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Written by MetricKit EditorialReviewed by MetricKit Editorial ReviewUpdated 2026-05-26

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Cohort LTV Forecast Calculator

Name: Cohort LTV Forecast Calculator
Author: MetricKit Editorial

Estimate cohort-based LTV using churn, expansion, gross margin, and optional discounting.

Simple LTV formulas can be misleading when churn changes over time or when expansion meaningfully offsets churn. A cohort-style forecast is a better planning tool.

This calculator models expected gross profit from a cohort over time using constant monthly churn and expansion assumptions, and can apply a discount rate to compute discounted LTV.

Use discounted LTV for planning decisions and undiscounted LTV for intuition. The gap between the two helps show how much timing matters.

Prefer an explanation- Read the guide.

Cohort LTV forecasting: churn, expansion, discounting (practical model)LTV guide: formula, customer lifetime, cohort models, and LTV:CAC Retention curves: how to read them and why they matter Two-stage churn: modeling early drop-off vs steady-state retention

ARPA (monthly)

Gross margin

Monthly logo churn

Churn as % of customers lost per month (not revenue churn).

Monthly expansion (existing accounts)

Expansion on surviving accounts (e.g., upgrades, seats).

Months to forecast

Annual discount rate (optional)

Used to discount future cash flows; set 0 to disable.

Tip: you can type commas (e.g., 10,000).

Next action

Stress-test the cohort before trusting the headline LTV

A forecasted LTV is most useful when it survives sensitivity checks on churn, expansion, and timing. If the discounted and undiscounted results diverge a lot, the next decision is usually about retention quality, not just scale.

Read the cohort LTV forecasting guide Compare with LTV:CAC

Example

Using the default inputs, the result is:

$22,535.28

ARPA (monthly): $800
Gross margin: 80%
Monthly logo churn: 2%
Monthly expansion (existing accounts): 1%
Months to forecast: 60
Annual discount rate (optional): 12%

How to calculate

Enter ARPA and gross margin to get gross profit per account per month.
Set monthly logo churn and expansion rate assumptions for the cohort.
Choose a horizon (e.g., 36-60 months) and an optional annual discount rate.
Use the discounted LTV for planning and the undiscounted LTV for intuition.

Formula

Expected revenue_t = ARPA * (1+expansion)^(t-1) * (1-churn)^(t-1); LTV = sum gross_profit_t (optionally discounted)

Uses constant monthly churn and expansion assumptions.
Expansion is applied to surviving accounts' revenue each month.
Outputs are per original account in the cohort (expected value).

Benchmarks

There is no universal 'good' cohort LTV number without CAC, payback, and segment context.
A large gap between discounted and undiscounted LTV usually means time-to-value matters more than the headline suggests.
If month-12 retention is weak, a high long-horizon LTV estimate usually deserves a harder sensitivity check.

FAQ

Is this better than LTV = ARPA * margin / churn-

Often yes for planning. The simple churn formula assumes constant churn and no expansion and can be very sensitive to small churn changes. Cohort-style forecasts are easier to scenario test and extend with discounting.

What discount rate should I use-

Use your required return / cost of capital as a rough starting point (e.g., 8-20% annually). If you're comparing scenarios, keep the discount rate consistent.

Common mistakes

Mixing logo churn (customer count) with revenue churn (MRR dollars).
Using annual churn as a monthly churn input (time unit mismatch).
Forecasting far horizons without scenarios (small rate changes compound).
Treating a long-horizon forecast as certain instead of stress-testing churn, margin, and expansion assumptions.

How to interpret

Why this model is more decision-useful

This model is still simplified, but it separates churn, expansion, margin, and time horizon instead of hiding everything inside one blended shortcut.
That makes it more useful when retention changes over time or when expansion meaningfully affects cohort economics.
It is best used for scenario planning, not as a promise of what every cohort will do.

How to read the output

Use discounted LTV when you care about economically meaningful value, not just nominal lifetime revenue or gross profit.
Compare month-12 retention and horizon retention to see whether the model is leaning on a fragile long tail.
If small churn or expansion edits move LTV sharply, treat the output as a range and test best/base/worst cases before using it in CAC decisions.