Three gates. One journey. Gate 1 validates your concept and budget before you build. Gate 2 returns a go/iterate/kill verdict in soft launch. Gate 3 tells you when and how to scale UA spend. Every verdict is grounded in cited practitioner research. Free for indie studios.
| Genre | D1 min | D7 min | CPI max | Hook CTR min |
|---|---|---|---|---|
| Puzzle | 42% | 18% | $2.00 | 8.0% |
| Match-3 | 44% | 19% | $1.65 | 9.0% |
| Casual | 38% | 15% | $1.80 | 7.5% |
| Hyper-Casual | 30% | 8% | $0.60 | 6.0% |
| Idle / Tycoon | 40% | 20% | $3.00 | 7.0% |
11 genres covered · View all benchmarks
PixyLiv covers three specific decision points every mobile studio faces. Everything else in your workflow stays the same.
Genre benchmarks, UA budget check, soft launch region guidance, concept stress test, and common pre-build mistakes — before you write a line of code.
Open Gate 1 →Decision Engine, Friction Finder, Update Evaluator, Launch Readiness Tracker, and Weekly Check-in — all the tools you need during active soft launch.
Open Decision Engine →Revenue Forecast across three scenarios and ROAS Waypoints — the measured payback curve that tells you whether scaling makes economic sense right now.
Open ROAS Waypoints →Named, cited failure patterns from practitioner research.
Empirical analysis of real app retention data found that apps with 100 users or fewer show highly volatile retention. a single user churning can shift the reading by a full percentage point. Studios reading too much into a thin cohort routinely overcorrect on noise.
Lim, Malik and Aiello, Sovereignty of the Apps.Practitioners who run real concept tests before building report only continuing development when Hook CTR clears a pre-set threshold. Most tested concepts do not clear it. Skipping this step before scaling spend is a common, avoidable way budgets get burned.
Pattern: published concept-testing methodology.Aggregate retention can rise simply because acquisition volume increased, even while each individual install cohort is retaining worse. Reading a single blended number instead of per-cohort curves can hide a worsening problem for weeks.
Pattern documented across practitioner post-mortems on cohort analysis.All tools are live today. No feature on this page is a future promise. Free for indie studios.
Before writing code, enter your genre, monetisation model, and UA budget. Get genre benchmarks, a UA budget check against the 385-install minimum, soft launch region guidance, and a concept stress test across 5 design conditions.
Enter D1, D7, and CPI. Get a plain go/iterate/kill verdict against genre benchmarks. Includes D7/D1 ratio diagnosis. tells you whether the issue is FTUE, core loop, or acquisition cost, with cited reasoning you can share with a team or investor.
Rate your first 10 levels as easy, medium, hard, or very hard. no analytics tool needed. PixyLiv identifies the single worst level versus genre norms and returns 3 specific fixes.
Enter metrics before and after a game update. Runs a two-proportion z-test and tells you whether the change was statistically significant or normal variance. Stops studios from reverting updates that were working.
Enter DAU, ARPDAU, and weekly growth rate. Returns a 90-day projection across 3 scenarios with a burn rate sustainability signal. Tells you whether your trajectory covers costs within the soft launch window.
Tracks D1, D7, and CPI week by week against genre thresholds. Two consecutive green weeks is your go signal. Removes the emotional bias from the timing decision. the hardest call most studios make.
90-day revenue projection across three scenarios with burn rate signal. Plus the ROAS payback curve — a measured waypoint tracker that tells you whether scaling UA spend makes economic sense right now.
D1, D7, D30 retention thresholds and CPI ranges for 11 mobile game genres. Includes the D7/D1 ratio diagnostic table, 5 common failure patterns with specific fixes, and research citations for every threshold. 6 pages. Free.
Download Free ReportYour analytics tool tells you what already happened inside your live game. PixyLiv is the interpretation layer. it takes the numbers you already have and tells you what to do about them. Gate 1 answers the pre-build question: do I have the right concept, budget, and market to generate valid soft launch data? Gate 2 answers the soft launch question: do my numbers support scaling, iterating, or stopping?
Yes. Genre benchmarks are seeded from published practitioner benchmark research and the D3/D1 retention threshold framework. D1, D7, CPI ceiling, and Hook CTR minimums for 11 genres. They are indicative thresholds, not guarantees. The 385-install minimum is derived from the Cochran formula for 95% confidence interval at 5% margin of error. standard statistics.
PixyLiv covers two decision points every mobile studio faces: whether to build a concept, and whether to scale after soft launch. Gate 1 validates concept, UA budget, and market before you build. Gate 2 takes your real D1, D7, CPI, and Hook CTR and returns a plain go/iterate/kill verdict. Designed for studios without a dedicated data analyst who need a clear verdict, not another dashboard.
No. Your analytics setup collects the data. PixyLiv interprets it. Every input is designed to be obtainable from any analytics platform. or estimated from playtests and spreadsheets. You keep your existing tools.
Free for indie studios. Gate 1 validates your concept before you build. Gate 2 diagnoses soft launch. Gate 3 tells you when to scale. No credit card. No setup.