LTV to CAC ratio for ecommerce

What the ratio tells you

Customer lifetime value, LTV, estimates how much a customer is worth over a period. Customer acquisition cost, CAC, is what it cost to win them. The ratio of the two asks whether acquiring customers is a good use of money in the long run. A ratio of 1 means that over the chosen period the customer pays back exactly what they cost. A higher ratio means more is left over for overheads and profit.

For ecommerce this matters because many first orders barely cover advertising. The business case then rests on repeat purchases, and the ratio is the way to test that case.

Calculating LTV properly

Use contribution, not revenue

If you divide revenue by CAC, the ratio flatters the business, because revenue ignores product cost, shipping and fees. Use contribution margin per order instead, the amount left after direct costs and before advertising. The customer LTV calculator takes inputs of this kind.

A simple formula

A basic estimate multiplies three things: average contribution per order, average orders per customer over the period, and optionally a retention adjustment. For example, if contribution per order is 22 pounds and customers place on average 1.8 orders in the first twelve months, twelve-month LTV is 22 times 1.8, which is 39.60 pounds.

Choose a time horizon

Be explicit. Twelve-month LTV is more defensible for a young store than a five-year projection built on guesses. The longer the horizon, the more the number depends on assumptions you have not tested.

Use cohorts if you can

A cohort is a group of customers who made their first purchase in the same month. Tracking how much contribution each cohort generates over later months gives real figures. Your store platform or analytics tool may support cohort reports. If you are new, you may have too little history, in which case state that the estimate is provisional.

Calculating CAC

CAC is acquisition cost divided by new customers in the same period. The CPA versus CAC guide explains the choices: ad spend only, or all acquisition costs. Use the same definition every time.

Putting them together: a worked example

A store sells loose-leaf tea. A first order averages 28 pounds with contribution of 12 pounds before ads. Using cohort data, customers place on average 1.6 orders in twelve months, and later orders carry contribution of 14 pounds because there is no acquisition discount. So twelve-month LTV is 12 plus 0.6 times 14, which is 20.40 pounds.

Paid CAC this quarter is 15 pounds. The LTV to CAC ratio is 20.40 divided by 15, which is 1.36. First-order profit is a loss of 3 pounds, since 12 minus 15. The store recovers the cost only through repeat orders, and the margin left over after twelve months is just 5.40 pounds per customer before overheads. That is thin. If CAC rose to 19 pounds, the ratio would fall to 1.07, nearly nothing.

The numbers are invented, but the reasoning shows how sensitive the result is. The ratio would look far better if you used revenue, 28 plus 0.6 times 28, which is 44.80, divided by 15, giving 2.99. That is the error to avoid.

Payback time

A ratio does not say how long you wait. A customer whose value arrives over three years ties up your cash for three years. The CAC payback calculator estimates how many months it takes for contribution to recover CAC. For a small store with limited cash, short payback is usually more important than a high long-run ratio, because growth is funded from recovered spend.

Use the two together. A moderate ratio with quick payback can be safer than a high ratio with slow payback.

What is a good ratio?

You will often see a rule of thumb that three to one is healthy. It is worth knowing the figure and treating it carefully. It came from particular kinds of subscription businesses, and it depends on how LTV and CAC were defined. For an ecommerce store, the right level depends on margin, overheads, payback and risk tolerance. A better approach is to work backwards: decide how much profit per customer you need after overheads, then see what ratio that implies for your cost structure.

Linking to ad targets

If you accept a lower first-order return because of repeat purchases, convert this into a campaign target. Suppose twelve-month LTV in contribution is 40 pounds and you want to keep at least 40 per cent of that as profit after acquisition. Maximum CAC is 24 pounds. The max CPA calculator and break-even ROAS guide explain how to translate this into figures for your ad account. The first-order break-even ROAS will then be above 1 times your first-order margin, which means you are running at a deliberate first-order loss. Write that decision down and review it as cohort data matures.

Segment before you average

Averages can hide very different customers. Customers acquired through a deep discount may behave differently from those who bought at full price. Customers who buy one product category may repeat more than others. If you have enough data, calculate LTV for segments such as first product bought, acquisition channel and discount use. You may find that a channel with a poor first-order ROAS produces strong repeaters, or the reverse. Avoid over-slicing, however. Small segments give unreliable numbers.

Attribution cautions

CAC depends on how you attribute customers to acquisition spend. Customers influenced by several channels are hard to assign. The MER versus ROAS guide discusses looking at the whole business instead. LTV depends on retention, which can change with product quality, season and competition. Past cohorts are a guide, not a guarantee.

Common mistakes

• Using revenue instead of contribution.
• Projecting long horizons from a few months of data.
• Ignoring payback time.
• Mixing definitions of CAC between periods.
• Treating a borrowed target ratio as proof of health.
• Counting discounted first orders and full-price repeats as if they behaved the same way.

Scope note

All examples are invented. Treat the ratio as a decision aid based on estimates, and update it as real cohort data arrives. If the numbers look too good, check your inputs first.

Estimating repeat purchase rate from your own orders

You do not need specialist software to get a first estimate. Export your orders with customer identifiers and dates. Take all customers whose first order fell in one month, then count how many placed a second order within ninety days, and how many within twelve months if enough time has passed. Divide by the cohort size to get the repeat rate. Add up the contribution from those later orders and divide by cohort size to get the average later contribution per customer. Add first-order contribution to arrive at LTV for that cohort. Repeat the exercise for two or three other months, and compare. If the numbers vary widely, your estimate is uncertain and you should say so. Note that very recent cohorts have not had time to repeat, so do not compare them with older ones as if they had.

Product and offer effects on LTV

Not every product encourages repeat purchases. Consumables such as tea, coffee, skincare and pet food naturally invite reorders, while furniture and luggage do not. If you sell both, the blended LTV hides two businesses. Calculate LTV by the product bought first, and set different CAC limits for each. Offers matter too: a customer acquired with a deep first-order discount may have a different repeat rate from one who paid full price. Subscriptions change the picture again, because retention curves and cancellation rates replace simple repeat counts. The practical lesson is to let the data in your store, rather than a general rule, decide how much weight repeat purchase gets in your acquisition limits.

When the ratio is misleading

The ratio can mislead in a few predictable ways. A customer base dominated by a few very large buyers inflates the average LTV, so check the median too. A short history that includes a viral spike gives an unrepresentative cohort. A change of product mix, price or shipping policy makes old cohorts a poor guide to new ones. If any of these apply, show a range, for example a cautious and an optimistic estimate, rather than a single figure, and base spending limits on the cautious one. A range keeps the conversation honest about uncertainty.

12-month cohort LTV / CAC worksheet

Blank review record. Complete from evidence you hold; this is not approval.

Cohort start / cutoff: [dates, 12-month horizon]
Original new customers: 100 (illustrative; include non-repeaters)
Net cohort revenue over 12 months: £15,000
Variable costs: £9,000
Contribution: £6,000 / 100 = £60/customer
Acquisition costs: £4,000 / 100 = £40 CAC
Contribution LTV / CAC: 1.5× over 12 months, not lifetime certainty
Low/base/high retention assumptions:
Refund basis / acquisition cost scope / review date:

Common questions

What is the LTV to CAC ratio?

Customer lifetime value divided by customer acquisition cost. It shows how much value a customer brings relative to what it cost to acquire them.

Should LTV use revenue or profit?

Use contribution margin. Revenue-based LTV overstates the value of a customer.

Is 3 to 1 a good ratio for ecommerce?

It is a common rule of thumb from other contexts. Your target should come from your margins, overheads and payback needs.

How long should the LTV period be?

Choose a period you have data to support, often twelve months for a young store. State it clearly.

How do I calculate LTV with little history?

Use a provisional estimate, label it clearly, and update it as cohort data grows. Prefer the first order break-even as your safe baseline until then.

Why does payback matter if the ratio is high?

Because cash returns slowly in a long-payback business, which can limit how fast you can grow.