LTV (lifetime value), also called CLV or customer lifetime value, is the total profit or revenue a business expects to earn from one customer over the whole relationship, not just the first purchase. It tells you how much a customer is worth, and so how much you can afford to spend to win and keep one.
LTV and CLV mean the same thing. Subscription apps and SaaS teams tend to say LTV; retail and marketing textbooks more often say CLV.
How CLV is calculated
The quick version multiplies what a customer spends per order, how often they order, how long they stay, and your gross margin.
A more careful version discounts future money, because a dollar next year is worth less than a dollar today.
A widely used formula, popularized by Columbia professors Sunil Gupta and Donald Lehmann in their "Customers as Assets" work, applies when margin and retention stay roughly constant (formula as given here):
CLV = margin x (retention rate / (1 + discount rate - retention rate))
| Input | Example value |
|---|---|
| Annual margin per customer | $100 |
| Retention rate (share still a customer next year) | 80% |
| Discount rate (cost of capital) | 10% |
| CLV | $100 x (0.80 / (1 + 0.10 - 0.80)) = $100 x 2.67 = about $267 |
Retention has an outsized effect. Raise it from 80% to 90% in the same example and CLV becomes $100 x (0.90 / 0.20) = $450. That is why subscription businesses watch churn so closely.
Our subscription LTV calculator runs these numbers for you.
This formula is the wrong choice when margins grow over time, when retention changes sharply after the first months (common in apps), or when customers buy irregularly rather than renewing.
In those cases, build LTV from cohort data instead.
How LTV shows up in A/B testing
Most A/B tests measure a short-term metric such as conversion rate, because LTV takes months to observe.
The risk is that a variant wins on conversion but attracts customers who cancel sooner or spend less.
The reverse also happens: a variant can lose on conversion and still win on lifetime value.
Several tests in our database show this trade-off directly:
- Zumba sent paywall users to a web checkout instead of the native in-app purchase. Immediate conversions fell 25%, but LTV rose 17%.
- Teaching.com replaced a free trial with a 30-day money-back guarantee. Conversion was slightly lower, but revenue and LTV were higher (no exact figures were published).
- Wizz showed about half as many paywall prompts, at better moments. The primary offer flow rose 81% and LTV rose about 20%.
- Pepper tested a two-step paywall with a day-by-day trial timeline and reported +50% LTV.
The practical lesson: for pricing, trial, paywall and subscription tests, pick LTV (or a close proxy such as revenue per user after 30 or 90 days) as the primary metric before the test starts, and keep conversion rate as a secondary one.
Treat a reported lift in LTV with care when it comes from a short window, because early estimates often shift as cohorts age.
Related terms
- Conversion rate: the short-term metric LTV often trades off against.
- Lift: how test results, including LTV changes, are expressed.
- Average order value: one input to ecommerce CLV; see the AOV calculator.
- Churn and retention: covered in our guide to subscription metrics.
Browse more definitions in the glossary, or search every result in the test database.