What a customer is worth over time, so you know what you can afford to pay to win one.
Enter your order value, repeat rate and margin, and see both the number worth spending against and the number that gets quoted in meetings.
Everything here is worked out in your browser. Nothing you type is sent anywhere, and there is no account to make.
Per customer, not across the store.
The share of customers who buy again the following year. Fill this in OR the lifespan below.
Use this instead if you have measured it. A measured lifespan beats a derived one. Fill in this OR the retention rate above, not both.
Result
The numbers below are an example so the tool opens working. Replace them with yours.
What comes out
How to use it
Average order value and gross margin. Margin here is after the cost of the goods, before marketing.
Orders per customer per year, then either an annual retention rate or a measured lifespan. A measured lifespan beats a derived one every time.
The contribution number is what you can spend against. The revenue number is larger, easier to quote, and the reason accounts overpay for customers.
Lifetime value is what one customer is worth across the whole time they keep buying, rather than on the first order. A store looking only at the first order sets its acquisition budget from the smallest number it will ever have.
There are two versions of it and they are far apart. Gross revenue LTV counts every pound the customer spends. Contribution LTV counts what is left after the cost of the goods. On a 55% margin the second is a little over half the first, and only the second one can pay for anything.
Both appear in the result here, in that order, so the gap between them is visible rather than a matter of which one someone reached for.
Most stores know their repeat rate and do not know their customer lifespan. The calculator will derive one from the other: lifespan is one divided by one minus retention, so a 35% annual retention implies a customer who lasts about 1.5 years.
That derivation carries an assumption worth naming. It treats the retention rate as holding steady year after year, which is a model rather than a measurement. Real retention usually falls hardest in year one and flattens after it, which makes the derived lifespan pessimistic for a store with a loyal core and optimistic for one with a leaky first year.
If you have measured a lifespan, enter it and the derivation is skipped.
The tool
Contribution first, gross revenue second, each labelled with what it is safe to do with it.
Give a retention rate and the tool works out the implied lifespan, and shows it as its own row so the assumption is visible.
Two ratios, 3 to 1 and 4 to 1, so the number arrives as a budget rather than as a statistic.
It is a software convention, carried over to stores that fund inventory up front and have far lower margins. It is a common target, not a law.
LTV is only as good as the retention behind it, and retention measured on a young store is measured on customers who have not had time to leave yet.
Six currencies, and the formatting follows the one you pick rather than defaulting to dollars.
Reading the result
We look at your search visibility across Google and the answer engines, and tell you what is costing you orders. No charge for the first look.
In practice
Take the contribution figure, divide by your ratio, and you have a number to hold every channel to rather than a feeling about what is too expensive.
Run the numbers at your current repeat rate, then at the rate a subscription would give you. The gap is the size of the prize.
A channel bringing customers who buy twice is worth more per customer than one bringing customers who buy once, even at a higher cost per order.
Plenty of stores lose money on order one on purpose. This says whether the rest of the relationship pays it back.
Questions
Three to one is the number people quote. It came out of software, where gross margins run far higher than a store that has to buy stock. A store funding inventory up front usually wants four to one, because the cash is out of the business for longer.
Gross margin, after the cost of goods and before marketing. Putting marketing into the margin and then comparing the result against a marketing budget counts the same cost twice.
A year, and the same year for every input. The main trap is a store measuring retention on customers acquired three months ago: they have not had the chance to churn yet, so the rate looks far better than it will settle at.
Usually because the figure in your head was the revenue one. The contribution version is smaller by exactly the cost of your goods, and it is the version that can pay for an ad.
It handles any business where a customer buys more than once a year. Enter orders per year as the number of billing cycles and retention as your annual renewal rate. Monthly churn needs converting to an annual figure first.
No. Everything is worked out in your browser, with no account and no upload.
The rest of the set
Lifetime value carries a time horizon inside it. Change the horizon and the number changes, so the useful version is the one your cash can wait for.
Where this comes up
