You're tracking downloads, DAU, and ad spend across Meta, Google, and TikTok—but none of those numbers tell you whether to scale your best campaign or cut your worst one tomorrow. Most mobile game dashboards overflow with metrics that look impressive in a pitch deck but don't actually change what you do next week.

The metrics that matter tie directly to revenue, guide your next budget decision, and stay consistent across every acquisition channel you run. This guide breaks down the five UA metrics that determine profitability, the engagement and monetization numbers every CFO tracks, and how to unify fragmented data so you stop reconciling spreadsheets and start making faster decisions.

What Makes a Mobile Game Metric Actually Matter

Mobile game success comes down to tracking metrics that connect directly to revenue, guide your next campaign decision, and stay consistent across Meta, Google, and TikTok. Most numbers on your dashboard look impressive but don't actually change what you do tomorrow—those are vanity metrics.

A metric earns its spot in your weekly review when it passes three tests:

• Revenue impact: Does it tie to money coming in through IAP or ads, or money going out through UA spend?

• Actionability: Can you adjust a campaign, tweak a feature, or shift budget based on what this number tells you?

• Consistency: Can you measure it reliably across ad networks, not just inside one platform?

Total downloads or app opens sound great in a pitch deck. But they won't tell you whether to scale your Meta campaigns or cut TikTok spend tomorrow.

The 5 UA Metrics That Determine Profitability

User acquisition metrics sit at the top of your funnel and determine everything downstream—your revenue, retention, and whether this game becomes a business or burns cash. Five metrics answer the only question that matters for UA: Is this channel worth the money?

Cost Per Install (CPI) by Channel

CPI means total ad spend divided by installs from that campaign. Breaking CPI down by channel matters far more than looking at one blended number, because Meta attracts different users at different prices than Google or TikTok.

A $2 CPI on Meta might deliver users who spend $10 in their first week. Meanwhile, a $1 CPI on TikTok might bring users who churn in 48 hours. CPI alone doesn't show profitability—you pair it with LTV to see if the math works.

Return on Ad Spend (ROAS) Over Time

ROAS is revenue generated divided by ad spend, and it's the clearest signal of campaign health. Measuring ROAS at Day 7, Day 30, and Day 90 windows shows whether a campaign pays back quickly or takes months to break even.

iOS attribution through SKAN (Apple's SKAdNetwork framework) limits how much user-level data you see. Server-side event tracking fills the gaps and gives you reliable ROAS numbers even when users don't grant ATT permission.

Install-to-Purchase Conversion Rate

This metric shows the percentage of installs that make any in-app purchase. It separates profitable games from install farms—games that rack up download counts but don't pay the bills.

Conversion rates vary by genre. Casual puzzle games monetize differently than mid-core RPGs. But the pattern holds: higher conversion means you can afford higher CPI and still hit profitability.

Blended vs. Paid Customer Acquisition Cost

Blended CAC divides total marketing spend by all new users, including organic installs. Paid CAC divides spend by paid users only.

Blended CAC hides channel performance because it mixes free organic growth with expensive paid campaigns. Paid CAC reveals true unit economics—what you actually pay to acquire a user through ads. If your paid CAC is $5 and your LTV is $15, you have room to scale. If paid CAC is $8 and LTV is $6, you're burning cash.

Payback Period by Campaign

Payback period measures how many days it takes for a cohort's revenue to cover its acquisition cost. This metric determines cash flow and scale decisions.

Games with 30-day payback can scale faster than games with 180-day payback because you reinvest revenue sooner. Ad-monetized casual games might pay back in 7–14 days, while IAP-heavy mid-core games might take 60–90 days. Knowing your payback period tells you how much budget you can deploy without running out of runway.

Engagement Metrics That Predict Revenue

Engagement metrics act as leading indicators of monetization. They won't guarantee revenue, but low engagement guarantees churn. High session length and strong DAU/MAU ratios signal that users find your game worth returning to—the foundation of long-term monetization.

Daily, Weekly, and Monthly Active Users

DAU (daily active users), WAU (weekly active users), and MAU (monthly active users) show how many unique users engage with your game in each time window. Tracking all three together reveals growth trajectory and retention health better than any single number.

Raw DAU or MAU counts matter less than trends. Is DAU growing week-over-week? Is the ratio between DAU and MAU improving? Patterns tell you whether your game is building momentum or plateauing.

Session Length and Frequency Patterns

Session length measures time between app open and close. Session frequency counts how many times per day or week a user opens your game. Both metrics together reveal engagement depth (long sessions) versus breadth (frequent check-ins).

A puzzle game might see short, frequent sessions throughout the day. A strategy game might see longer, less frequent sessions. Neither pattern is inherently better—what matters is whether session behavior aligns with your monetization model.

Stickiness Ratio (DAU/MAU)

Stickiness is DAU divided by MAU, expressed as a percentage. A 20% stickiness ratio means that on an average day, 20% of your monthly users open the game.

Higher stickiness reveals stronger habit formation. Habit formation predicts LTV better than raw DAU counts because users treat the game as part of their daily routine, not something they remember once a week.

Feature Adoption Rate

Feature adoption rate tracks the percentage of users who engage with a specific game feature—multiplayer mode, daily quests, battle passes, or seasonal events. Tracking adoption helps prioritize your product roadmap.

Features with high adoption deserve more investment. Features with low adoption might need redesign or removal. Feature adoption often connects directly to monetization—if 40% of users engage with your battle pass and those users have 3x higher ARPPU, you know where to focus product development.

Monetization Metrics Every Gaming CFO Tracks

Four metrics determine whether your game is a business or a hobby. Investors, finance teams, and growth leaders care most about them because they reveal profitability, scalability, and long-term viability.

Average Revenue Per User (ARPU)

ARPU is total revenue divided by total users—both paying and non-paying. It shows blended monetization health across your entire user base, combining ad revenue and in-app purchase revenue into one number.

ARPU gives you a baseline. If your ARPU is $2 and your CPI is $3, you're losing money on every user unless retention extends LTV beyond that initial window.

Lifetime Value (LTV) by Cohort

LTV is the predicted total revenue a user generates over their entire lifecycle with your game. Cohort-based LTV—broken down by install date, acquisition channel, or campaign—matters far more than a blended LTV number.

You can calculate LTV using historical data (what past cohorts actually spent) or predictive models (what Day 7 or Day 30 behavior suggests about future spend). Predictive LTV helps you make faster decisions without waiting months for data.

Average Revenue Per Paying User (ARPPU)

ARPPU is total revenue divided by paying users only. It reveals monetization depth among spenders.

While ARPU shows overall monetization across all users, ARPPU shows whale behavior—how much your paying users actually spend once they open their wallets. A game with $50 ARPPU and 5% conversion monetizes differently than a game with $10 ARPPU and 15% conversion, even if both hit similar ARPU.

Free-to-Paid Conversion Rate

This metric is the percentage of users who make their first purchase, and it determines your monetization ceiling. A game that converts 8% of users to payers has more room to scale than a game that converts 2%.

Typical conversion rates vary by genre—casual games often see 2–5% conversion, while mid-core games might hit 5–10%. Higher conversion means you can afford more aggressive UA spend.

Retention Rates That Signal True Product-Market Fit

Retention is the single most important metric category for long-term success. You can't monetize users who don't come back. Strong retention compounds every other metric—engagement, LTV, and ROAS all improve when users stick around.

Day 1, Day 7, and Day 30 Retention

Retention measures the percentage of users who return on a specific day after install. Each window reveals something different:

• D1 retention: First impression quality—did the tutorial work, did the game hook them?

• D7 retention: Habit formation—are users coming back after the novelty wears off?

• D30 retention: Long-term fit—does your game have staying power beyond the first few weeks?

Games with strong D1 but weak D7 often have onboarding issues or shallow core loops. Games with strong D7 but weak D30 might lack endgame content or progression depth.

Churn Rate by Player Segment

Churn is the percentage of users who stop playing within a time window. Segmenting churn by spender status, level reached, or acquisition channel reveals actionable insights.

If paying users churn at 20% while non-payers churn at 60%, your monetization works but your core loop might not. Tracking churn separately for specific cohorts—especially high-value segments—helps you prioritize retention efforts where they matter most.

Resurrection and Reactivation Rate

Resurrection rate measures the percentage of churned users who return after 30+ days of inactivity. Tracking reactivation matters because re-engagement campaigns targeting churned users often deliver better ROI than cold acquisition.

A 10% resurrection rate might not sound impressive. But if those users cost $0.50 to reactivate versus $3 to acquire fresh, the unit economics make reactivation campaigns worth running.

How to Unify Your Mobile Game Metrics Across Networks

Fragmented data kills good decisions. When your metrics live in Meta Ads Manager, Google Ads, TikTok, App Store Connect, and three internal dashboards, you spend more time reconciling spreadsheets than optimizing campaigns.

Modern attribution platforms unify data from Meta, Google, TikTok, and other networks into one dashboard. You see which channels drive installs and revenue without opening ten browser tabs. This isn't about convenience—it's about accuracy and speed.

Connecting Meta, Google, and TikTok Data

Each ad network reports installs differently, using different attribution windows and counting methods. Attribution links ad clicks to in-app events across networks, so you know which campaign on which platform delivered which user and what they did after installing.

Server-to-server tracking ensures you capture post-install events—purchases, level completions, ad views—even when users don't grant ATT permission on iOS. Without S2S tracking, you're flying blind on a significant chunk of your iOS traffic.

Solving the iOS Attribution Problem with SKAN 4.0

SKAN (SKAdNetwork) is Apple's privacy-safe attribution framework for iOS. It limits user-level data while still providing campaign-level insights. SKAN 4.0 introduced conversion values and hierarchies that give you more granular data than earlier versions, but you still need decoding logic to translate Apple's postbacks into actionable metrics.

SKAN won't give you the user-level detail you had pre-iOS 14. But proper SKAN implementation and decoding still lets you optimize campaigns, measure ROAS, and scale profitable channels.

Server-to-Server Event Tracking

S2S tracking sends event data directly from your server to ad networks, bypassing the device entirely. This approach improves data accuracy, reduces discrepancies between what your analytics platform sees and what ad networks report, and captures events that client-side SDKs might miss.

S2S is essential for tracking post-install events like purchases and level completions, especially on iOS where ATT opt-out rates limit client-side tracking.

Setting Realistic Benchmarks for Different Game Genres

Benchmarks vary wildly by genre, so comparing your casual puzzle game to a hardcore MMO leads to bad conclusions. Casual games prioritize DAU and ad revenue. Mid-core games focus on LTV and ARPPU. Hardcore games optimize for session length and long-term retention.

Compare your metrics to games in your genre, not all mobile games. A 40% D1 retention rate might be excellent for a hyper-casual game but weak for a mid-core RPG.

Your Mobile Game Metrics Stack: From Spreadsheets to Real Intelligence

Most teams start with manual CSV exports from ad networks, stitching data together in spreadsheets and hoping the numbers reconcile. This approach works until you scale past two or three acquisition channels—then it becomes a full-time job just keeping dashboards updated.

A modern metrics stack unifies attribution, deep linking, event tracking, SKAN decoding, and AI-powered insights. You stop reconciling spreadsheets and start making decisions. Here's what a complete stack includes:

• Attribution tracking: Know which campaigns on Meta, Google, and TikTok drive installs and revenue

• Deep linking: Send users from ads directly to the right in-game experience, not a generic home screen

• Event tracking: Capture every meaningful action—purchases, level-ups, ad views—so you see the full user journey

• AI insights: Auto-surface underperforming campaigns and budget reallocation opportunities without manually digging through reports

Linkrunner unifies attribution, deep linking, and analytics for mobile-first apps, so growth teams see the full journey from click to install to revenue in one place. Instead of stitching together data from five platforms, you get clean attribution and actionable insights without the reconciliation work.

FAQs About Mobile Game Metrics

How often should I review my game metrics?

Daily for UA spend and ROAS, weekly for retention and engagement trends, monthly for LTV and cohort analysis.

Which metrics matter most for fundraising?

Investors focus on LTV-to-CAC ratio, retention curves, and month-over-month revenue growth to assess scalability and unit economics.

What is a healthy LTV to CAC ratio for mobile games?

A ratio above 3:1 indicates strong unit economics, meaning each user generates three times their acquisition cost over their lifetime.

How do privacy regulations impact metric accuracy?

iOS ATT limits user-level tracking, so SKAN and probabilistic modeling fill gaps, but campaign-level insights remain reliable with proper attribution setup.

Can I track these metrics without an expensive MMP?

You can manually stitch data from ad networks and analytics tools, but unified attribution platforms eliminate discrepancies and save hours of reconciliation work each week.