CLTV Calculator — Customer Lifetime Value

How to use and interpret customer lifetime value

Customer lifetime value, often shortened to CLTV, CLV, or LTV, estimates the revenue generated by an average customer across the entire commercial relationship. This calculator uses the simple revenue model: average purchase value multiplied by annual purchase frequency, then multiplied by average customer lifespan. It is designed for a fast, transparent baseline rather than a discounted cash flow or profit model.

Enter the three operating assumptions

Average purchase value is the average revenue from one completed transaction. Use a consistent source period and divide total recognized customer revenue by the number of purchases in that period. Enter a non-negative U.S. dollar amount. A higher purchase value increases both annual customer value and CLTV in direct proportion. Common errors include mixing gross merchandise value with net recognized revenue, combining currencies, or including refunded orders without an offset.

Average purchase frequency is the average number of purchases made by one customer per year. For example, 2.5 means the typical customer buys two or three times annually. The value is required for a positive result and should use the same customer definition as the purchase value calculation. A higher frequency raises annual value, lifetime purchases, every projection row, and final CLTV. Avoid mixing monthly frequency with a field expressed per year; convert a monthly rate by multiplying it by 12.

Average customer lifespan is the average number of years between acquisition and the end of the active relationship. Decimal values are valid: 18 months equals 1.5 years. A longer lifespan increases lifetime purchases and CLTV but does not change annual customer value. Use a cohort-based estimate where possible instead of guessing from only current active customers, because incomplete cohorts can overstate lifespan. The calculator accepts values up to 200 years to prevent accidental extreme entries.

Read each result

Customer lifetime value is the primary result. It represents estimated lifetime revenue per average customer, not gross profit, contribution margin, or cash flow. A high value can support larger acquisition and retention budgets, but only after costs and timing are considered. A zero result means at least one required driver is zero or invalid. Negative values are rejected because the simple revenue model does not treat refunds or losses as negative purchase activity.

Average customer value is annual revenue per customer: average purchase value multiplied by annual purchase frequency. It isolates the yearly economics from customer longevity. Lifetime purchases is frequency multiplied by lifespan and indicates the expected number of transactions over the relationship. Monthly customer revenue converts annual customer value to a monthly run rate for planning. Projection rows reports how many periods appear in the schedule; the calculator uses monthly rows for lifespans up to two years, quarterly rows up to ten years, and annual rows beyond ten years.

Use the chart and projection table

The cumulative value chart starts at zero and ends at the calculated CLTV. Its line assumes revenue accumulates at a constant average rate. The legend and exact summary use the same calculated model as the headline result. The table provides the underlying period data: elapsed years, purchases during the period, period revenue, cumulative purchases, and cumulative value. The final row is prorated so it lands exactly on the entered lifespan and reconciles to the headline CLTV.

Actual purchasing is usually uneven. Seasonal businesses may earn most customer revenue in a few months, while subscription businesses can be more regular. Use the table as an average planning path, not a transaction forecast for an individual customer. For deeper measurement, Google Analytics documents user lifetime analysis, while Investopedia provides a broader lifetime value overview.

How assumption changes affect CLTV

• Raising purchase value by 10% raises annual customer value and CLTV by 10%, with frequency and lifespan unchanged.
• Raising purchase frequency by 10% produces the same 10% increase and also raises expected lifetime transaction count.
• Extending lifespan by 10% raises CLTV and lifetime purchases by 10% but leaves the annual value unchanged.
• Changing two drivers at once compounds the effect. A 10% increase in both purchase value and frequency raises annual value by 21%, not 20%.

Benefits, limits, and common mistakes

The simple CLTV model is useful because it is explainable, easy to audit, and suitable for comparing customer segments measured with the same method. It can help frame retention priorities, pricing experiments, and acquisition economics. Shopify's guide to customer lifetime value discusses practical uses in commerce.

Frequent mistakes include averaging unlike customer segments, using a purchase frequency from a different period, counting orders instead of unique customer transactions inconsistently, and assuming historical retention will continue unchanged. Recalculate by cohort or segment when customer behavior varies materially. The best input is not the most optimistic one; it is the one that can be traced to consistent source data and updated as new cohorts mature.