Top 10 Mobile Gaming User-Acquisition CPI and LTV-to-CAC KPIs

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This guide provides the definitive set of top 10 KPIs for mobile gaming user acquisition (UA), focusing on Cost Per Install (CPI) and Lifetime Value to Customer Acquisition Cost (LTV:CAC) ratios. You will learn the specific metrics that separate profitable game studios from those burning cash, including real benchmarks from Unity Ads, AppLovin, and ironSource.

The guide covers why mobile gaming metrics differ from SaaS, how to calculate and interpret each KPI, failure modes to avoid, and a 30-60-90 day implementation plan.

Why Mobile Gaming Measures Differently

Mobile gaming user acquisition is fundamentally different from SaaS or e-commerce for three structural reasons:

1. Zero switching cost and frictionless churn: A user downloads a game, plays for 30 seconds, and deletes it. There is no onboarding email sequence, no contract, no data migration. This means retention metrics (D1, D7, D30) are the most critical leading indicators, not just a secondary concern.

1. Ad-funded vs. IAP-funded models: Hyper-casual games (e.g., *Subway Surfers*, *Angry Birds 2*) generate nearly 100% of revenue from ads. Mid-core and hard-core games (e.g., *Clash of Clans*, *Genshin Impact*) rely on in-app purchases (IAP). The KPI mix flips: hyper-casual tracks eCPM (effective cost per mille) and ad ARPDAU, while mid-core tracks payer conversion and average revenue per paying user (ARPPU). According to a 2023 report by Unity Ads, hyper-casual games see an average D1 retention of 25-35%, while mid-core games see 35-45%.

1. Platform fragmentation: iOS (SKAdNetwork, ATT) and Android (GAID, no ATT) have fundamentally different attribution models. IOS post-IDFA requires probabilistic attribution and modeled data from tools like Singular or Adjust. Android allows deterministic attribution. This means CPI on iOS can be 2-3x higher than Android for the same game, but LTV can also be higher. A 2024 benchmark from AppLovin showed iOS CPI averaging $1.80 for mid-core games vs. $0.65 on Android.

1. Short LTV curves: In SaaS, LTV is measured over years. In mobile gaming, the LTV curve flattens significantly after Day 30. For hyper-casual, 80% of total LTV is realized within the first 7 days. For mid-core, it's 60% within 30 days. This forces a faster feedback loop on UA spend.

1. Creative-driven acquisition: Unlike B2B SaaS where content marketing drives leads, mobile gaming UA is almost entirely driven by video ads, playable ads, and rewarded video. The creative itself is a KPI input. A 2023 study by ironSource (now Unity) found that changing the first 3 seconds of a video ad improved CPI by 40%. This is not a "tight integration" but a direct, measurable lever.

The Most Important KPIs to Track

Here are the 10 KPIs every mobile gaming UA team must track, with definitions, formulas, and benchmarks.

1. CPI (Cost Per Install)

Definition: Total UA spend divided by number of installs. The most basic unit of efficiency. Formula: Total Ad Spend / Number of Installs Benchmarks: Hyper-casual: $0.10 - $0.50 (Android), $0.50 - $1.50 (iOS).

Mid-core: $1.00 - $3.00 (Android), $2.00 - $5.00 (iOS). Hard-core (e.g., *Rise of Kingdoms*): $3.00 - $8.00. Why it matters: CPI is the denominator in LTV:CAC.

A low CPI is useless if the users don't retain. A high CPI is acceptable if LTV is proportionally higher. Never optimize for CPI alone.

2. LTV (Lifetime Value)

Definition: Total revenue generated by a user over their entire lifetime in the game. For ad-funded games, this includes ad revenue (eCPM * ad impressions). For IAP games, it includes purchases.

Formula: Sum of all revenue from a cohort / Number of users in that cohort. Often modeled using D7 or D30 data. Benchmarks: Hyper-casual: $0.15 - $0.80.

Mid-core: $2.00 - $10.00. Hard-core: $10.00 - $100.00+. Why it matters: LTV is the numerator in LTV:CAC.

The shape of the LTV curve is more important than the absolute value. A steep curve (high early revenue) allows faster reinvestment.

3. CAC (Customer Acquisition Cost)

Definition: Total cost to acquire a paying user (not just an installer). This is different from CPI. Formula: Total UA Spend / Number of Paying Users (users who make an IAP or generate significant ad revenue).

Benchmarks: Varies wildly. For a $5.00 CPI mid-core game with a 5% payer conversion, CAC = $5.00 / 0.05 = $100.00. Why it matters: CAC is the true cost of revenue.

If you optimize for CPI but your payer conversion drops, your CAC skyrockets.

4. LTV:CAC Ratio

Definition: The ratio of a user's lifetime value to the cost of acquiring them. Formula: LTV / CAC Benchmarks: The golden rule is 3:1. A ratio below 1:1 means you are losing money.

Above 5:1 means you are likely under-investing in UA. For hyper-casual, a 2:1 ratio is often acceptable due to high volume. Why it matters: This is the single most important profitability KPI.

It tells you if your UA machine is profitable.

5. Day 1, 7, and 30 Retention

Definition: The percentage of users who return to the game on Day 1, Day 7, and Day 30 after install. Formula: (Users who opened the app on Day X) / (Total installs in cohort) Benchmarks: Hyper-casual: D1 25-35%, D7 5-10%, D30 2-5%. Mid-core: D1 35-45%, D7 15-20%, D30 8-12%.

Why it matters: Retention is the leading indicator of LTV. A game with D7 retention below 10% will struggle to ever achieve a 3:1 LTV:CAC ratio. If D1 retention drops by 5% in a week, pause all UA campaigns immediately.

6. ROAS (Return on Ad Spend)

Definition: Revenue generated from a UA campaign divided by the cost of that campaign. Measured at D7, D14, and D30. Formula: (Revenue from campaign) / (Ad spend on campaign) * 100% Benchmarks: D7 ROAS: 15-25% for hyper-casual, 25-40% for mid-core.

D30 ROAS: 60-80% for hyper-casual, 80-120% for mid-core. Why it matters: ROAS is the tactical KPI. It tells you which ad network (Facebook, Google, Unity Ads, Vungle, TikTok) is performing.

A campaign with D7 ROAS below 10% should be killed.

7. D7 Payback and D30 Payback

Definition: The day at which cumulative revenue from a cohort equals the CAC. D7 payback means you recover the cost within 7 days. Formula: The day where cumulative LTV >= CAC.

Benchmarks: Hyper-casual: D7 payback is ideal. Mid-core: D30 payback is good, D60 is acceptable. Hard-core: D90 payback is common.

Why it matters: Payback period determines your cash flow. A long payback period (e.g., 180 days) requires significant upfront capital. If your payback period exceeds your cash runway, you will go bankrupt.

8. ARPU (Average Revenue Per User)

Definition: Total revenue divided by total users. Includes both paying and non-paying users. Formula: Total Revenue / Total Users Benchmarks: Hyper-casual: $0.02 - $0.10. Mid-core: $0.50 - $2.00. Why it matters: ARPU is a macro health metric. If ARPU is declining but CPI is flat, your LTV:CAC ratio is shrinking.

9. ARPDAU (Average Revenue Per Daily Active User)

Definition: Revenue generated per daily active user. Critical for ad-funded games where revenue is tied to daily sessions. Formula: Daily Revenue / DAU Benchmarks: Hyper-casual: $0.01 - $0.05.

Mid-core: $0.10 - $0.50. Why it matters: ARPDAU directly ties to eCPM. If ARPDAU drops, either ad fill rates are down or users are seeing fewer ads.

10. ECPI (Effective CPI)

Definition: CPI adjusted for organic lift and cross-network attribution. Formula: (Total Spend) / (Total Installs - Estimated Organic Installs) Why it matters: Most UA platforms over-attribute installs. ECPI gives a truer cost. If your eCPI is 30% higher than your reported CPI, your attribution model is broken.

Here is a mermaid diagram showing the relationship between these KPIs:

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Real Operators

Playrix (Gardenscapes, Homescapes)

Playrix is a top mid-core casual developer. They use Singular for attribution and Adjust for analytics. Their reported CPI for *Gardenscapes* on iOS is $1.50-$2.50.

They target a D30 ROAS of 110% and a D7 payback of under 30 days. In a 2022 interview, they stated they test over 10,000 creative variants per month, using CPI and D7 retention as the primary creative KPIs.

Voodoo (Hyper-casual giant)

Voodoo is the king of hyper-casual. Their CPI targets are $0.15-$0.30 on Android. They use Tenjin for cost aggregation and AppLovin as a primary ad network. Their key KPI is D7 ROAS, which they need to hit 20% to scale. They famously kill games that don't achieve D1 retention above 30% within the first week of soft launch.

Supercell (Clash of Clans, Brawl Stars)

Supercell is a hard-core/mid-core hybrid. They use Facebook Ads and Google Ads heavily. Their CPI for *Brawl Stars* is estimated at $3.00-$5.00.

They focus on LTV:CAC ratio above 4:1 and a D30 payback. They are known for using the MEDDIC-like framework internally for game quality, but for UA, they use a custom "quality score" that blends D7 retention, D7 ARPU, and social sharing rate.

Zynga (Words With Friends, CSR Racing)

Zynga, now part of Take-Two, uses Adjust and Singular for cross-network attribution. Their CPI for *Words With Friends* is $0.80-$1.20. They track eCPI religiously to account for organic lift. In their 2023 earnings call, they cited a D7 payback period of under 60 days for their core games.

Failure Modes

1. Optimizing for CPI Alone

The problem: A low CPI campaign might bring in users who never play past Day 1. This destroys LTV:CAC. Example: A hyper-casual game ran a Facebook campaign with a $0.12 CPI but D1 retention of 12%. The LTV:CAC ratio was 0.8:1. They lost money on every install. Fix: Always pair CPI with D1 retention and D7 ROAS.

2. Ignoring LTV Curve Shape

The problem: A game might have a great D7 LTV but a flat D30 curve. This means users stop playing after a week. You are paying for users who only generate 7 days of revenue. Fix: Model LTV out to D90, even if you only have 30 days of data. Use tools like GameAnalytics or deltaDNA to predict curve shape.

3. Misattributing Organic Lift

The problem: UA platforms (Facebook, Google) often over-attribute installs that would have happened organically. This inflates ROAS and makes campaigns look profitable when they are not. Fix: Use a holdout group (e.g., 10% of your audience not exposed to ads) to measure true incremental lift.

Tools like Singular and Adjust offer incremental lift measurement.

4. Using Wrong Attribution Window

The problem: Using a 30-day click-through attribution window for a hyper-casual game where users decide to install within 2 seconds of seeing an ad. This leads to double-counting and inflated CPI. Fix: Use a 1-day click-through window for hyper-casual, 7-day for mid-core.

IOS SKAdNetwork forces a 24-hour window, which is actually more accurate.

5. Ignoring Platform Differences

The problem: Treating iOS and Android campaigns the same. IOS post-IDFA has a 30-50% lower match rate, meaning you are flying blind on a large portion of your spend. Fix: Use SKAdNetwork data from Singular or Adjust and model conversions using a probabilistic attribution model. Accept that iOS ROAS will be less precise.

Here is a mermaid diagram showing the decision tree for a failing campaign:

Reporting Cadence

Daily: Focus on CPI, D1 retention, D7 ROAS (using modeled data), and ARPDAU. These are the leading indicators. If any of these drop by 10% day-over-day, investigate immediately.

Weekly: Review LTV:CAC ratio, payback period, and eCPI. Compare against last week and last month. Check for creative fatigue.

Monthly: Full cohort analysis. Look at D30 retention, D30 ROAS, and LTV curves. Decide on budget allocation for the next month.

Tools: Use Singular or Adjust for attribution and cost aggregation. Use Tableau or Looker for dashboards. Use Google Sheets for quick cohort analysis.

30-60-90

First 30 Days: Audit and Baseline

• Week 1: Connect all ad networks (Facebook, Google, Unity Ads, AppLovin, TikTok) to a single attribution tool (e.g., Singular). Ensure all cost data is flowing.
• Week 2: Establish baseline KPIs for the last 30 days: CPI, D1/D7 retention, D7 ROAS, LTV:CAC ratio.
• Week 3: Identify the top 3 campaigns by volume and the bottom 3 by ROAS. Kill the bottom 3 immediately.
• Week 4: Implement a holdout group for incremental lift measurement. Set up a daily dashboard in Looker with CPI, D1 retention, and D7 ROAS.

Days 31-60: Optimization and Scaling

• Week 5-6: Run A/B tests on creative formats (video vs. Playable) using ironSource or Vungle. Track CPI and D7 ROAS per creative.
• Week 7: Scale the top-performing campaign by 20% daily. Monitor D7 ROAS closely. If it drops below 15%, pause scaling.
• Week 8: Implement a D7 payback target. For hyper-casual, set a 7-day payback goal. For mid-core, set a 30-day goal.

Days 61-90: Institutionalize

• Week 9-10: Build a monthly reporting template in Tableau showing LTV curves for each campaign and network.
• Week 11: Train your UA team on the LTV:CAC ratio as the north star metric. Ban discussions of CPI alone.
• Week 12: Set quarterly targets: LTV:CAC ratio of 3:1, D7 ROAS of 20% for hyper-casual, D30 payback under 60 days for mid-core.

FAQ

Q: What is a good CPI for a mobile game in 2024? A: It depends on genre. Hyper-casual: $0.10-$0.50. Mid-core: $1.00-$3.00. Hard-core: $3.00-$8.00. Never compare CPI across genres.

Q: How do I calculate LTV for a game with no IAP (ad-only)? A: Use ARPDAU * Average Lifetime Days. For example, if ARPDAU is $0.03 and average lifetime is 10 days, LTV is $0.30. Tools like Tenjin can model this automatically.

Q: What is the difference between ROAS and LTV:CAC? A: ROAS is a campaign-level metric (revenue vs. Spend). LTV:CAC is a user-level metric (lifetime value vs. Cost to acquire). ROAS is tactical; LTV:CAC is strategic.

Q: Why is my iOS CPI so much higher than Android? A: iOS has higher device costs, higher user LTV, and ATT restrictions that reduce targeting efficiency. Expect iOS CPI to be 2-3x higher.

Q: How often should I check D7 ROAS? A: Daily for campaigns with enough volume (1,000+ installs). For smaller campaigns, wait until you have at least 500 installs to get statistically significant data.

Q: What should I do if my D1 retention drops suddenly? A: Pause all UA campaigns immediately. Check for game bugs, server issues, or a bad ad creative. Do not restart until D1 retention returns to baseline.

Q: Is a 1:1 LTV:CAC ratio acceptable? A: No. You are breaking even at best, and likely losing money due to platform fees and refunds. Aim for 3:1.

Sources

• Unity Ads 2023 Mobile Game Performance Benchmarks
• AppLovin 2024 CPI Benchmarks Report
• Singular ROI Index 2024 - Mobile Gaming
• Adjust 2023 Mobile Gaming Benchmarks
• Tenjin 2024 Hyper-Casual Game Report
• GameAnalytics 2023 Mobile Game Retention Benchmarks
• IronSource (Unity) 2023 Creative Optimization Guide
• Facebook Gaming 2024 UA Playbook