Project 01 · Live-Service · Economy Modeling
Game Economy Simulator: retention, monetization, and unit economics for a free-to-play title.
A working simulator that models a free-to-play game's player base day by day, then A/B-tests a pricing or product change against the unit economics a live-service team decides on.
Premise: a live-service game is run as an economy. Whether to raise a battle-pass price or ship a retention feature, the trade-off lands in LTV, payback, and revenue rather than intuition. Most decks describe these mechanics; few let you move the levers and watch the economics respond.
The tool simulates daily active users from a power-law retention curve, layers free-to-play conversion and ARPPU on top, and reports LTV, LTV/CAC, and payback against the 3x sustainability bar. A spender-concentration model shows how a thin band of whales drives most revenue, and every default is calibrated to published benchmarks (GameAnalytics 2025, Unity 2025, AppsFlyer 2024). Scenario B applies a price, conversion, or retention change, and the dashboard reads the net effect. North-star: LTV/CAC. Counters: payback days, ARPDAU, end-of-horizon DAU.