Mobile Game Retention Benchmarks 2026: D1, D7, D30 Data for Publishers
Quick answer: The mobile game retention benchmarks 2026 all trace back to one dataset. According to GameAnalytics' 2026 Mobile & PC Gaming Benchmarks report, based on 16,000+ live mobile games, the median mobile title retains roughly 22% of players at D1, just under 4% at D7, and about 0.7% to 0.8% at D30. The top 1% of games hold 64 to 68% at D1 and 13 to 15% at D30. These are cross-genre, cross-platform medians. Genre design, platform split, regional market, and whether the game has an active LiveOps program all shift where a specific title should expect to land. This guide breaks down the current distribution data, explains what it means by tier, covers regional differences, and shows how publishers use retention data in practice.
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Why Retention Benchmarks Matter for Publishers
Retention is the single metric that determines whether a mobile game is a business or a sunk cost. It measures the percentage of an install cohort that returns on Day 1, Day 7, and Day 30 after first session. Those three numbers tell a publisher more about a game's commercial potential than almost any other signal available before significant UA spend.
The reason is structural. Retention sits upstream of every other metric that matters at scale: LTV, ROAS, payback period, and the viability of paid acquisition. A game with weak retention cannot be fixed by better creatives or a lower CPI. The unit economics simply do not close.
The commercial stakes are direct. Consider the math at the D30 level. If a game retains 2% of players at D30 versus 5%, the difference in cost-per-surviving-player across a typical Tier 1 UA campaign is not marginal. It is the difference between economics that work and economics that require subsidy. Every percentage point of D30 retention is a multiplier on the return from every dollar spent on acquisition.
Publishers and investors evaluate retention against three reference points:
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The market distribution — where does this game sit relative to all live games?
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The genre expectation — is this game above or below the typical curve for its design type?
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The commercial viability bar — does this game's retention profile support the UA economics required to scale?
Understanding all three is the prerequisite for any serious publisher conversation. A game that clears the market median but sits below genre expectation is a different problem than a game that clears both but still cannot support paid acquisition economics at Tier 1 CPIs.
How to Read Retention Data Correctly
Before using any of the D1 D7 D30 retention benchmarks in a real decision, three interpretive rules matter.
Benchmarks are distributions, not targets
The most useful retention data is not a single pass/fail number. It is the market distribution: median, top quartile, top decile, and top 1%. Knowing your D7 is 8% is operationally useful only if you know that the top quartile sits at 6 to 7% and the top 1% exceeds 25%. Without the distribution, a number is just a number. With it, you know exactly where you stand in the market and what closing the gap to the next tier would require.
The 2026 report does not publish genre-level benchmarks
This is a critical caveat for anyone using GameAnalytics as a source. The 2026 Mobile & PC Gaming Benchmarks report explicitly notes that genre-level benchmarks are unavailable in this edition due to ongoing improvements to genre categorization methodology. Any article presenting precise genre-level D1/D7/D30 tables as current 2026 data is sourcing from older benchmark sets, typically 2022 to 2024 attribution-network data, and presenting them as current. The genre directional guidance in this article is clearly labeled by source and vintage.
Each interval diagnoses a different structural problem
D1, D7, and D30 are not just three points on the same curve. Each one surfaces a different failure mode:
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Weak D1 is almost always an onboarding or first-impression problem. The game is not delivering enough value in the first session to justify a return.
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D1 is acceptable but D7 is weak points to a player habits and early progression problem. The game hooks players initially but fails to give them a reason to build a daily return pattern in the first week.
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D7 is acceptable but D30 is weak is a content depth and LiveOps problem. Players are establishing a habit but running out of reasons to continue past the first month.
Misdiagnosing the interval leads to misallocated effort. Reworking creatives and onboarding will not fix a D30 problem caused by insufficient content depth. Redesigning the meta economy will not fix a D1 problem caused by a confusing first session.
The 2026 Retention Tier Distribution
The mobile game retention data below comes directly from GameAnalytics' 2026 Mobile & PC Gaming Benchmarks report, covering 16,262 live mobile games with at least 1,000 monthly active users on iOS and Android across all genres and regions. All figures reflect 2025 calendar-year performance as reported in the 2026 edition.
| Tier | D1 Retention | D7 Retention | D30 Retention |
| Bottom 25% (P25) | Below 10–11% | 1.67–1.94% | Below 0.5% |
| Median (P50) | ~22% | Just under 4% | 0.68–0.79% |
| Top 25% (P75) | Just above 30% | 6–7% | 1.6–1.8% |
| Top 10% (P90) | ~40% | 11–12% | Not published separately |
| Top 1% (P99) | 64–68% | 25–28% | 13–15% |
Key takeaway: Three quarters of all tracked mobile games fail to clear 3% at D30. A game holding 3% or more one month in is outperforming roughly 75% of the live market. The top 1% — the titles that generate serious revenue — hold 13 to 15% at D30. That gap is not incremental. It is structural.
What these tiers mean commercially
The distribution reveals something that flat benchmark targets obscure: the gap between average and elite is not a matter of degree. It is a different kind of game.
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A median game at D7 of ~4% is structurally organic-first. Paid UA economics at Tier 1 CPIs do not work at that retention level, regardless of the creative or channel mix.
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A top-quartile game at D7 of 6 to 7% is marginally better but still below the bar most publishers use as a minimum threshold for UA investment conversations.
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A top-10% game at D7 of 11 to 12% is where paid acquisition starts to become viable in select markets and channels.
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A top-1% game at D7 of 25 to 28% is operating in a different commercial category entirely.
The practical working bar for publisher conversations sits above the top quartile, not at the median. Teams often use a D1/D7/D30 profile in the range of 30 to 35% / 10 to 15% / 3 to 6% as a rough commercial viability screen. This is a working heuristic used by practitioners, not a published industry median. It reflects the reality of marketed games competing for paid acquisition, not the average of all 16,000+ live titles in the GameAnalytics dataset.
iOS vs. Android: the split that catches teams out
GameAnalytics' data shows a consistent retention advantage for iOS across all performance tiers. Among top-quartile games, D1 retention runs 31 to 33% on iOS versus 25 to 27% on Android. At the median, iOS sits around 25% D1 and Android around 19%.
The implication: evaluating a game's retention against a single blended global benchmark will make Android numbers look broken when they are simply normal for the platform. Retention targets should be set separately by store before any roadmap decisions are made on the basis of the data.
Retention by Genre: What the Data Supports
An important caveat upfront about retention benchmarks by genre: the GameAnalytics 2026 report does not publish genre-level D1/D7/D30 breakdowns in this edition. The directional guidance below draws on prior GameAnalytics benchmark cycles and published industry analysis, clearly labeled by source. Treat these as reference ranges rather than current 2026 benchmark facts.
Puzzle and card games: the strongest long-term retention profiles
Across multiple benchmark cycles, puzzle, match, board, and card games consistently show the strongest D7 and D30 retention in mobile gaming. The structural reason is session design: bite-sized levels with clear completion states and visible progress toward the next goal create habitual return behavior. Each session ends with a concrete reason to come back.
Published genre analysis from prior GameAnalytics cycles and industry sources consistently places puzzle and match games above the cross-genre average on every retention horizon, with card, board, and casino genres also showing strong long-term curves driven by habit loops and competitive mechanics.
What this means for publishers: If you are evaluating a puzzle or match title, the relevant benchmark is not the 22% D1 median for all games. The genre has historically cleared that median meaningfully. A puzzle game at 22% D1 is likely underperforming its genre, not meeting the market average.
Hypercasual: strong D1, structural D30 weakness
Hypercasual games typically post competitive D1 numbers, benefiting from zero-friction first sessions and immediate accessibility. The D30 picture is structurally different. Without a meta layer, there is no progression investment to protect and no long-term goal to pull players back after the first day's novelty fades.
This is not a design failure. It is a design choice with deliberate commercial implications: hypercasual monetizes through install volume and ad revenue, not through long-term player retention. A hypercasual title at 1.5% D30 may be performing at or above genre expectation. The benchmark that matters for that genre is D1 and early ARPDAU, not D30.
Hybrid casual and meta-driven casual: the D30 gap
Hybrid casual titles, which combine casual core loops with a meta progression system, consistently show meaningfully stronger D30 retention than pure casual or hypercasual. The meta layer creates long-term goals that sustain return behavior past the first week. Players who have invested in an economy, a collection, or a progression tree have something to protect and a reason to continue.
The practical implication: adding a meta layer to a casual game is not just a design decision. It is a D30 retention decision. The presence or absence of a meta system is one of the clearest predictors of where a casual game will land on the D30 distribution.
Mid-core and RPG: depth-driven retention with a harder onboarding curve
Mid-core and RPG titles can sustain some of the strongest long-term retention in mobile gaming when the onboarding curve is managed well. Published analysis, including data cited by AppFollow's 2026 retention guide, suggests mid-core and RPG titles can hold 20 to 21% at D7 and 11 to 12% at D30 among commercially performing titles. The meta gives players a reason to return that compounds over time: character progression, economy position, and competitive ranking all create switching costs that sustain engagement.
The challenge is the onboarding window. The investment that drives long-term retention takes time to establish. A mid-core game that loses players before they have invested in the progression system has lost them before the retention-driving mechanics have had a chance to work.
Social casino: habit loops and daily structures
Social casino titles, including slots, bingo, poker, and card variants, show some of the strongest long-term retention in mobile gaming. The structural driver is daily bonus architecture and habitual engagement patterns: daily login rewards, recurring tournament structures, and social competitive mechanics create consistent return triggers that sustain D30 engagement well above genre averages for casual games.
The genre comparison that matters most: when evaluating any game's retention, the first question is not "does this beat the 22% D1 median?" It is "does this beat the typical curve for this design type?" A social casino game at 30% D1 may be underperforming its genre. A hypercasual game at 30% D1 may be performing at the top of its category. Genre context is the frame that makes the number meaningful.
How LiveOps Changes the Retention Curve
The benchmark data above reflects the full distribution of live mobile games, including the majority that have no structured LiveOps program. For games with active live operations, the retention curves look meaningfully different, particularly at D30 and beyond.
The biggest separation between average and top-tier D30 curves almost always comes from systems outside the first-session loop. The core game design determines the floor. The LiveOps program determines the ceiling.
The specific mechanics that move each part of the curve
D1 to D7: daily engagement systems. Login rewards, daily missions, and daily challenges create the habitual return behavior that carries players from D3 to D7. These mechanics do not improve the game's inherent quality. They create a reason to return before the player has built an intrinsic motivation to do so. The D7 gap between games with and without daily engagement infrastructure is one of the clearest observable signals of LiveOps quality.
D7 to D30: event cadence. Regular limited-time events create return triggers that interrupt the natural decay in the D7-to-D30 window. A player who would otherwise churn at D10 or D14 has a specific, time-bounded reason to return if a new event has launched. Consistent weekly event cadence is the single most common structural difference between games that hold D30 above the top quartile and games that decay to the median.
D30 and beyond: content update frequency. Games that launch without a content update plan exhaust their library for engaged players within 7 to 14 days of the most active users' consumption rate. A content update cadence that stays ahead of the most engaged players is the structural requirement for sustaining D30 engagement over a multi-year commercial lifecycle. This is not a post-launch consideration. It requires planning the content pipeline before launch.
Re-engagement campaigns. Well-timed push notification campaigns targeting churned players at specific post-churn intervals recover a meaningful share of the D7-to-D30 dropout that every game experiences. The D30 retention number a game reports includes these recoveries. A game with an active re-engagement program will show higher reported D30 than the raw cohort decay would predict.
What this means for how you read the benchmarks
The GameAnalytics distribution data includes games across the full LiveOps spectrum, from titles with no live content whatsoever to titles with sophisticated event engines and weekly update cadences. The median reflects the average of all of them.
For a game with a structured LiveOps program, the relevant comparison is not the cross-genre median. It is the top quartile or top decile for the genre. The LiveOps program is precisely what separates top-quartile performance from median performance in the D7-to-D30 window. A game with strong core loop design and active LiveOps should be held to a higher benchmark than the market median suggests.
Regional Retention Differences
Regional retention data from the GameAnalytics 2026 report shows meaningful differences across markets, with the most important divergence happening at D7 and D30 rather than D1. All figures below are median (P50) values from the 2026 dataset.
D1 retention by region
Western markets lead on early engagement. Oceania posts the highest median D1 at 25.63%, followed by North America at 23.28% and Europe at 22.20%. Asia and Africa both trail at slightly below 19%, reflecting tougher early engagement dynamics in those markets.
D7 and D30: where the regional picture changes
The D7 picture shifts in a notable way. Africa and Oceania both lead at 5.60% median D7, followed by North America at 4.97% and Europe at 4.06%. Asia trails significantly at 2.68%, with South and Central America below 3.8%.
By D30, the regional divergence is clearest. Oceania leads at 1.39%, followed by North America at 1.18% and Europe at 0.92%. Most other regions cluster between 0.5% and 0.8%.
| Region | Median D1 | Median D7 | Median D30 |
| Oceania | 25.63% | 5.60% | 1.39% |
| North America | 23.28% | 4.97% | 1.18% |
| Europe | 22.20% | 4.06% | 0.92% |
| Africa | Below 19% | 5.60% | 0.5–0.8% |
| South & Central America | Below 19% | Below 3.8% | 0.5–0.8% |
| Asia | Below 19% | 2.68% | 0.53% |
Source: GameAnalytics 2026 Mobile & PC Gaming Benchmarks, median (P50) values.
Session behavior by region
Regional differences extend beyond retention into session behavior. North America leads median daily playtime at 14.45 minutes. Africa stands out for habitual play, with a median of 5.48 sessions per day and top-1% players reaching 21.10 sessions per day. Median session length is broadly consistent across regions, clustering between 2.7 and 3.6 minutes, with North America (3.64 min) and Oceania (3.47 min) leading slightly.
The soft launch implication
Western markets, particularly Oceania, North America, and Europe, lead on both D7/D30 retention and session length. This makes them the most reliable soft launch environments for generating retention data that is predictive of global commercial performance. Retention data from a Southeast Asian soft launch cohort may not accurately predict how the game will perform in North America or Europe, where both the behavioral baseline and the competitive landscape are different.
What Publishers Use Retention Data For
Publishers evaluate retention at three specific decision points. Understanding how these publisher retention metrics are used is as important as understanding what the benchmarks are.
Go/no-go for investment conversations
The first filter in any publisher evaluation is D1 and D7 retention from a real soft launch cohort. A game without soft launch data is not yet in the publisher conversation, regardless of concept quality or prototype performance. The soft launch cohort is the evidence base. Everything before it is a pitch.
A game with D7 retention below the top quartile (6 to 7% per the 2026 GameAnalytics data) faces a structural challenge in UA economics conversations. The unit economics at Tier 1 CPIs require a D7 meaningfully above the top quartile to generate viable ROAS projections. Most games presenting to publishers are structurally organic-first whether they know it or not.
UA economics modeling
Publishers use retention benchmarks to project LTV and evaluate whether the projected LTV-to-CPI ratio justifies UA investment at scale. The D30 retention figure is the most important input into that model, because it determines the shape of the LTV curve past the first month.
The early ROAS trap: a cohort can hit strong D7 ROAS while the underlying retention curve is already collapsing. Early ROAS rewards fast monetizers, not durable ones. A cohort that looks profitable at D7 may never reach the D30, D90, or D180 LTV the original model projected if D30 retention is structurally weak. Publishers who have been burned by this pattern screen specifically for the gap between D7 ROAS and D30 retention as an early warning signal.
LiveOps roadmap evaluation
Publishers increasingly evaluate whether a studio has a credible plan to sustain D30 retention through the live phase, not just whether the product's inherent design produces good early retention numbers.
A game with 35% D1 and no LiveOps plan is a game that will decay toward the median D30 within 60 to 90 days of launch. A game with the same D1 and a structured LiveOps program, content pipeline, and event cadence is a meaningfully different investment proposition. The retention curve a game shows at soft launch is the starting point. The LiveOps program is what determines where that curve lands 12 months later.
How Galaxy4Games Approaches Retention
At Galaxy4Games, retention is a design constraint from the first day of production, not a metric reviewed after launch. That approach is built into the three components of the studio's proprietary in-house technology: the Game Application Template, the Modular Solutions Library, and the LiveOps-ready Framework. Each plays a distinct role in how retention is built, measured, and sustained.
The Game Application Template is the production foundation every project starts from. It is not a generic scaffold or a no-code constructor. It is internal production infrastructure that includes core architecture, platform integrations, store compliance, backend connectivity, analytics hooks, and LiveOps readiness from day one. Analytics instrumentation is part of that foundation: session tracking, return rate monitoring, event tracking, and balancing support are operational before the game reaches soft launch, not bolted on afterward. The result is that retention data is visible and actionable from the first real cohort.
The Modular Solutions Library is where the specific mechanics that move D7 and D30 retention live. It is a growing collection of production-ready systems, refined through 15+ years of real game production and live game operations across multiple genres. It covers analytics infrastructure, retention systems, event infrastructure, daily rewards, progression loops, monetization features, social mechanics, and LiveOps tooling. Critically, every project at Galaxy4Games remains fully custom: gameplay vision, progression design, art direction, monetization strategy, and technical architecture are built around the specific product. The library eliminates the need to rebuild solved production challenges from scratch, which frees the team to focus development effort on the things that actually differentiate a game in the market.
The LiveOps-ready Framework closes the operational loop. It is designed for long-term game operations: event management, content pipelines, analytics integration, retention systems, monetization optimization, and scalable live content delivery. Because Galaxy4Games also operates its own live titles on the App Store and Google Play, the framework is not theoretical. It reflects the real operational demands of running games in a live market, including the content cadence, event timing, and behavioral data loops that separate top-quartile D30 performance from median decay.
Together, these three components compress development timelines and costs by 30 to 50% compared to conventional blank-slate production, without trading away quality, customization, or long-term scalability.
For studios and publishers evaluating whether a game is retention-ready for soft launch or publisher conversations, or diagnosing why an existing game's retention curve is below genre expectation, Galaxy4Games offers a free consultation to assess the specific structural causes and the interventions most likely to move each part of the curve.
Learn more about LiveOps game development services, data-driven game design, and mobile game development services.
Further Reading
Retention and KPIs
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Understanding Game KPIs: Metrics Every Publisher and Studio Should Track — Galaxy4Games
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Why Is My Casual Game Not Retaining Users Long-Term? Diagnosis and Fixes — Galaxy4Games
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Data-Driven Game Design: How Studios Use Player Behavior to Improve Retention — Galaxy4Games
LiveOps and Retention
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The Definitive LiveOps Guide for Mobile and PC Games 2026 — Galaxy4Games
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Best Practices for LiveOps in Mobile and Online Games — Galaxy4Games
Services
Sources
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2026 Mobile & PC Gaming Benchmarks — GameAnalytics (primary source for all tier distribution and regional data in this article)
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GameAnalytics: Mobile and PC Game Benchmarks in 2026 — GameDevReports / Substack (summary and corroboration of GameAnalytics 2026 report)
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Mobile Game Retention in 2026 — AppFollow (mid-core and RPG genre retention reference; commercially performing title ranges)
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Understanding Game KPIs: Metrics Every Publisher and Studio Should Track — Galaxy4Games
