acquire, permanently, after one order.
The more useful finding is what separated the strong performers. Retailers who could recognise more than 40% of their customers ran repeat purchase rates 53% above average. Those recognising under 10% ran 33% below. That is the single clearest signal in the data, and it is not a marketing-creativity finding. It is a data finding.
Where the gap usually hides
In most omnichannel retailers the leak is in store. Online, every order is attached to an email address whether you like it or not. In store, a sale without a loyalty scan or an email capture is a sale to nobody, the revenue lands but the customer does not. A brand doing half its trade in store with a low capture rate is, in practice, running its retention programme on half its customers while believing it runs on all of them.
Fixing that is unglamorous work: joining point-of-sale, ecommerce and loyalty records to the same person, keeping them current, and making the result usable by a marketer without a data request. But it is the work that moves the number this calculator measures, and it is why a retention problem is so often a data problem in a marketing costume.
FAQs
What is repeat purchase rate?
The share of customers who buy again after their first order. Measured over a first year, it tells you how many of the customers you paid to acquire came back without being re-acquired.
How do you calculate the revenue gap from a low repeat rate?
Expected orders per customer equal one divided by one minus the repeat rate. Because revenue is customers times order value times expected orders, comparing two rates cancels both customer count and order value — leaving revenue times the ratio of the two rates, minus one.
What is a good repeat purchase rate for a retailer?
Bluecore found retailers recognising over 40% of their customers ran 53% above average, and those under 10% ran 33% below. Applied to apparel’s 20.2% average, the strong band starts at 30.9% and the behind band ends at 13.5%.
The maths, and where the numbers come from
Every benchmark here has a source and a date. Where we couldn’t find one, we say so instead of inventing a figure.
Comparing two repeat rates cancels out both customer count and order value, which is why this calculator needs only your revenue and your repeat rate. Nothing else is required, and nothing else is assumed about your business.
Sources
| Figure | Source | Date | Sample |
|---|---|---|---|
| Repeat purchase rate by category — apparel 20.2%, health and beauty 21.5%, sporting goods and outdoor 21.2%, all retail 16.5% | Bluecore, Customer Growth Benchmarks Report | April 2024, calendar 2023 data | 100+ retailers, seven verticals, United States |
| Strong and behind bands (×1.53 and ×0.67) | Bluecore, same report — cohorts recognising over 40% and under 10% of customers | April 2024 | As above |
What we’re assuming
Order value holds steady as repeat rate rises. In practice repeat buyers spend more so the gap shown here is conservative.
Category benchmarks are United States figures. No equivalent Australian or New Zealand benchmark is published. Both settings use the same category rates and the page says so.
Four categories have no published rate of their own. Footwear, home goods, jewellery and accessories, and department stores fall back to the all-retail average of 16.5%, and the page labels it when they do.
The benchmark is from calendar 2023, published April 2024. It is the most recent figure we could verify with both a stated sample and a stated definition.
Some categories have a structural ceiling. Nobody rebuys a mattress annually. Treat the strong band as the top of your category’s realistic range, not a universal target.