Customer Lifetime Value (LTV) Calculator
Use this LTV calculator to estimate customer lifetime value with a simple, a margin-adjusted or a mobile ARPDAU model.
LTV (simple model)
$720.00
Enter your numbers and press Calculate.
Average order value × Purchases per year × Customer lifespan (years)
How to calculate customer lifetime value
LTV (simple model) = Average order value × Purchases per year × Customer lifespan (years)
- Pick the model that fits your data: simple for order history, margin-adjusted when you know gross margin and annual churn, mobile when revenue is tracked per daily active user.
- For the simple model, multiply average order value by purchases per year and by lifespan in years. The margin-adjusted model multiplies order value, frequency and gross margin, then divides by the annual churn rate.
- Read the result as an average per customer, and note which model produced it before you compare it with CAC.
$60 × 4 purchases × 3 years = $720 (simple model)
The guide to this topic: Customer retention metrics: retention, churn and LTV explained
What is customer lifetime value (LTV)
Customer lifetime value, shortened to LTV or CLV, is an estimate of how much a customer is worth to your business over the whole time they stay a customer. It is modeled from data you already have, such as average order value, how often customers buy and how long they stay. A customer who spends $60 per order, orders four times a year and stays three years has a simple LTV of $720.
There is more than one formula, and each answers a slightly different question. The simple model gives revenue per customer. The margin-adjusted model multiplies by gross margin and replaces a fixed lifespan with churn, which gives the gross profit a customer leaves behind. Corporate Finance Institute shows the same split: its worked example gives $640 on revenue and $128 once a 20% profit margin is applied (CFI: Lifetime value calculation). The mobile model uses revenue per daily active user, the unit app teams already report.
Analytics tools usually report the revenue version. Google Analytics 4 treats LTV as a revenue metric that covers all of a user's data since their first visit. GA4 can show it as a total, an average or percentiles (GA4 Help: User lifetime). That figure is useful for comparing acquisition sources, but it is gross revenue to date. Convert it to margin before you set an acquisition budget from it.
Three LTV models and when each fits
The lifetime value calculator above offers three models. The table compares the inputs each one needs, what the result represents and the situation it suits. Use it to pick the LTV calculation formula that matches the data you actually have.
| Model | Formula | Result represents | Best fit |
|---|---|---|---|
| Simple (historic) | AOV × purchases per year × lifespan in years | Revenue per customer | Ecommerce with clean order history |
| Margin-adjusted (churn-based) | (AOV × purchases per year × gross margin) ÷ annual churn rate | Gross profit per customer | Acquisition budgets and LTV:CAC |
| Mobile (ARPDAU) | ARPDAU × average lifetime in days | Revenue per user | Apps measured per daily active user |
With a $60 order, four purchases a year, 60% gross margin and 20% annual churn, the margin-adjusted model also gives $720. That is 60 × 4 × 0.6 = $144 a year, divided by 0.2. The two models agree here only because of these inputs. Change the margin or the churn and they part ways. For an app, an ARPDAU of $0.20 over an average lifetime of 400 days gives an LTV of $80. Google AdMob describes mobile app LTV the same way, as the cumulative revenue a user generates since installing, from in-app purchases, ads and subscriptions (AdMob Help: Understand lifetime value).
Inputs that make or break an LTV estimate
The LTV formula itself is simple. The inputs are where an estimate goes wrong, so check these before you put the result in a plan:
Lifespan or churn from real cohorts: an assumed three-year lifespan with no cohort data behind it is a guess. Measure churn from customers who joined long enough ago, or use the retention rate calculator on a recent period.
Revenue or margin: if the number will be set against acquisition cost, use the margin-adjusted model or apply gross margin to the revenue figure.
Segments: a blended LTV across small and large customers describes an average customer who may not exist. Calculate LTV per segment or channel when they behave differently.
Stable conditions: all three models assume the future looks like the recent past. After a price or product change, older data stops describing current customers.
Once the estimate holds up, put it next to acquisition cost. The LTV:CAC ratio calculator divides it by CAC and shows whether each new customer is likely to be worth what you paid to win them.
When to use LTV
Use LTV when you size how much you can afford to spend to acquire a customer or compare the value of segments, channels or cohorts. It also feeds the LTV:CAC ratio and payback calculations. Always note which model produced the figure. A revenue LTV and a margin-adjusted LTV for the same customers can differ several times over, and mixing them in one comparison gives a wrong answer.
Where LTV misleads
All three models assume churn, order value and margin stay where they were, so in a business whose retention is still moving the estimate lags reality. None of them discounts future revenue for the time value of money, so a long lifespan inflates the figure. Feeding a revenue-based LTV into a spending decision overstates how much room you have.
Guides on this topic
Frequently Asked Questions
What is customer lifetime value (LTV)?
Customer lifetime value (LTV) is an estimate of the revenue or gross profit a customer brings in over the whole time they remain a customer. It is modeled from inputs such as average order value, purchase frequency, lifespan or churn, which is why more than one formula exists. A simple model built from order history describes revenue. A margin-adjusted model describes what remains after the costs in gross margin. Neither predicts what one specific customer will be worth. Both describe an average across a group, and both are only as reliable as the data and assumptions behind them.
Which LTV model should I use?
If the result will feed an acquisition budget or the LTV:CAC ratio, use the margin-adjusted model, since it counts gross profit and derives lifespan from churn. If you need a quick, backward-looking estimate from order history, the simple model needs fewer inputs, but it overstates value for any business with real cost of goods. If you run a mobile app and track revenue per daily active user, the ARPDAU model fits that data without forcing it into an order-based formula.
Is LTV the same as CLV?
LTV vs CLV is mostly a naming question. LTV (lifetime value) and CLV or CLTV (customer lifetime value) are used interchangeably in marketing, finance and analytics, and neither label implies a specific formula. Some sources use CLV for one customer's value and LTV for the average across a customer base, but that convention is not applied consistently. What matters more is the model and inputs behind the number. A CLV built from revenue and an LTV built from margin cannot be compared, whatever each one is called.
What is a good LTV?
There is no universal good LTV, because the number only means something next to what it costs to acquire that customer and how fast the value arrives. A $720 LTV is excellent against a $50 CAC and worrying against a $700 one. Compare it with CAC as a ratio, and check the CAC payback period to see when the cost actually comes back. LTV benchmarks published online do not always say which model produced them, so they are hard to compare with your own figure. Your own trend by cohort, calculated the same way, is a safer reference.
How far back should I look when estimating LTV?
Far enough to see a representative cohort through most of its lifecycle, and not so far that pricing, product or audience has changed since. For the simple model, use order history from customers who joined long enough ago that most have already reached a typical lifespan. A recent cohort is still active, so its final lifespan is unknown. For the margin-adjusted model, take churn from a period long enough to smooth month-to-month noise and recent enough to reflect current retention. After a major pricing or product change, start the measurement again.
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