Customer Lifetime Value Calculator

Customer lifetime value—CLV, CLTV, or often simply LTV—estimates the value associated with an average customer relationship over time. A useful CLV calculator should make the value basis explicit, because a revenue estimate and a gross-profit estimate can differ substantially even when they describe the same customers.

How to use the Customer Lifetime Value Calculator

For an ecommerce or repeat-purchase business, choose Purchase behavior. Enter average order value, average purchases per customer per year, and average customer lifespan in years. The calculator estimates annual customer value, expected lifetime orders, and lifetime value.

For a recurring subscription with a reasonably stable customer churn rate, choose Subscription / churn estimate. Enter average monthly revenue per customer and monthly customer churn. This mode approximates expected customer lifetime as 1 divided by the monthly churn rate.

Then choose the value basis. Revenue CLV measures expected lifetime revenue. Gross-profit CLV applies your gross margin percentage so the output reflects gross profit rather than top-line revenue. Gross-profit CLV is still not net profit because operating and other expenses may remain.

You can optionally enter CAC to display a simple CLV:CAC ratio. The calculator does not impose a universal pass/fail benchmark because useful thresholds depend on margin basis, payback timing, retention, cash constraints, growth stage, and business model.

What is customer lifetime value?

CLV estimates the economic value associated with the relationship between a customer and a business over the customer's active lifetime. It shifts analysis from one transaction to the repeat behavior and duration of the relationship.

Depending on the model, “value” may mean revenue, gross profit, contribution profit, or a discounted estimate of future cash flows. Those are not interchangeable. Whenever CLV is quoted, the first question should be: what exactly is included in the value?

The calculator uses transparent simplified models designed for planning and comparison. More advanced predictive CLV systems can incorporate cohort retention curves, customer-level probability models, discount rates, future margin changes, and uncertainty.

Purchase-behavior CLV formula

A common ecommerce-style revenue formula is:

If average order value is 50, customers buy four times per year, and the relationship lasts three years on average:

The same inputs imply 12 expected lifetime orders and 200 of average annual customer revenue.

Understanding AOV, purchase frequency, and lifespan

Average order value (AOV) is average revenue per order. A common calculation is total relevant revenue divided by the number of orders in the same scope.

Purchase frequency is the average number of purchases made by a customer during a defined period. This calculator asks for purchases per customer per year so the time unit matches the lifespan field.

Average customer lifespan is how long customers remain economically active, on average. For non-contractual ecommerce businesses, defining when a customer has truly become inactive can require a business rule or cohort analysis rather than a simple cancellation date.

Time units must be consistent. Four purchases per month multiplied by a lifespan entered in years would overstate value unless frequency is first converted to a yearly rate.

Revenue CLV vs gross-profit CLV

Revenue CLV answers: how much revenue is the customer relationship expected to generate? Gross-profit CLV goes one step further by applying gross margin:

If revenue CLV is 600 and gross margin is 65%, gross-profit CLV is 390.

This distinction matters when comparing CLV with acquisition cost. A revenue-based lifetime value can make customer economics appear more generous than a profit-based measure because it has not accounted for COGS.

Even gross-profit CLV is not necessarily contribution profit or net profit. Payment processing, customer service, fulfillment classification, returns, discounts, overhead, taxes, and other expenses may sit outside the gross-margin figure used.

A simplified subscription CLV using churn

For a subscription business with a relatively stable churn probability, a simple model estimates customer lifetime from churn:

With 5% monthly customer churn, the simplified expected lifetime is 1/0.05 = 20 months. If monthly revenue per customer is 80:

At a 70% gross margin, the gross-profit version is approximately 1,120.

The churn rate must use the same time period as the revenue input. Monthly revenue should be paired with monthly churn; annual revenue with annual churn.

Why 1/churn is useful but limited

The 1/churn shortcut is not a universal prediction rule. It assumes a stable churn probability from period to period. Real subscription cohorts often have higher early churn, lower mature-customer churn, seasonal effects, reactivation, plan changes, expansion revenue, downgrades, and changing prices.

A churn rate of zero also makes 1/churn undefined. That does not mean customer value is literally infinite; it means this simplified model cannot infer a finite lifetime from a zero observed churn rate.

For important forecasting, cohort survival analysis or a model based on actual retention curves can be more informative than assuming constant churn forever.

Customer lifetime value and CAC

CLV is often compared with customer acquisition cost because acquisition economics depend on how much value acquired customers later generate.

If gross-profit CLV is 450 and CAC is 150, the ratio is 3:1. The arithmetic is simple; interpretation is not.

A ratio based on revenue CLV should not be casually compared with one based on gross-profit CLV. CAC also needs a consistent definition: paid-media-only CAC and all-in blended CAC answer different questions.

Timing matters too. Two businesses with the same eventual CLV:CAC can have different cash requirements if one earns value back in three months and the other takes three years.

Historical CLV vs predictive CLV

Historical CLV summarizes value already observed from customers. It is grounded in realized transactions but may understate still-active customers whose relationships have not ended.

Predictive CLV estimates future value. It is more useful for forward-looking acquisition and retention decisions but depends on model assumptions about future behavior.

The formulas on this page are simplified predictive planning estimates when lifespan or churn is used to project future activity. They should not be mistaken for guaranteed future cash flows.

Why one company-wide CLV can hide important differences

Customers acquired from different channels, products, geographies, cohorts, or campaigns can have very different repeat behavior and margins. A single blended CLV may hide that variation.

For example, one channel may acquire customers cheaply but attract mostly one-time buyers, while another has a higher CAC but brings customers who purchase repeatedly for years. Segment-level CLV can reveal differences that average order value or first-order ROAS cannot.

When comparing segments, use consistent definitions and enough data to avoid overreacting to small samples.

Worked customer lifetime value examples

What can increase or decrease CLV?

CLV can rise if customers spend more per order, purchase more frequently, remain active longer, or generate a higher gross margin. It can fall when discounts reduce realized order value, repeat purchase behavior weakens, churn rises, product mix shifts toward lower-margin items, or relationships shorten.

That decomposition is useful because “increase CLV” is not one action. Improving average order value, retention, purchase frequency, and margin require different operational strategies.

Changes should be evaluated for quality as well as magnitude. A promotion that raises purchase frequency but destroys margin may increase revenue CLV while reducing gross-profit CLV.

Common CLV mistakes

Calling revenue CLV profit. Revenue and gross-profit value are different metrics.

Mixing time units. Purchase frequency and lifespan must use compatible periods; subscription revenue and churn must use the same period.

Using 1/churn when churn is zero. The shortcut is undefined and cannot produce a finite lifetime estimate.

Assuming churn is constant forever. Real cohorts often have changing retention behavior.

Comparing CLV:CAC ratios built from different definitions. Revenue CLV versus gross-profit CLV or paid CAC versus blended CAC can materially change the ratio.

Using one blended CLV for every customer segment. Different cohorts can have different order values, margins, retention, and frequency.

Treating estimated CLV as guaranteed cash flow. It is an estimate based on historical behavior and assumptions.

Frequently asked questions

What is the basic CLV formula?

A common repeat-purchase formula is Average Order Value × Purchase Frequency × Average Customer Lifespan.

Is CLV the same as LTV?

They are commonly used to mean the same general concept. CLV emphasizes customer lifetime value; LTV is a shorter lifetime-value label.

Should I calculate CLV from revenue or profit?

Both can be useful, but label the basis clearly. Revenue CLV measures lifetime revenue; gross-profit CLV applies gross margin and is closer to product-level economic value.

How do I estimate subscription CLV from churn?

Under a simplified stable-churn assumption, expected lifetime periods are approximately 1/churn rate, so revenue CLV is approximately revenue per customer per period divided by churn rate.

What if churn is 0%?

The 1/churn model becomes undefined. Do not interpret that as truly infinite CLV; use a finite observed horizon or a more appropriate retention model.

Can I compare CLV with CAC?

Yes, provided the value and acquisition-cost definitions are compatible. Enter CAC optionally to calculate the simple CLV:CAC ratio.

Does this calculator discount future cash flows?

No. These are simplified undiscounted planning models. More advanced financial CLV models may apply discount rates to expected future cash flows.

Is there one good CLV or CLV:CAC target?

No universal target applies to every business. Margin, payback timing, retention risk, capital needs, growth strategy, and metric definitions all affect interpretation.