Customer lifetime value (CLV) is what a customer brings in over the whole period they stay a customer: average order value times purchases per year times the number of years.
It's more common than you'd think: businesses setting their ROAS target based on what they assume the average order value is. Not on what a customer generates over time. If you can shift that philosophy to account for what a customer can bring in on average, beyond the first purchase, you can afford a higher acquisition cost.
If you know a customer buys an average of three times, you also know that customer is worth three times more than their first order suggests. If you set your acquisition budget based on that first purchase alone, you aim too low and miss potential customers.
This article is about how to understand the actual value of a customer, where measuring it goes wrong, and what that means for your ROAS targets and acquisition budget.
The usual calculation
The standard approach goes like this. You know your average order value. You know what margin sits on it. You determine an acceptable acquisition cost based on that first transaction. And you set your Google Ads or Meta campaigns to a ROAS target that reflects that.
Some businesses go a step further. They look at the number of repeat customers and try to build a multiplier from that. If 40 percent of our customers come back, we can pay more for a new customer. That's the right line of thinking. But the way that 40 percent gets calculated determines everything.
Repeat share is not the same as repeat rate
This is where it goes wrong. Repeat share is the proportion of your total orders that comes from returning customers. If you have 100 orders today and 40 come from people who have bought before, your repeat share is 40 percent.
Repeat rate is fundamentally different. It tells you how many of the customers you acquired in a given period came back afterwards. Of all the new customers you acquired three years ago, how many have made another purchase since then?
"Repeat share tells you how dependent your revenue today is on returning customers. Repeat rate tells you how many acquired customers from the past ordered again."
The difference sounds subtle. The consequences are not. Imagine: 5 returning customers against 10 new ones. Repeat share: 33 percent. The following year: 6 returning customers against 20 new ones. Repeat share drops to 23 percent. Internal alarm about falling loyalty. While in absolute terms you have more returning customers than ever and your acquisition is exploding. A falling repeat share alongside rising absolute volumes is exactly what you want to see.
| Year 1 | Year 2 | |
|---|---|---|
| Returning customers | 5 | 6 ↑ |
| New customers | 10 | 20 |
| Repeat share | 33% | 23% ↓ |
How to calculate customer lifetime value
The basic formula for customer lifetime value is simple: average order value, multiplied by the number of purchases per year, multiplied by the number of years a customer remains active. A customer who spends an average of €120, buys twice a year, and stays a customer for three years is worth €720. Not €120. If you want to get it exactly right, use your gross margin instead of revenue. At a 40% margin that customer is worth 288 euros to you, and that's the number you set against your acquisition cost.
That sounds logical. But the ROAS target is then built on that €120, while a customer brings in €720. The result is that you consistently underpay to win that customer, while in this case they're worth six times more than they appear at first glance.
Where it gets interesting: you can also reverse that logic. If you know how many customers you acquired last year, and you know the repeat rate of comparable cohorts from the past, you can predict how many of those customers will buy again this year. Multiply that by your average order value and you have a well-founded revenue forecast based on your existing customer base, without acquiring a single new customer.
The difference from using a global average repeat rate is that you look per cohort. Customers you acquired three years ago behave differently from customers of six months ago. If you don't make that distinction, you steer on an average that doesn't precisely fit any segment.
"Your existing customer base is a predictable revenue source. The question is whether you have the data to make that prediction."
What a correct CLV calculation changes
The strategic consequences of a correct CLV are clear. The acquisition cost of a new customer can be higher. If you know that a customer buys an average of three times over two years, you can pay more for that first purchase than someone who only looks at the margin on that first order. That's a better investment.
Your ROAS target needs to reflect that. A ROAS target based on the first purchase alone is fundamentally too conservative for customers with a high repeat rate.
At the client where I implemented this, the ROAS target could be adjusted from over 700 percent to around 400 percent within an attribution model with a 60-day time window. That sounds like a reduction. In reality it was an expansion: more could be invested in acquisition than the business had thought possible for years. And if you know you're working on loyalty and customer value grows over time, you can scale up the acquisition cost further. A rising repeat rate justifies a higher investment in new customers, because you know that investment pays itself back across multiple purchases.
Being too conservative with acquisition costs can indirectly cost you more than you think.
To close
The ROAS you measure is almost always the ROAS on the first purchase. That's the number your reporting shows, the number your targets are built on, and the number that determines how much you're willing to pay for a new customer. But the actual ROAS, measured over the full lifecycle of a customer, is consistently higher for everyone who comes back afterwards.
That has a concrete implication. If you know your customers buy an average of three times over two years, then the ROAS on that first purchase is not the benchmark on which you should base your acquisition budget. You can set your ROAS target lower. Or your CPA higher. As a logical conclusion from what your customers bring in, without guesswork.
I also understand that other factors come into play. You need to account for your monthly and annual fixed costs and other financial constraints over time. It can sometimes be complicated to invest today's marketing budget across different financial years. But the question remains: do you have the data to make that trade-off properly?
Related: want to know how to measure whether your retention holds up, and what your purchase cycle tells you about where customers drop off? The cohort analysis article explains how.