Customer retention, and the three metrics people confuse for it
In short
Customer retention is the share of the customers you had who are still customers at the end of a period. Two hidden choices decide the answer — which customers you start with and how long the period is — and changing either moves the number by tens of points without a single customer behaving differently.
What customer retention actually measures
Customer retention is the share of customers you had who are still customers at the end of a period. That is the whole definition, and it hides the two decisions that determine the answer: which customers you started with, and how long the period is.
Change either and the number moves by tens of points without a single customer behaving differently. That is why retention figures are close to useless when quoted without both, and why a benchmark from another company tells you nothing at all.
The three metrics people call retention
They answer different questions and routinely disagree.
| Metric | What it asks | Where it misleads |
|---|---|---|
| Retention rate | Of the customers I had, how many are still here? | Says nothing about how much they spend |
| Repeat purchase rate | Of all customers, how many bought more than once? | Rises when you acquire fewer new customers |
| Revenue retention | Of last period's revenue, how much came back? | Can look healthy while customer count falls |
The second one is the trap. Repeat rate improves when acquisition slows, because the denominator stops filling with first-time buyers. A store that halves its ad budget will report better retention next month and will not be healthier.
If you report one number to a board, report revenue retention and say what the customer count did. If you report one number to a marketing team, report repeat rate by acquisition cohort, because that is the one a campaign can move.
How to compute each one
Take a period — a month is usual, your purchase cycle is better.
- Retention rate. Customers active at the end who were also active at the start,
divided by customers active at the start. Exclude anyone acquired during the period; including them measures acquisition and calls it retention.
- Repeat purchase rate. Customers with two or more orders, divided by all
customers, in a fixed window. Fix the window explicitly — an all-time figure only ever rises and cannot be compared to anything.
- Revenue retention. Revenue this period from customers who existed last period,
divided by last period's total revenue. Above 100% means the customers you kept grew enough to cover the ones you lost.
Cohort them by acquisition month, always. A blended figure mixes customers acquired in a discount push with customers acquired organically, and those two groups behave so differently that the average describes neither.
Why your retention number is probably measuring your acquisition
The uncomfortable part, and the reason the metrics above disagree so often.
Retention is a ratio with an acquisition-shaped denominator. Anything that changes how many new customers arrive changes retention arithmetic without changing customer behaviour at all:
- Spend less on ads → fewer first-time buyers → repeat rate rises
- Run a discount acquisition push → many one-time bargain buyers → repeat rate falls
- Change channel mix → different customers → every retention figure moves
This is why retention and acquisition cannot be judged separately. The same event improves one and damages the other, and a team optimising them in different rooms will each report success. Following the cohort back to the campaign that opened it — what CAC payback measures over time — is the only view where both are visible at once.
What no retention metric can tell you
Whether your retention work caused any of it.
Every number above is descriptive. It says what happened, not what your loyalty programme, your email flow or your win-back campaign contributed. Members of a loyalty programme retain better than non-members in essentially every dataset, and that finding survives no scrutiny at all: your best customers join first. The programme did not create their loyalty; their loyalty created their membership.
The only method that separates the two is withholding the programme from a random group and comparing — which is what measuring a loyalty campaign works through end to end, with the sample sizes it needs. It costs a little revenue and it is the sole version of this measurement that survives a sceptical CFO.
If you have never run a holdout, you do not know what your retention programme is
worth. You know what your loyal customers are worth, which you knew already.
For what the mechanics do to basket size once you can measure them, see raising average order value without buying it, and the rest of retention.
Common questions
What is a good customer retention rate?
There is no cross-industry answer, because retention is a function of purchase cycle. A coffee subscription and a mattress retailer cannot be compared, and a benchmark quoted without a period length and a cohort definition is not a number at all. Your own rate over time, split by acquisition channel, is the only version that can inform a decision.
What is the difference between retention rate and repeat purchase rate?
Retention rate asks how many of the customers you had are still here. Repeat purchase rate asks how many customers ever bought twice. The second rises when acquisition slows, because the denominator stops filling with first-time buyers — so a store cutting its ad budget will report improving retention while getting smaller.
How do I know if my loyalty programme is working?
Withhold it from a random group and compare. Every other method is confounded by the fact that your best customers join first: members outperform non-members in almost every dataset, and that finding survives no scrutiny, because their loyalty caused their membership rather than the other way round.
Should retention be measured on customers or on revenue?
Both, and they can move in opposite directions. Revenue retention above 100% with a falling customer count means a shrinking group of customers is spending more — which is a real result and also a concentration risk worth naming out loud.
See it on your data
Loyalz joins ad spend to settled order lines, so POAS is a column rather than a spreadsheet you rebuild every month.
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