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Player Retention Player Lifetime Value Estimator

The Player Retention Player Lifetime Value Estimator estimates gross-margin-adjusted player lifetime value from monthly average revenue per user (ARPU) and a constant monthly retention rate. It is intended for live-service teams analyzing retained-player behavior evaluating a retained player cohort when a simple cohort model is more useful than a full predictive revenue system.

The model treats retention as a repeating month-to-month survival probability. From that rate it estimates the expected number of active months, then multiplies that lifetime by monthly ARPU and gross margin. This lets teams see how retention and monetization interact: small changes in sustained retention can materially extend expected lifetime, while gross margin keeps the result focused on value retained after variable costs. Because real cohorts often change behavior over time, the estimate works best as a scenario benchmark rather than a precise forecast of future cash flow.

Lifetime value assumptions

/month
%
%
Result
—
Estimated player lifetime value
Expected active lifetime—
Gross profit per active month—
Implied monthly churn—

1. Enter monthly ARPU
Use average monthly revenue per active player for the cohort or segment you want to evaluate.

2. Set gross margin
Enter the percentage of revenue remaining after the variable costs you want the LTV model to exclude.

3. Enter monthly retention
Use the share of active players expected to remain active into the next month. Keep the period consistent with ARPU.

4. Review expected lifetime
The calculator converts constant monthly retention into an expected active lifetime in months.

5. Compare LTV scenarios
Use the main result to compare monetization, margin, or retention assumptions on the same basis.

Expected lifetime (months) = 1 ÷ (1 − r) LTV = Monthly ARPU × Gross margin × Expected lifetime

r is the monthly retention rate expressed as a decimal. Gross margin is also converted from percent to decimal. This geometric model assumes the same retention probability every month and does not discount future cash flows. Retention must be below 100%, because a constant 100% rate implies an unbounded lifetime in this simplified model.

What the result means

The result estimates how much gross-margin-adjusted value one player generates over a modeled lifetime when ARPU and retention remain constant.

Real player cohorts can have changing retention, monetization, reactivation, and discount rates. Use a cohort model when those dynamics materially affect the decision.

Given
Monthly ARPU = 12
Gross margin = 70%
Monthly retention = 80%

Calculation
Expected lifetime = 1 ÷ (1 − 0.80) = 5.00 months
Gross profit per active month = 12 × 0.70 = 8.40
LTV = 8.40 × 5.00 = 42.00

Result
Estimated player lifetime value is 42.00 value units on the same currency basis as ARPU. The figure is a scenario estimate under constant retention, not a discounted cash-flow forecast.

How should I interpret the LTV result?

It is the estimated gross-margin-adjusted value generated over the player’s modeled active lifetime. Compare it with acquisition, incentive, or servicing costs only when those costs are measured on a compatible basis.

Can I use weekly retention with monthly ARPU?

No. The retention period and revenue period should match. Convert both to the same time interval before using this simplified formula.

Why is retention capped below 100%?

The formula uses 1 ÷ (1 − retention). At 100% the denominator becomes zero, which would imply an infinite lifetime under the constant-retention assumption.

Does this account for declining ARPU over time?

No. It assumes the same average ARPU and margin each active month. For cohorts with strong aging effects, use a period-by-period cohort model instead.

How is this different from revenue per player?

Revenue per player describes value over a specified observed period. LTV extends that concept across an estimated future lifetime using retention and margin assumptions.

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