← All tools
UA utility · Market allocation

UA geo budget planner.

Cheap installs can still be an expensive growth problem. Rank markets by what an install returns relative to what it costs — then fund them in that order.

For each market enter CPI, revenue per daily active user and expected active days per user over your LTV horizon, plus the most you can spend there before CPI climbs. Defaults are illustrative.

Your numbers

Budget allocated——
Installs / day—From allocated spend
Blended yield-to-cost—Allocated markets

—

Yield-to-cost by market
MarketCPILTV / installLTV ÷ CPIAllocatedInstalls
How it's calculated

The method, in plain terms.

  1. Projected LTV per install = ARPDAU × expected active days
  2. Yield-to-cost = Projected LTV ÷ CPI
  3. Allocate budget to markets with the highest yield-to-cost above your hurdle
Worked example

A market with a $2.40 CPI, $0.09 ARPDAU and 30 expected active days projects $2.70 of LTV — a 1.13× yield-to-cost. A $0.30 CPI market at $0.008 ARPDAU and 25 days projects $0.20: cheaper installs, but only 0.67×.

Defaults on this page are illustrative starting points, not benchmarks for your game. Replace them with your own numbers.

The thinking behind it
Terms on this page

Country tiers · CPI · Mix shift

Embed this calculator

Free to embed on your blog, wiki or course page with the credit link intact.

FAQ

Common questions.

How should I split a UA budget across countries?

Rank markets by the value an install is expected to generate relative to what it costs — yield-to-cost — and fund the best markets first, up to the spend each can absorb at that efficiency. Cheap installs are only a good deal if the market’s yield is not proportionally cheaper.

What is yield-to-cost?

Projected lifetime value per install divided by cost per install. Above 1.0 the market is expected to pay back within the LTV horizon you used; your hurdle should sit above 1.0 to cover uncertainty, platform fees if revenue is gross, and time value of money.

Where do expected active days come from?

From your retention curve: the average number of days a new user is active over the horizon you care about (for example 180 days). The DAU Forecaster and LTV Simulator on this site both estimate it from D1/D7/D30.

Why include a maximum daily spend per market?

Every market has a scale ceiling: past some spend level, CPI rises and quality falls. Capping each market at the spend its current CPI holds for keeps the plan honest; test the cap with marginal ROAS as you scale.

Calculator by The Game Scientist ↗