What are your customers’ future cash flows worth?
Follow a worked example from customer retention and spending to lifetime value, then connect those customer economics to the value of the whole business.
Two recurring revenue businesses can have the same sales today and very different values. The difference often starts with who stays, how much those customers spend, and what it costs to keep serving them.
Customer lifetime value gives those drivers a financial meaning. It can help you evaluate a SaaS company, membership business, subscription service, or other operation with repeat customer revenue. To turn LTV into business value, you also need future acquisition costs, overhead, taxes, reinvestment, and the timing of cash flows.
All figures below are hypothetical teaching assumptions, not industry benchmarks, a real company valuation, or a recommended purchase price. Dollar amounts are USD. Calculations use unrounded monthly values; displayed amounts are rounded.
LTV should reflect what a customer contributes.
A customer who spends $5,000 does not necessarily create $5,000 of value. Hosting, fulfillment, payment processing, support, and other costs of serving that customer consume part of the revenue.
Revenue LTV
Expected revenue across the customer relationship. Useful for understanding spending, but it leaves out the cost of earning that revenue.
Contribution LTV
Expected revenue less the direct costs of serving the customer, discounted to today. In this article, it is measured before acquisition cost and fixed overhead.
A common shortcut is monthly revenue per customer × margin ÷ monthly churn. It relies on a stable churn rate, stable spending and margin, and an indefinite, undiscounted customer life. A month-by-month calculation is more useful when those assumptions do not fit.
Define the horizon. Our example calculates a 60-month contribution LTV. It excludes customer cash flows after Month 60, so it is a five-year customer value estimate rather than an unlimited lifetime estimate.
Churn is the change in retention from one period to the next.
A cohort is a group of customers acquired in the same period. Its retention curve shows the share of that original group still active at each customer age. Keep customer age separate from calendar time: customers acquired in October start at Month 1, even if the business forecast is already in Year 3.
The reverse also works: current retention = previous retention × (1 − churn). If your model accepts a retention curve, derive churn from that curve. Entering an unrelated churn assumption as well can make the forecast contradict itself.
Example: difficult onboarding, then a more durable customer base
| Customer age | Monthly churn |
|---|---|
| Months 1–3 | 6% |
| Months 4–12 | 3% |
| Month 13 onward | 1% |
This produces 63.1% retention after 12 months. A constant monthly churn rate of approximately 3.76% produces the same first-year retention. After five years, however, the age-based curve retains 39.0% of the original customers versus only 10.0% under constant churn.
The same Year 1 result can hide a different future
View retention chart values
| Months elapsed | Age-based curve | Constant churn |
|---|---|---|
| 0 | 100.0% | 100.0% |
| 3 | 83.1% | 89.1% |
| 12 | 63.1% | 63.1% |
| 24 | 56.0% | 39.9% |
| 36 | 49.6% | 25.2% |
| 60 | 39.0% | 10.0% |
A flattening curve needs evidence. Early departures may leave a more committed group of customers, but a small sample or short history can create the same appearance. Annual contracts can also create sharp renewal drops instead of smooth monthly losses. Use the pattern supported by the business.
Keeping the customer is only half of the revenue equation.
Surviving customers might add seats, upgrade plans, increase usage, or accept price increases. They might also downgrade, use less, or move to discounted contracts. Model average spend per active customer at each age, alongside retention.
Start with 1,000 customers paying $100 per month. Use the age-based retention curve above and increase spending among active customers by 0.5% per month, about 6.2% compounded annually.
| Billing month | Active customers | Spend per active customer | Cohort monthly revenue |
|---|---|---|---|
| 1 | 1,000 | $100.00 | $100,000 |
| 4 | 831 | $101.51 | $84,311 |
| 13 | 631 | $106.17 | $67,038 |
| 25 | 560 | $112.72 | $63,087 |
| 37 | 496 | $119.67 | $59,368 |
| 60 | 394 | $134.21 | $52,842 |
Customers active at the start of a month receive a full month of service; that month’s churn occurs after service. Cash is modeled at month-end. Thus billing Month 13 uses retention after 12 completed months. Fractional customer counts are expected values, rounded here for display.
Spending changes the revenue generated by the same retention curve
Logo retention and revenue retention are different. At billing Month 13, 63.1% of the original customers remain, while their $67,038 of monthly revenue is 67.0% of the initial $100,000. That is the cohort’s net revenue retention over those 12 months. NRR includes expansion and contraction; gross revenue retention excludes expansion. New-customer revenue belongs outside both measures.
Also check what caused average spend to rise. If low-spending customers leave first, average spend among survivors can increase without anyone upgrading. Segmenting customers by plan or size helps distinguish that mix effect from actual expansion.
SmartHelping’s Dynamic Customer Spend and Retention Curves model combines monthly acquisitions with retention and spending by customer age across a 60-month framework. It is a focused customer and revenue forecasting tool.
Explore the Customer Spend & Retention Model →The same starting price can lead to very different LTVs.
Assume an 80% contribution margin after direct customer service costs and a 12% effective annual discount rate. Discount each month separately using the equivalent monthly rate of approximately 0.9489%.
Discounted 60-month contribution LTV
Using the full retention curve instead of constant churn increases estimated LTV from $1,603 to $2,122 with flat spending. Adding 0.5% monthly spending growth raises it to $2,385. If spending falls 0.5% monthly instead, LTV drops to $1,900.
A positive result does not establish that the business is profitable or that rapid growth is affordable. Acquisition spending often occurs before the customer’s later contributions arrive. Check payback timing and the cash needed to fund growth. If higher spending requires more support or computing resources, revise the margin too.
See the calculation convention
Let S(a) be retention after a completed months, with S(0) = 1. For billing month t, starting at 1, spend in the expansion case is $100 × 1.005^(t − 1). The calculation is: 60-month LTV = SUM, for t = 1 through 60, of [S(t − 1) × $100 × 1.005^(t − 1) × 80% ÷ 1.12^(t/12)]. Replace 1.005 with 1 for flat spend or 0.995 for declining spend. The constant-churn comparison uses S(a) = (1 − 3.7588588%)^a. CAC is paid at acquisition; customer contribution is received at month-end.
Value the remaining customer cash flows, then the cost of running the company.
Multiplying every current customer by new-customer LTV mixes together different starting points. Existing customers have already generated part of their revenue, incurred their original acquisition cost, and reached different ages on the retention curve.
Value only their future contribution, conditional on being active today. For a customer aged a months, the chance of remaining active another k months is S(a + k) ÷ S(a). Historical CAC is already spent; include future retention and service costs where they belong.
A simplified business built from those customer economics
| Assumption | Example |
|---|---|
| Active customers today, all aged 12 completed months | 1,000 |
| Starting spend for these existing customers | $106.17/month |
| New customers acquired each month | 25 |
| Acquisition cost per new customer | $500 |
| Contribution margin after direct service costs | 80% |
| Fixed cash operating costs, including management | $30,000/month |
| Capital spending; depreciation assumed equal | 2% of revenue |
| Illustrative cash tax rate on positive operating profit | 25% |
| Change in net working capital | $0 |
| Annual discount rate / terminal cash-flow growth | 12% / 2% |
The existing 1,000 customers are a separate starting population from the 1,000 new customers in the earlier cohort illustration. They have already survived the first year. Their future monthly churn is 1%; their spending continues to grow 0.5% monthly. New customers start at $100 and follow the entire 6% → 3% → 1% churn sequence.
For the first five forecast years, add the contribution from both groups and subtract acquisition spending, overhead, cash taxes and capital spending. Sales costs included in CAC are excluded from overhead so they are not counted twice.
View the resulting annual cash flows
| Forecast year | Revenue | Free cash flow before debt payments |
|---|---|---|
| Year 1 | $1,406k | $440k |
| Year 2 | $1,586k | $545k |
| Year 3 | $1,744k | $638k |
| Year 4 | $1,893k | $725k |
| Year 5 | $2,034k | $807k |
Taxes equal 25% of positive operating profit after depreciation. Capital spending equals depreciation; there is no assumed working capital change. All monthly business cash flows, including acquisition spending, are modeled at month-end. The valuation uses monthly discounting; annual totals are shown here for readability.
| Value bridge, in today’s dollars | Present value |
|---|---|
| Existing customers: contribution within Years 1–5 | $3.395m |
| Future customers: contribution within Years 1–5 | $1.758m |
| Future customer acquisition costs | −$0.570m |
| Fixed operating costs | −$1.368m |
| Cash operating taxes | −$0.772m |
| Capital expenditure | −$0.129m |
| Present value of Years 1–5 free cash flow | $2.315m |
| Present value of cash flows after Year 5 | $4.671m |
| Illustrative enterprise value | $6.987m |
| Excess cash | $0.200m |
| Debt | −$0.700m |
| Illustrative equity value | $6.487m |
The existing customers contribute approximately $3,395 each in discounted contribution over the next 60 months, compared with $2,385 for a newly acquired customer’s first 60 months. The surviving customers enter at a higher spend and a lower churn rate. This is why the age and quality of the current customer base matter.
Keep the value after Year 5 visible
Year 5 free cash flow is about $807,103. To complete the example, assume the business transitions to sustainable 2% annual growth in total free cash flow after Year 5, with the necessary acquisition, service, overhead, tax and reinvestment costs reflected in that cash flow.
About 67% of this valuation comes from cash flows after Year 5. The 2% terminal growth assumption is a separate mature-business scenario, not a result proven by the retention curve. With 0% terminal growth and the same five-year forecast and discount rate, enterprise value falls to approximately $6.132 million. If the business has not stabilized, extend the explicit forecast before applying a terminal formula.
Avoid double counting: a customer acquired in forecast Month 60 contributes only that month’s cash flow to the explicit forecast. The later contributions belong in terminal value. Do not add that customer’s full 60-month LTV and then add terminal value for the same cash flows.
Enterprise value measures the operating business. Adding $200,000 of excess cash and subtracting $700,000 of debt produces approximately $6.487 million of equity value in this example. Actual transactions may require other debt-like, working capital, or non-operating adjustments. The discount rate and long-run assumptions must fit the company’s risk.
Use customer history to test the assumptions.
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Define an active customer consistently.
Use customer IDs, start dates, subscription status, cancellations, renewals, revenue and service costs. An annual subscriber with no payment this month has not necessarily churned. For non-contractual repeat purchasing, define inactivity carefully; a gap between orders may not be permanent loss.
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Compare cohorts at the same age.
Group customers by first paid month. A cohort that is only three months old has no observed Month 12 result: leave that cell blank. Do not treat unobserved months as zero retention. Calculate age-specific loss rates from customers actually observed and at risk of leaving.
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Separate meaningful customer groups.
Review acquisition channel, plan, company size and contract term where sample sizes allow. Weight churn by customers at risk, rather than taking a simple average of percentages. For average LTV, weight segment values by the expected acquisition mix or the current customer mix, as appropriate.
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Check the shape and the tail.
Look for onboarding losses, renewal cliffs, seasonality, reactivations and differences between recent and older cohorts. A permanent-churn survival curve cannot rise; track reactivations separately. Mark where observed history ends and forecast assumptions begin, and stress-test the unobserved tail.
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Reconcile the forecast to financial results.
Match cohort revenue to the accounts and connect direct costs, acquisition spending, staffing, working capital and investment needs. Test higher mature churn, lower spend, higher CAC and higher overhead, then compare actual results with the forecast.
SmartHelping’s Customer Cohort Modeling template analyzes up to five years of customer transaction history, with retention, churn, spending and LTV views. Use the results to investigate patterns, and reconcile transaction activity with actual subscription status for your business.
Explore the Historical Customer Cohort Model →Move from customer behavior to a complete forecast.
Choose a template based on the question you need to answer. A retention-and-revenue tool can supply the customer forecast; a full business model adds the costs, financing and valuation framework.
SaaS Pricing & Sensitivity Simulator
Compare customer configurations, retention, renewal expansion, support costs, discounted LTV, CAC and payback. Useful for testing whether a pricing or service change improves customer economics.
Explore the Pricing & LTV Simulator →Rolling SaaS Revenue Forecast
Build a five-year monthly revenue forecast from existing cohorts and new additions across four tiers, including customer age, contract terms and retention assumptions.
Explore the Rolling Revenue Forecast →B2B / B2C SaaS Financial Model
Connect pricing tiers, contracts and renewals with staffing, financial statements, financing, DCF and exit analysis. Review the walkthrough to confirm its operating logic matches your business.
Explore the Full SaaS Financial Model →SaaS & Recurring Revenue Models
Browse financial models and customer-analysis tools for subscription and recurring revenue businesses. Compare the retention, spending and cost structure before choosing your starting point.
Browse the SaaS & Recurring Revenue Collection →The numerical example in this article is independently calculated for illustration. Individual templates have different structures and features; they do not all reproduce this exact example without adaptation.
Methodology and further reading
The charts and financial example are original illustrative calculations. They assume permanent customer churn with no reactivation, monthly service periods, constant contribution margin, and the timing stated above. Existing customers in the business forecast continue along the mature retention and spending assumptions through customer age 72; the new-customer LTV comparison stops after 60 billing months.
For background on grouping subscribers by start date and weighting cohort metrics, see ChartMogul’s cohort analysis documentation. Its net MRR retention documentation explains how revenue retention incorporates customer spending changes.
For the underlying discounted cash flow framework, see Aswath Damodaran’s introduction to valuation. Customer-level contribution is an operating building block; enterprise value requires cash flows after corporate costs, operating taxes and reinvestment, before financing payments.
