Mobile App Unit Economics: LTV, CAC, and the Metrics That Actually Matter

Downloads and revenue are vanity metrics. They tell you there’s activity, but they say nothing about whether your business is sustainable.

The numbers that actually matter are unit economics: how much it costs to acquire a user (CAC), how much that user is worth over time (LTV), and whether the ratio between them makes mathematical sense. Most indie developers skip this because it feels like enterprise stuff. It’s not. Unit economics apply at 100 users the same as 100,000, and understanding them early can save you from spending months scaling something that’s fundamentally losing money.

CAC (Customer Acquisition Cost)

CAC is the total cost of acquiring one paying customer. Not cost per install - cost per user who actually pays you.

CAC = Total Marketing Spend / Number of New Paying Customers

Spend $2,000 on ads, get 50 new paying users, your CAC is $40.

The mistake most developers make: looking at CPI from their ad platforms and thinking that’s the cost. CPI is cost per install, not cost per paying user (reported CPI is almost always too low). If your CPI is $2.00 and only 5% of installs convert to paying, your real CAC is $40. Twenty times higher than the number the ad platform shows you.

Blended CAC

If you run ads on multiple platforms:

Blended CAC = (Google Ads + Apple Search Ads + Other Marketing) / Total New Paying Customers

This shows your true cross-channel cost and reveals when one channel is way more efficient than another - useful for deciding where to shift budget.

Current CPI benchmarks (to estimate CAC)

Start with these and multiply by your conversion rate:

• iOS overall: $2.52 average
• Android overall: $1.29 average
• Apple Search Ads by category: Games ~$2.00, Utilities $2.90, Productivity $3.13, Finance $8.23
• Google App Campaigns: Casual games $0.63, Simulation $0.59, Mid-core $2.00

If 3% of installs convert to paying users, multiply CPI by ~33. A $2.00 CPI becomes a $66 CAC. Sobering, right?

LTV (Lifetime Value)

LTV is the total revenue you expect from a single user over their entire time with your app. Calculation depends on your model.

Subscription apps

LTV = ARPU per Month x Average Subscriber Lifespan (months)

App charges $9.99/month, average subscriber stays 8 months: LTV = $79.92.

Retention data matters a lot here. RevenueCat’s 2025 numbers show yearly plans retain best - up to 53.7% for low-priced plans, 48.3% for high-priced. Monthly plans retain 12-22% depending on price. Weekly plans hover around 3-6%.

So subscription LTV swings wildly based on billing period and price point.

Ad-supported apps

LTV = ARPDAU x Average Days Active

ARPDAU benchmarks for 2025:

• Hypercasual games: $0.03
• Casual games: $0.10
• Mid-core games: $0.30-$0.40

Casual game user, $0.10 ARPDAU, active for 60 days on average: LTV = $6.00. Not a lot of room for paid acquisition at that number.

IAP-driven apps

LTV = Average Revenue Per User over their lifetime

You need cohort tracking to calculate this properly. And keep in mind that most IAP revenue comes from a small group of big spenders, so average LTV is misleading. Look at the median alongside the average for a more honest picture.

The LTV:CAC ratio

This is the number. The one that tells you if your business model works.

• Above 3:1 - Healthy. $3 earned for every $1 spent on acquisition.
• 1:1 to 3:1 - Breakeven to thin. Only works if your operating costs are low.
• Below 1:1 - You’re losing money on every user you acquire. Stop spending on ads and fix your monetization or retention first.

A lot of indie developers are unknowingly below 1:1. They see a CPI of $1.50 and ARPU of $0.50/month and assume they’ll make money eventually. But if the average user churns after 2 months, LTV is $1.00 - and they’re losing $0.50 per acquired user before platform commissions even come into play.

Retention is the biggest lever

Small retention improvements have outsized effects on LTV.

A subscription app that improves month-1 retention from 40% to 50% doesn’t just get 25% more users in month 2. It compounds across every subsequent month. Over 12 months, that 10-point improvement might double total LTV.

General benchmarks for good retention:

• Day 1: 25-35%
• Day 7: 10-15%
• Day 30: 5-8%

If you’re significantly below these, improving retention will move your unit economics far more than optimizing your ad spend will.

How to actually calculate this

The annoying part: CAC data lives in your ad platforms (Google Ads, Apple Search Ads). Revenue data lives in your app stores (App Store Connect, Google Play Console, AdMob). Retention data lives in your analytics tool. Three separate systems that don’t connect.

At minimum you need:

1. Total ad spend per month across all channels
2. Revenue per month across all platforms (App Store + Google Play + AdMob)
3. New paying customers per month
4. Average customer lifespan from your analytics

Apps Finboard handles the first two automatically - it syncs costs from Google Ads and Apple Search Ads alongside revenue from all three app stores. Having total costs and total revenue in one place makes calculating blended CAC and comparing it to LTV straightforward instead of a quarterly spreadsheet marathon.

Start rough, get better over time

Don’t wait for perfect data. Start with rough estimates:

1. Total ad spend last month
2. Total revenue last month
3. If revenue > ad spend, you’re probably positive (but platform commissions eat 15-30%, so factor that in)
4. If revenue < ad spend, you’ve got a problem to fix before you scale

The developers who build sustainable businesses check these numbers regularly. Monthly at minimum, weekly if you’re actively running campaigns. The sooner you spot a ratio going the wrong direction, the less money you burn before fixing it.