Customer lifetime value can be calculated using different formulas depending on the business model and the level of sophistication required. A simple formula is average purchase value multiplied by average purchase frequency multiplied by average customer lifespan. If customers spend an average of £50 per transaction, make six transactions per year and remain customers for four years, estimated lifetime revenue is £1,200. This is a revenue-based calculation and does not account for gross margin, servicing costs or the time value of money. A more economically meaningful calculation can replace revenue with gross profit or contribution margin and can incorporate retention probabilities and discounted future cash flows.
For subscription businesses, a simplified LTV formula is often based on average revenue per customer, gross margin and expected customer lifetime. If average monthly revenue is £100, gross margin is 80 percent and expected customer lifetime is 30 months, a simple gross-profit LTV would be £100 multiplied by 30 multiplied by 80 percent, producing £2,400. Another common approximation uses average revenue per account multiplied by gross margin divided by customer churn rate, where the assumptions are compatible with the chosen measurement period. Such formulas are simplifications and can become inaccurate when churn varies materially over time, expansion revenue is significant or customers have different retention patterns.
Customer lifetime can be estimated using observed retention or churn. If the relevant period's churn rate is stable and the model assumes a constant hazard, an approximate expected lifetime can be derived from the reciprocal of the churn rate. For example, a monthly churn rate of 5 percent gives a simple expected-lifetime approximation of 20 months under a particular constant-churn assumption. This does not mean every customer remains for exactly 20 months. It represents an expected value under the mathematical model. Real customer survival curves often change with tenure, and early-stage customers can churn at different rates from long-established customers, so cohort-based retention curves can produce better estimates.
A cohort approach calculates lifetime value from the actual behaviour of groups of customers acquired during a common period. The business can track how much revenue and gross profit each cohort generates over successive months or years and compare retention and purchasing behaviour. This approach can reveal whether newer customers are behaving differently from older customers. For example, a company may discover that a marketing channel produces high initial conversion but substantially lower retention, reducing long-term LTV. Cohort analysis can therefore be more informative than applying one average customer lifespan to every acquisition source.
A more advanced CLV model discounts future cash flows. If a customer is expected to generate £100 of contribution in one year and £100 in a later year, those future amounts are not economically identical to receiving £100 immediately. A discounted CLV model assigns probabilities to future retention and purchasing and discounts expected cash flows using an appropriate discount rate. Conceptually, the calculation is the sum of each future period's expected customer cash contribution multiplied by the probability that the customer remains active and then discounted to present value. This approach is more rigorous but requires more assumptions and reliable data.
The choice of economic measure matters. Revenue-based LTV is easy to calculate but can overstate economic value because it ignores direct costs. Gross-profit LTV subtracts direct costs associated with delivering the product or service and is often more useful for comparing with CAC. Contribution-based LTV can also deduct variable servicing or support costs. A business with £10,000 of customer lifetime revenue and 20 percent gross margin has approximately £2,000 of lifetime gross profit before further costs, while a business with the same revenue and 80 percent margin has approximately £8,000. The appropriate measure should therefore reflect the economic question being answered.
LTV should be calculated consistently with CAC and other unit economics. If CAC includes sales and marketing costs, LTV should not be compared casually with a measure that represents only gross revenue without acknowledging the difference. Likewise, if LTV is calculated before refunds but CAC is calculated after them, the resulting ratio can be distorted. Businesses should define customer, revenue period, gross margin, retention, refunds, expansion and cost treatment. Sensitivity analysis is useful because modest changes in churn, margin or purchase frequency can produce large changes in estimated lifetime value, especially when the assumed relationship lasts for many periods.
The practical calculation process is therefore to define the customer cohort and time period, select revenue or contribution as the value measure, determine purchase or subscription behaviour, estimate retention and future lifespan, account for gross margin and relevant variable costs, and discount future amounts where appropriate. The business should validate the model by comparing predicted customer behaviour with subsequent cohorts. For mature businesses, observed cohort data can provide strong evidence; for young businesses, estimates may depend heavily on assumptions. LTV is most useful when treated as a dynamic estimate that improves as customer behaviour becomes better understood rather than as a fixed accounting number.
