Customer lifetime value (CLV or LTV) estimates the economic value a customer generates over the relationship with a business. It supports acquisition budgets, retention strategy, segmentation and long-term profitability decisions. The result depends heavily on the chosen definition and assumptions.
Simple calculation approaches #
For a simple repeat-purchase business, a rough revenue-based estimate may be:
CLV ≈ average purchase value × purchase frequency × customer lifespan.
A contribution-based model replaces revenue with contribution per purchase or period and may account for gross margin and retention probability. A more advanced model discounts expected future cash flows and subtracts relevant service costs.
Example #
If a customer spends an average of ₹1,500 per order, purchases four times per year and remains active for three years, simple revenue-based CLV is ₹1,500 × 4 × 3 = ₹18,000. This is revenue, not profit. If contribution margin is 40%, the rough contribution before service and acquisition costs is ₹7,200.
Inputs to define #
- Average order or revenue per period.
- Purchase frequency and repeat behaviour.
- Retention or expected customer lifespan.
- Gross margin or contribution margin.
- Returns, discounts, servicing costs and discount rate when appropriate.
Using CLV responsibly #
Compare CLV with CAC using compatible cohorts, time horizons and cost definitions. A high average CLV can conceal low-value segments or large uncertainty. Use cohort analysis and periodically refresh assumptions as retention, pricing and product mix change.
Common mistakes #
- Calling revenue CLV “profit” without adjusting for margin and costs.
- Extrapolating a short observation window too confidently.
- Comparing CLV from one cohort with CAC from a different period or population.
- Ignoring churn, discounting, returns or customer-support costs.
Related: CAC Formulas, Marketing ROI and Marketing Metrics vs KPIs.
