UA Break-Even Calculator
Compare CPI against LTV to get payback period and your maximum profitable CPI.
Profit per install
$3.50
LTV : CPI ratio
2.40×
A healthy target is 3× or better.
Payback period
3.1 months
Max profitable CPI
$6.00
Spend above your LTV and every install loses money.
Paid user acquisition is profitable exactly when the lifetime value of an acquired user exceeds what you paid for them. This calculator makes the comparison explicit: enter your CPI (cost per install) and your LTV per install, and it returns profit per install (LTV − CPI), the LTV:CPI ratio, and — if you provide monthly revenue per user — the payback period: how many months until a cohort’s revenue covers its acquisition cost (CPI ÷ monthly net revenue per user).
It also answers the forward-looking question: your maximum profitable CPI. At a target LTV:CAC ratio of 3:1, max CPI = LTV ÷ 3; at pure break-even, max CPI = LTV. Knowing that ceiling before you enter an auction is the difference between bidding strategy and bidding hope.
How to find your UA break-even point
- 1
Enter your CPI — blended or per channel — and your LTV per install, on net revenue (after store commission).
- 2
Enter average monthly net revenue per user if you want a payback period.
- 3
Read the outputs: profit per install, LTV:CPI ratio, months to payback, and your max profitable CPI.
- 4
Set channel rules from the results: pause sources where CPI exceeds your max, and scale sources paying back inside your target window (3–12 months is the common range).
The break-even math: ratio, margin, and payback
Three numbers fall out of CPI and LTV. Profit per install = LTV − CPI is your unit margin; the LTV:CPI ratio expresses the same thing as efficiency, with 3:1 the classic health target and anything at or below 1:1 destroying money. Payback period = CPI ÷ (monthly net revenue per user) adds the time dimension: a $6 CPI against $1.50/month of net revenue pays back in 4 months, after which every further month of that user’s revenue is profit.
Use per-install LTV consistently — blended across payers and non-payers — since CPI is also per install. If you model per-payer LTV instead, divide CPI by your paying conversion rate to get cost per paying user first. And build LTV on net proceeds: comparing a gross-revenue LTV to CPI overstates viability by the full 15–30% store commission.
Why payback period is the binding constraint
A campaign can be handsomely LTV-positive and still be un-runnable: if payback takes 18 months, every dollar of spend is locked up for 18 months before it returns, and scaling multiplies the cash hole. That’s why most app companies cap payback — commonly 3–6 months for cash-constrained teams, up to 12 for funded ones — and treat the cap, not the LTV ratio, as the real budget gate. The max CPI under a payback cap is simply monthly net revenue per user × the cap in months.
Payback discipline also protects against LTV estimation error, which is severe for young apps: an LTV projected from three months of data can miss by 2× in either direction, but revenue observed inside a 6-month payback window is mostly actuals, not forecast. When your predicted LTV and your payback-capped math disagree about a channel, trust the payback math until the LTV model has aged.
Frequently asked questions
How do I calculate my UA break-even point?
You break even when LTV per install equals CPI. Profit per install = LTV − CPI, and payback period = CPI ÷ monthly net revenue per user. Example: $4 CPI, $12 LTV, $1/month net revenue → $8 profit per install, 3:1 ratio, 4-month payback.
What is a maximum profitable CPI?
At pure break-even it equals your LTV per install; at the standard 3:1 LTV:CAC health target it’s LTV ÷ 3. Under a payback cap, max CPI = monthly net revenue per user × maximum acceptable months. Use whichever of these is lowest as your bidding ceiling.
What is a good payback period for app UA?
Most app companies target 3–12 months, with cash-constrained teams at the short end. Beyond 12 months, LTV forecast error and cash lock-up make scaling risky even when the LTV ratio looks great on paper.
Should I use blended LTV or per-channel LTV?
Per-channel whenever possible — install quality differs enormously by source, and a blended LTV lets bad channels hide behind good ones. Users from high-intent sources (search ads, organic-like placements) routinely show 2–5× the LTV of users from incentivized or broad-display traffic.
What are typical CPI benchmarks?
US iOS CPIs commonly run $2–5 for broad campaigns, with competitive categories (finance, gaming, dating) higher and Android or emerging markets often well under $1. But benchmarks matter less than your own ceiling: any CPI below your payback-capped maximum is good, and any above it is bad, whatever the market average says.
Hold every keyword under your max CPI
Appalize’s Apple Ads automation applies your CPA ceiling per keyword — bid recommendations, waster detection, and rules that pause anything drifting past break-even before it eats the budget.
Related free tools
App LTV Calculator
Estimate customer lifetime value from ARPU and churn or average lifetime.
CPI Budget Planner
Convert between install targets, CPI, and budget for any user acquisition plan.
ROAS Calculator
Calculate return on ad spend and the break-even ROAS your margin requires.
Apple Search Ads CPA Calculator
Compute CPT, CPA, and tap-to-install rate from your Apple Search Ads spend.