GameTech Financial Model Template

Know your player value before spending a dollar on ads.

Player value, retention, and monetization, modeled on real data from gaming companies.

Ready in under 5 minTrained on real market data1,000+ risk simulations
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What You Get

Every number is grounded in real benchmarks, not guesswork.

Built on real industry benchmarks
Full model in under 5 minutes
Revenue & profit projections
User retention analysis
Break-even timeline
1,000+ risk simulations
AI assistant for your model
Investor-ready report, Excel and PDF

How It Works

From idea to investor-ready projections, in minutes, not weeks.

1

Answer a few questions

Tell us your business type, market, and pricing. AI pre-fills realistic numbers based on real industry data.

2

Get your model instantly

A full financial projection appears in seconds, revenue, costs, profitability, and 1,000+ risk simulations.

3

Test, adjust, export

Change any assumption and see results update live. Download an investor-ready report when you're ready.

How the GameTech model works

The assumptions, benchmarks, and drivers behind your gametech projections.

The assumptions this template starts from

This template connects the chain that governs free-to-play economics: user acquisition spend to installs, installs to retained daily active users via a retention curve, and DAU to revenue via ARPDAU. Player LTV is modeled as ARPDAU multiplied by the sum of daily retention rates across a player's life, so the retention curve, not a flat lifespan assumption, does the heavy lifting. Monetization is treated as a blend across in-app purchases, ads, subscriptions, and battle passes rather than a single stream, matching how modern games actually earn.

Benchmarks that keep the numbers honest

ARPDAU typically ranges from about $0.01 to $0.05 depending on genre and monetization depth. Day-1 retention of 40%+ and Day-30 of 10%+ mark a strong title. On the acquisition side, a healthy LTV-to-CPI ratio is 1.5:1 or better measured at Day 180: at 1:1 you're breaking even with no room for overhead, below 1:1 every install destroys value, and above 2:1 you likely have room to scale UA harder. These thresholds are pre-loaded so a projection built on hero-title retention gets caught early.

What actually drives the outcome

In gaming, early retention is the master variable, it feeds both the DAU base that generates revenue and the LTV that justifies UA spend. A few points of Day-1 or Day-7 retention cascade through the entire cohort and can be the difference between a game that scales profitably and one that quietly burns its marketing budget. The model makes retention and ARPDAU the primary levers so you can see, before spending on ads, whether players will stick around long enough to pay back their install cost.

FAQ

Everything you need to know about gametech financial modeling.

How do I build a financial model for a mobile game?
Start with DAU/MAU projections, monetization mix (IAP, subscriptions, ads), and retention curves. Revenue Map generates ARPDAU projections and break-even analysis tailored to gaming economics.
What is a good Day-1 and Day-30 retention for mobile games?
Day-1 retention of 40%+ and Day-30 of 10%+ are strong benchmarks. Revenue Map models retention curves and shows how small improvements in early retention cascade into much higher LTV.
How do I calculate ARPDAU for my game?
ARPDAU is total daily revenue divided by daily active users. Revenue Map breaks this down by monetization source, IAP, subscriptions, and ads, so you can optimize each revenue stream.
How much should I spend on user acquisition for a mobile game?
UA spend should be recoverable within 90-180 days of a player's LTV. Revenue Map simulates different UA budgets and shows the ROI timeline so you avoid burning cash on unprofitable installs.
What monetization model works best for mobile games?
Hybrid models (IAP + ads + optional subscription) often outperform single-source monetization. Revenue Map lets you model all three simultaneously and find the optimal mix for your game genre.

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Real data. Real benchmarks. Your financial model, ready in minutes.

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