Estimate how monthly customer churn affects expected customer lifetime and revenue-based customer lifetime value, then review the movement of those metrics across a 24-month period.
The workbook is designed for SaaS and other recurring-revenue teams that want a consistent way to connect retention economics with customer revenue. Enter monthly churn and average monthly revenue per customer; the template calculates implied lifetime in months and customer lifetime value (CLTV) for each period, with chart views that make changes easier to interpret.
Translate churn into customer lifetime
Convert a monthly churn assumption into an implied number of months that a customer remains active.
Estimate revenue per customer relationship
Combine expected lifetime with average monthly revenue per customer to produce a comparable CLTV estimate.
Track changes across periods
Review monthly outputs and charts to see when retention or customer revenue is strengthening or weakening the result.
What does this template help you analyze?
The model focuses on the operating relationship between churn, customer lifetime, average monthly revenue, and lifetime value. It gives decision-makers a structured monthly view rather than relying on a single isolated CLTV figure.
Retention sensitivity: see how a lower or higher monthly churn rate changes implied customer lifetime.
Revenue contribution: assess how average monthly revenue per customer influences the resulting lifetime value.
Period comparison: compare CLTV and lifetime months across the displayed 24-month timeline.
Marketing context: use the calculated value as an input when reviewing how much the business can rationally spend to acquire a customer.
Growth-quality review: identify whether improvements in customer economics are coming from stronger retention, higher monthly revenue, or both.
What is inside the workbook?
The visible workbook structure separates editable operating assumptions from calculated metrics and visual outputs. The input view presents monthly data by financial year, while the output view reports customer lifetime and CLTV for the same periods.
Monthly inputs
Enter the monthly churn rate and average monthly revenue per customer for each displayed period.
Calculated outputs
Review the implied customer lifetime in months and the corresponding revenue-based customer lifetime value.
Chart-based review
Use the 24-month charts to compare CLTV and customer lifetime trends without scanning every row individually.
The monthly worksheet shows churn and average revenue assumptions alongside calculated lifetime months and customer lifetime value.
Connect operating assumptions to CLTV
The worksheet places the core drivers and results in one monthly view. Yellow cells identify the visible assumptions, while the calculated rows show how those inputs translate into expected customer lifetime and lifetime value. This layout helps users trace a change in the output back to its operating cause.
The chart view plots customer lifetime value and customer lifetime in months across 24 monthly periods.
Review the direction of customer economics
The paired charts make it easier to distinguish value changes from lifetime changes. When CLTV rises while lifetime is stable, the movement may be driven by average monthly revenue; when both move together, retention is likely contributing. The charts support a fast management review while the worksheet retains the underlying monthly detail.
How do you use the template?
Prepare monthly assumptions
Gather a consistent monthly churn rate and average monthly revenue per customer for the periods you plan to review.
Enter the operating data
Populate the corresponding monthly input cells, keeping the same measurement definition from one month to the next.
Review calculated lifetime and value
Check the implied customer lifetime in months and the revenue-based CLTV generated for each period.
Interpret the charts
Compare the 24-month patterns and investigate whether material changes are linked to retention, monthly revenue, or both.
Who is this template for?
This workbook is appropriate for SaaS founders, finance teams, revenue operators, growth leaders, and investors who need a transparent monthly CLTV calculation based on churn and customer revenue. It is especially useful for recurring-revenue businesses reviewing acquisition economics, retention performance, customer revenue assumptions, or changes in growth quality. Because the visible calculation is revenue-based, teams that require contribution-margin or profit-based lifetime value should treat this output as one component of a broader unit-economics analysis.
For a fuller acquisition-efficiency review, compare this output with the CAC to LTV Ratio Calculator. Teams refining the retention assumption can use the Annual Churn Rate Calculator, while the CAC Payback template helps evaluate how quickly acquisition spending is recovered. For a broader sales-efficiency perspective, the SaaS Magic Number template connects revenue growth with sales and marketing investment.
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