How do you calculate customer lifetime value?
Customer lifetime value is calculated with the formula: Average Order Value times Purchase Frequency times Customer Lifespan, multiplied by gross margin for the accurate version. For example, a customer with a ₹1,000 AOV, buying 3 times a year for 2 years at 50% margin has a CLV of ₹3,000 in gross profit. The formula is easy; the hard part is that every input, especially frequency and lifespan, is driven by churn, which most brands cannot see. Improving those inputs is what raises CLV, and seeing them clearly is what DOPE helps Shopify and D2C brands do.
CLV is the economic heart of ecommerce: it sets how much you can profitably spend to acquire a customer. Google's Neil Hoyne argues brands should focus on CLV over conversion rate, because clicks and conversions lose sight of the customers who come back and contribute the most value. Here is how to calculate it correctly, with examples, and why the number is only as good as your ability to move its inputs.
The customer lifetime value formula
Start with the simple version, then make it accurate.
The basic CLV formula is: Average Order Value times Purchase Frequency times Customer Lifespan. It captures how much a customer spends, how often, and for how long.
The accurate version adds gross margin, because revenue is not profit: CLV = (Average Order Value times Purchase Frequency times Customer Lifespan) times Gross Margin %. Always calculate CLV on gross profit, not revenue. A revenue-based CLV can look healthy while the margin-adjusted number tells you that you are losing money on acquisition. The gross-profit number is the one that should govern your budget.
How to calculate it, step by step
Work it out from your last 12 months of data. Here is a worked example.
Suppose you did ₹5,00,000 in revenue across 2,500 orders from 1,000 unique customers, at 45% gross margin.
- Average Order Value = total revenue ÷ number of orders = ₹5,00,000 ÷ 2,500 = ₹200.
- Purchase Frequency = number of orders ÷ unique customers = 2,500 ÷ 1,000 = 2.5 orders per customer per year.
- Customer Lifespan = the average number of years a customer keeps buying. Say 3 years.
- Multiply: ₹200 × 2.5 × 3 = ₹1,500 revenue CLV.
- Apply margin: ₹1,500 × 0.45 = ₹675 gross-profit CLV.
So each customer is worth ₹1,500 in revenue, or ₹675 in gross profit, over their lifetime. That gross-profit figure is your real number.
The ratio that makes CLV useful: CLV to CAC
CLV on its own is a number. Paired with acquisition cost, it becomes a decision.
Divide CLV by your customer acquisition cost. A healthy CLV to CAC ratio is around 3:1, meaning each customer is worth at least three times what you paid to acquire them. Below 2:1 usually means you are not generating enough margin to sustain growth. Above 5:1 can signal you are underinvesting in acquisition and could grow faster.
Using the example: if CAC is ₹200, your ratio is 7.5:1, a strong position. If CAC is ₹800, the ratio is under 1:1, and no amount of marketing optimization fixes a structural problem like that. This is why CLV is the number that sets your acquisition budget, not first-order margin.
The catch: the formula hides where the value actually comes from
Here is what most CLV guides do not stress. The formula is trivial. The inputs are where the truth lives, and two of them, purchase frequency and customer lifespan, are almost entirely determined by churn.
A customer's lifespan is just the inverse of your churn: keep customers longer and lifespan rises. Purchase frequency rises when customers come back more often, which again is retention. So the two inputs that most move CLV are not really separate levers, they are both churn in disguise. This is why raising CLV is mostly a retention problem, not an AOV or acquisition problem. Improve retention and both frequency and lifespan climb, and CLV climbs with them.
There is a second catch: the average CLV hides a distribution. Your ₹675 figure blends customers worth ₹100 with customers worth ₹5,000. Managing to the average means treating your most valuable customers like everyone else, which is how brands lose their best customers without the blended number ever flinching.
Why you cannot improve CLV you cannot see
Follow both catches to their conclusion. To raise CLV you must raise frequency and lifespan, which means reducing churn. And to protect CLV you must know which customers carry the high value and which are about to leave. Both require seeing your customers individually, not as one average.
Most brands cannot. They know their blended CLV but cannot tell you which specific customers are drifting toward a shorter lifespan, or which high-value customers are cooling. And they will not learn it from complaints, only about 1 in 26 unhappy customers ever says anything. The signals that predict a customer's lifespan live in their behavior and sentiment, unread. A CLV number you cannot break down and act on is a report, not a lever.
How DOPE turns CLV from a number into a lever
DOPE is a customer intelligence tool for Shopify and D2C brands, and it works on exactly the inputs that determine CLV.
DOPE reads behavior and sentiment across your customer base and surfaces the customers whose lifespan is about to shorten, the ones churning before they reached their full value, and the high-value customers cooling before they leave. That directly protects the frequency and lifespan inputs your CLV depends on. Instead of watching a blended CLV number drift, you see which specific customers are pulling it down and why, in time to act, and which high-value customers are worth protecting first.
A note on how it works: DOPE surfaces which customers threaten or carry your CLV and why, then you act on your own channels, in your own voice, to keep them. It does not calculate your CLV dashboard for you or message customers. It is the intelligence that lets you move CLV's inputs, by catching the churn that shortens lifespans and cuts frequency, rather than just measuring the outcome.
Calculate your CLV, on gross profit, against CAC. Then remember the number only improves when customers stay longer and buy more often, which means CLV is really a retention metric wearing a math costume. For the distribution problem, see customer lifetime value, for the churn that shortens lifespan, how to reduce customer churn, and for the frequency side, repeat purchase rate.
FAQ
What is the formula for customer lifetime value?
The simple CLV formula is Average Order Value times Purchase Frequency times Customer Lifespan. The accurate version multiplies that by gross margin: CLV = (AOV × Purchase Frequency × Customer Lifespan) × Gross Margin %. Always use the gross-profit version to set your acquisition budget, since revenue is not profit.
How do I calculate CLV step by step?
Calculate AOV (revenue ÷ orders), purchase frequency (orders ÷ unique customers), and customer lifespan (average years a customer stays), then multiply the three and apply gross margin. Example: ₹200 AOV × 2.5 frequency × 3 years × 45% margin = ₹675 gross-profit CLV per customer.
What is a good CLV to CAC ratio?
Around 3:1 is the healthy benchmark, meaning a customer is worth at least three times what you paid to acquire them. Below 2:1 usually signals insufficient margin to grow; above 5:1 can mean you are underinvesting in acquisition. Calculate it on gross-profit CLV.
Why is my CLV lower than it should be?
Usually because of churn. Two of the three CLV inputs, purchase frequency and customer lifespan, are driven by retention, so a low CLV is often a churn problem in disguise. Reducing churn raises both frequency and lifespan, which lifts CLV more than AOV tactics alone.
How does DOPE help improve customer lifetime value?
DOPE reads behavior and sentiment to surface customers whose lifespan is about to shorten and high-value customers who are cooling, so you can protect the frequency and lifespan inputs CLV depends on. It turns CLV from a number you measure into inputs you can move, by catching churn early. You act on your own channels.
