State of Subscription Apps 2026

Founder’s letter

Methodology

Overview of the dataset

This report draws on subscription app performance data from a wide range of apps that use RevenueCat’s platform. Our goal is to provide a comprehensive snapshot of how apps are performing under different scenarios, across iOS, Android and web ecosystems.

• Scope of apps included: we included apps that have active subscription revenue, meet a minimum threshold of installs or revenue (to ensure statistically meaningful findings), and have integrated RevenueCat for in-app subscription management.
• Time frame: the target time frame for metrics in this report is 2025. In some cases we have pulled older data to run certain calculations (we can’t calculate third renewal rate for annual subscriptions bought in 2024, for example)
• Size and composition: we analyzed over 115,000 apps across all app categories, covering more than $16 billion in revenue across more than a billion transactions. The apps vary in scale, from indie teams to mid-size organizations and large publishers.
• Revenue channels: the dataset includes both apps that primarily generate revenue from in-app subscriptions and those that generate a portion of revenue from subscriptions alongside other revenue channels.
• Anonymity: all data is anonymized and aggregated, ensuring that no single app’s performance metrics are individually identifiable. The findings are presented as aggregated performance benchmarks across segments, categories, and platforms.

Anonymization and data privacy

To preserve the confidentiality of individual apps, we apply controls to endeavor that if a segment has too few apps, results are either omitted from the report or combined with a larger segment to avoid the possibility of inferring any single app’s data. Throughout this report, numbers represent aggregated totals, averages, medians, quartiles, or other summary statistics. No app-specific or developer-specific details are ever disclosed.

Statistical definitions

Throughout this report we aim to use clear, accessible language and minimize unnecessary jargon. However, some key statistical terminology is used at times.

The following measures of central tendency and spread have been used to illustrate app performance.

• Bottom quartile (Q1): The value below which 25% of the dataset falls. An app that falls into the bottom quartile is among the lower 25% of performers on that metric.
• Median (Q2): The middle value, with half of the data above and half below. When comparing your own metrics to the median, you can see if you are performing above or below the midpoint of the industry.
• Upper quartile (Q3): The value above which 25% of the dataset falls. An app in the upper quartile is among the top 25% of performers for that metric.
• P90: The 90th percentile. This indicates the point at or above which 10% of the dataset lies. An app at P90 is outperforming 90% of apps in that particular metric (aka, crushing it).

Reading the charts

We often use candlestick (box-and-whisker–style) charts to show the distribution of a given performance metric (e.g. RPI, LTV) across apps. The ‘box’ represents the bulk of distribution, the interquartile range, while the ‘whiskers’ represent the lower and upper bounds of performance.

Percentile mapping

• Lower ‘whisker’: marks P10 (10th percentile), the bottom 10% of app performance.
• Bottom of the ‘box’: marks P25 (25th percentile) and represents Q1 (bottom quartile) — apps below this make up the lowest 25% of performers.
• Marker inside the ‘box’: marks P50 (50th percentile) and represents Q2 (median) — this is the midpoint of app performance.
• Top of the ‘box’: marks P75 (75th percentile) and represents Q3 (upper quartile) — apps above this fall into the top 25% of performers.
• Upper ‘whisker’: marks P90 (90th percentile) — apps here or above are the highest performers.
• Any points outside P10–P90 indicate unusually low or high performance outliers.

Data not based on RevenueCat

While the majority of the metrics in this report derive from aggregated app subscription data (via RevenueCat), two charts within the State of the market chapter feature data not from RevenueCat. This data has been provided by Appfigures, and is indicated on the relevant pages.

Measures we include

Below are some of the included metrics in this report that benefit from some additional context. Each metric is calculated consistently across all apps to allow for accurate comparison.

• Realized lifetime value (RLTV) per payer: the net value of an average paying user over a specific period of time, including initial subscriptions, renewals, reactivations, expansion, and one-time purchases.
• Revenue per install (RPI): total revenue earned divided by total installs. This metric highlights how well an app monetizes each new user.
• Active renewal rate: the share of renewals that are done by subscribers that were active in the second half of the previous subscription period (in case of a monthly subscription, this asks if the user was seen in the app in the ~15 days prior to the renewal).
• Reactivation rate: the share of churned subscribers that become active in the 12 months following a churn event.
• MRR growth rate (year-on-year): the percentage change in an app’s monthly recurring revenue between two point-in-time snapshots (end of the previous year vs. end of the current year). MRR is normalized to a 30-day basis regardless of plan duration.
• Download-to-paid conversion rate (D35): the share of installs that result in at least one paid subscription within 35 days of the install date. This metric captures how effectively an app converts new users into paying customers in the first ~5 weeks.
• Download-to-trial conversion rate: the share of installs that start a free trial within 30 days of the download date. This metric is calculated for apps that use a trial-based acquisition strategy.
• Trial-to-paid conversion rate: the share of free trial starts that convert into a paid subscription.
• Retention rate: the share of paid subscriptions that remain active after a given time period (e.g. 6 months, 12 months). A subscription is considered ‘retained’ if it has accumulated enough paid renewals to cover the elapsed time — for example, 12 monthly renewals for 12-month retention, or 1 annual renewal for yearly plans. This is a subscription-level metric, not a user-level metric.
• Renewal rate (1st, 2nd, 3rd): the share of subscriptions that successfully renew at each sequential billing cycle. This differs from retention rate, which measures cumulative survival over time.
• Refund rate: the share of paid subscriptions that are refunded during their first billing period.
• Monthly trailing revenue (MTR): a 30-day rolling revenue figure at a specific point in time, used to measure an app’s revenue run-rate. This is the basis for the ‘monthly revenue 1 year after launch’ and ‘time to revenue milestones’ metrics in this report.

Segments we cover

To provide nuanced insights, we break down certain metrics by segments. These segments offer a closer look at how different development choices and distribution methods might impact subscription metrics.

• Access method: how users primarily access the app (freemium, via a hard paywall).
• App development framework: the primary technology stack used for app development (e.g., native iOS/Android, Flutter, React Native, Other).
• Pricepoint: how an app’s average pricepoint compares to the rest of the measured apps (below average, average, above average).
• Developer HQ: the (estimated) region the app developer team is based in.
  • Regions are bucketed together: Asia-Pacific, IN/SEA (India & Southeast Asia), Latin America, MEA (Middle East & Africa), North America, Western Europe, ROW (rest of world), all regions.
• Geography: the region users are based in.
• AI vs. non-AI app: whether an app uses AI/ML models for its primary value (e.g. generative AI, chatbots and AI assistants, predictive analytics, AI photo/video editing, AI writing tools).
  Note: apps not categorized as ‘AI apps’ may still use basic ML or have minor AI features.

Category bucketing (App Store and Google Play)

The App Store (iOS) and Google Play (Android) each have numerous categories. For clearer analysis, we’ve aggregated or ‘bucketed’ closely-related categories under common labels:

• Utilities: includes Weather, Reference, Utilities, Finance, Tools, and more.
• Health & Fitness: includes Health & Fitness, Medical.
• Media & Entertainment: includes Entertainment, Music, News, Magazines & Newspapers, Sports, and more.
• Education: includes Education, and Educational.
• Productivity: includes Graphics & Design, Art & Design, Developer tools.
• Social & Lifestyle: includes Lifestyle, Social Networking, Social, Dating.
• Gaming: includes Games, Puzzle, Casual, Word, Simulation, Board, and more.
• Photo & Video: Includes Photo & Video, Photography, Video Players & Editors.
• Business: Includes Business.
• Travel: Includes Travel, Travel & Local.
• Shopping: Includes Shopping.

We have done this to simplify comparisons — especially when certain official categories have too few apps to provide stable, anonymized benchmarks.

Key insights

State of the market

Where are subscription apps growing fastest, based on developer HQ?

Median year-on-year monthly recurring revenue growth rate by developer HQ

Region

Swipe chart

Key takeaway

Half of all apps grew MRR by at least 5.3% YoY, but the spread is enormous: the top 10% grew 306%+, while the bottom 10% shrank sharply.

Benchmarks to know

• Median growth of ~5–17% puts you in the middle of the pack.
• Shrinking by more than 33% places you in the bottom quartile.
• Growing 80%+ means you’re outpacing 75% of apps.

What stands out

• MEA is the only geography with negative median growth (−9.7%).
• Latin America shows the highest median growth (17.2%).
• Several geographies show extreme right-tail outliers above 300% growth (IN/SEA, Latin America, MEA, ROW, and overall).

What annual value does each payer generate?

Realized lifetime value (RLTV) per payer after Year 1 by developer HQ

Region

Swipe chart

Key takeaway

Apps by North American developers realize about 40% more annual value per payer ($32) than the global median ($23), while IN/SEA apps realize the least at $14.

Benchmarks to know

• $23 annual RLTV per payer is the global median.
• $44+ puts you in the top quartile globally.
• Below $10 places you in the bottom quartile in many geographies.

What stands out

• North America’s median ($32) is 2.3× higher than IN/SEA ($14).
• Western Europe is the next-highest median ($25).
• IN/SEA has a relatively tight middle range compared to other geographies, suggesting less variance in payer value.

What’s the D35 download-to-paid conversion rate by developer HQ geography?

Conversion rate to payer by developer HQ

Region

Swipe chart

Key takeaway

North America leads D35 conversion at 2.6% median, nearly 2× IN/SEA’s 1.4%.

Benchmarks to know

• North America median: 2.6%, top quartile above 5.6%.
• Western Europe median: 2.0%, higher than every other geography outside of North America.
• IN/SEA median: at 1.4%, converts at the lowest rate of all geographies.

What stands out

• North America top performers reach 10.4% at the 90th percentile.
• Latin America (1.5%) sits toward the bottom, closer to IN/SEA than North America or Western Europe.
• Geographical gaps in conversion are narrower than other revenue metrics.

What does the iOS vs. Android split of new subscription app launches look like, and how has it changed?

New subscription apps launched per month (Feb 2022–Feb 2026)

Month

Platform

Swipe chart

• iOS
• Android

Key takeaway

Monthly subscription app launches have grown 7× since January 2022, but this is almost entirely an iOS story. Android has grown at roughly half the rate, and the gap is widening.

Benchmarks to know

• ~2,000 new subscription apps launched per month in Jan 2022; 14,700+ by Jan 2026.
• iOS now accounts for ~77% of all new subscription app launches, up from ~67% in 2023.
• Android absolute launches have grown – from ~700 to ~3,300/month – but iOS has lapped it.

What stands out

• The steepest iOS acceleration begins in early 2025, coinciding with the rise of AI-assisted development tools, which appear to default to App Store-first.
• Android’s share of new launches has been declining since mid-2023, despite growing in absolute terms.

Growth teams of 2026 won’t look the same as they do today

Do older apps dominate the market?

Monthly revenue by app launch cohort across all storefronts (Jan 2026)

Launch cohort

Swipe chart

Key takeaway

The subscription economy runs on established apps: apps launched before 2020 generate 69% of all subscription revenue. Despite a 7× surge in new app launches since 2022, apps launched before 2020 still account for nearly 70 cents of every dollar generated. Apps launched in 2025 or later (aka, the vibe coding era) account for just 3%.

What stands out

• The ‘before 2020’ cohort generates more revenue per app than any other group by a wide margin — these are the apps that had years to build audiences, optimize monetization, and compound growth.
• The 2022–2023 cohort outperforms 2020–2021 in absolute revenue, driven by a handful of breakout apps that launched in that window.
• Apps launched in 2024 and 2025 are generating real revenue, but at a fraction of what older cohorts produce and with far more competition than those cohorts ever faced.

Winning big

Macro trends: key takeaways

The subscription market is expanding, but outcomes are uneven. The median app grew monthly recurring revenue (MRR) 5.3% year-on-year, but top-decile apps grew 306%+, while the bottom decile contracted sharply. 

Monetization strength varies materially by developer HQ: North America leads with $32 median realized lifetime value (RLTV) per payer after Y1, compared to a $23 global median and $14 in IN/SEA. 

Conversion gaps exist, but they’re tighter than revenue gaps — North America’s median D35 download-to-paid rate is 2.6% vs. 1.4% in IN/SEA. Meanwhile, supply is accelerating, but new ≠ better: monthly new subscription app launches increased from ~2,000 in January 2022 to 14,700+ by January 2026 (likely driven by the AI app explosion), yet apps launched before 2020 still generate 69% of all subscription revenue.

What stands out

Growth is concentrated in the right tail: the median YoY MRR growth rate is 5.3%, but the 90th percentile exceeds 306%. Shrinking more than 33% places an app in the bottom quartile, underscoring how polarized outcomes are.

Value-per-payer differs hugely between regions: median Y1 RLTV per payer is $32 in North America, $25 in Western Europe, $23 globally, and $14 in IN/SEA. The spread between top and bottom regions is more than 2x.

Conversion gaps are meaningful, but narrower than value-per-payer: median D35 conversion is 2.6% in North America, 2% in Western Europe, and 1.4% in IN/SEA. Even top North America performers (10.4% at the 90th percentile) don’t offset weaker long-term monetization in lower-LTV regions.

Launch growth is real — and skewed to iOS: monthly launches grew roughly 7x over four years. iOS now represents ~77% of new subscription app launches, up from ~67% in 2023.

Revenue remains anchored in older cohorts: apps launched before 2020 account for 69% of all subscription revenue. Apps launched in 2025 or later contribute just 3%, despite the surge in new supply.

Store and revenue economics

How do monetization strategies differ across app categories?

Monetization mix by category

App category

Monetization model

Swipe chart

• Subscriptions Only
• Subscriptions + Lifetime
• Subscriptions + Consumables
• Subscriptions, Consumables, and Lifetime

Key takeaway

Most categories favor pure subscriptions (63.5% overall); Gaming is the outlier at 40.5% subs-only with the heaviest consumable usage (27.5%).

Benchmarks

• Overall: 63.5% subs-only, 23.2% + lifetime, 10.7% + consumables, 2.5% all three.
• Shopping (79.6%) and Business (76.5%) are the purest subscription categories.
• Gaming is the most evenly split: 40.5% subs-only, 27.5% consumables, 9.6% all three.

What stands out

• Gaming’s “all three” rate is 4× the overall average (9.6% vs. 2.5%).
• Photo & Video has highest lifetime combo usage at 33.0%.

Hybrid monetization: still nascent, with different paths opening up

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How do monetization strategies differ across geographies?

Monetization mix by geography

Region

Monetization model

Swipe chart

• Subscriptions Only
• Subscriptions + Lifetime
• Subscriptions + Consumables
• Subscriptions, Consumables, and Lifetime

Key takeaway

Geography barely moves the needle: subscriptions-only spans 56.4–61.0% across all geographies, a spread of just 4.6pp.

Benchmarks to know

• North America: 61.0% subs-only (highest).
• Western Europe: 60.3% subs-only.
• IN/SEA: 56.4% subs-only (lowest), 29.2% + lifetime (highest).
• All geography: ~3% use all three types.

What stands out

• Asia-Pacific has highest consumable combination at 12.2%.
• Lifetime combos range 25–29% across geographies — tight clustering.
• Geographic uniformity is extreme — all within 4.5% of baseline across all models.
• North America slightly favors subs-only, while N/SEA favors lifetime (+1.3 points).
• No meaningful geographic preference for any monetization approach.

Don’t settle for one paywall design

Which plan durations do subscribers choose by category?

Plan duration mix by category

App category

Plan duration

Swipe chart

• Weekly
• Monthly
• Yearly
• Other

Key takeaway

Gaming is dominated by weekly plans (82%), while Health & Fitness leads annual adoption at 68%. Plan duration strategy varies dramatically by category economics.

Benchmarks to know

• Weekly, monthly, and annual each capture roughly a third overall.
• 68%+ annual indicates retention-focused strategy.
• 80%+ weekly signals high-churn, high-volume model.

What stands out

• Gaming (82% weekly) and Health & Fitness (68% annual) represent opposite extremes.
• Productivity is the monthly outlier at 77%.
• Education, Travel, and Shopping all favor annual plans (59–66%).

Which plan durations drive revenue by category?

Revenue share by subscription duration

App category

Plan duration

Swipe chart

• Weekly
• Monthly
• Yearly
• Other

Key takeaway

Revenue concentration by duration diverges sharply from volume — Productivity drives 77% of revenue from monthly plans, while Health & Fitness captures 68% from annual.

Benchmarks to know

• Monthly subscriptions dominate overall revenue share.
• Annual plans drive majority revenue in Health & Fitness, Education, Travel.
• Weekly plans rarely exceed 30% of category revenue except Gaming.

What stands out

• Productivity’s 77% monthly revenue share is highest of any category-duration.
• Gaming’s weekly volume (82%) translates to lower revenue share due to price.
• Shopping shows 66% annual revenue despite lower volume penetration.

How does web revenue adoption vary by app revenue tier?

Apps with web revenue by revenue tier

Revenue tier

Swipe chart

Key takeaway

Web revenue adoption scales dramatically with tier: 41% of top-performing apps (Tier 5) generate web revenue vs. just 1.3% of hobby apps (Tier 1).

Benchmarks to know

• Tier 5: 41% web adoption.
• Tier 4: 28% web adoption.
• Tier 1: 1.3% web adoption.

What stands out

• 31× difference between Tier 5 (41%) and Tier 1 (1.3%).
• Clear step function: each tier roughly doubles the previous.
• Suggests web infrastructure investment correlates with scale.

The rise of web revenue blends three different tactics quietly routing around platforms

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What’s the D14 revenue benchmark?

Average revenue per install (RPI) at Day 14 by category

App category

Swipe chart

Key takeaway

Health & Fitness leads early monetization at $0.48 median RPI at D14, nearly 6× higher than Gaming’s $0.08 — category economics diverge sharply.

Benchmarks to know

• $0.23 median at D14 across all categories.
• $0.48+ indicates strong early monetization (top quartile Health & Fitness).
• Under $0.10 suggests volume-dependent business model.

What stands out

• Health & Fitness ($0.48) leads; Gaming ($0.08) trails.
• Business ($0.31) and Education ($0.30) monetize early.
• Gaming’s tight spread suggests consistent low-average RPI model.

How does revenue grow from D14 to D60?

Average revenue per install (RPI) at Day 60 by category

App category

Swipe chart

Key takeaway

By D60, Health & Fitness reaches $0.66 median RPI (still 4.7× Gaming’s $0.14) with gaps widening as retention-focused categories compound value.

Benchmarks to know

• $0.34 median at D60 across all categories.
• $0.66+ indicates strong 60-day monetization.
• 1.5× D14→D60 multiplier is typical.

What stands out

• Health & Fitness grows from $0.48 (D14) to $0.66 (D60): 1.4× multiplier.
• Gaming grows from $0.08 to $0.14: 1.7× multiplier but low absolute value.
• Business shows highest absolute $ growth: $0.31 to $0.50 (+$0.19).

Which geographies generate the highest D14 revenue?

Average revenue per install (RPI) at Day 14 by geography

Region

Swipe chart

Key takeaway

North American users generate $0.38 median RPI at D14 (5× higher than IN/SEA’s $0.08), reflecting purchasing power and monetization maturity.

Benchmarks to know

• North America: $0.38 median.
• Western Europe: $0.25 median.
• IN/SEA: $0.08 median.

What stands out

• 5× gap between North America ($0.38) and IN/SEA ($0.08).
• Asia-Pacific ($0.28) outperforms Western Europe ($0.25).
• Latin America, MEA, ROW cluster tightly around $0.10.

How does D60 revenue vary by geography?

Average revenue per install (RPI) at Day 60 by geography

Region

Swipe chart

Key takeaway

North American apps generate 5× higher D60 RPI than IN/SEA apps, with a median of $0.55 vs. $0.11.

Benchmarks to know

• North America median: $0.55, top quartile above $1.39.
• Europe median: $0.33, balanced performance.
• IN/SEA median: $0.11, reflects lower pricepoints.

What stands out

• 5× gap between highest and lowest geographies.
• North America’s top performers reach $3.19 at the 90th percentile.
• LATAM tracks closer to Europe than to IN/SEA.

Do longer plans drive more revenue?

Average revenue per install (RPI) after 14 and 60 days split by plan duration

Plan duration

Time

Swipe chart

• Day 14
• Day 60

Key takeaway

Apps whose most popular plan is yearly generate the highest total RPI at both D14 ($0.36) and D60 ($0.46). Note: each app is classified by its most-sold plan duration, but the revenue figure reflects all revenue from that app — not just revenue from that plan type.

Benchmarks to know

• Yearly-dominant apps: D14: $0.36, D60: $0.46.
• Monthly-dominant apps: D14: $0.18, D60: $0.29.
• Weekly-dominant apps: D14: $0.19, D60: $0.32.
• Lifetime-dominant apps: D14: $0.19 ,D60: $0.24.

What stands out

• Apps that primarily sell yearly subscriptions monetize installs ~2× better than other groups at D14, widening slightly to D60.
• The spread for yearly-dominant apps is notably large, suggesting high variance; some monetize extremely well, others modestly.
• Growth from D14→D60 is strongest for weekly (+68%) and monthly (+61%) dominant apps, consistent with recurring short-cycle billing accumulating over time.

Most subscription apps should optimize their monetization strategies to maximize RPI, particularly those supporting AI-powered features with non-trivial underlying costs

Does pricing strategy affect D14 revenue?

Average revenue per install (RPI) after 14 days split by pricepoint

Pricepoint

Swipe chart

Average revenue per install (RPI) after 14 days split by access method

Access method

Swipe chart

Key takeaway

Hard paywall apps generate 9× more D14 RPI than low-priced freemium apps, with a median of $2.32 vs. $0.27.

Benchmarks to know

• Hard paywall median: $2.32, top quartile above $4.50.
• High-priced median: $0.61, solid middle ground.
• Low-priced median: $0.08, volume-dependent model.

What stands out

• Hard paywalls dominate early monetization.
• 8× spread between highest and lowest pricing tiers.
• Freemium sits at ~12% of hard paywall performance.

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How does pricing strategy affect D60 revenue?

Average revenue per install (RPI) after 60 days split by pricepoint

Pricepoint

Swipe chart

Average revenue per install (RPI) after 60 days split by access method

Access method

Swipe chart

Key takeaway

Hard paywall apps maintain dominance at D60 with $3.09 median, 8x higher than freemium at $0.38.

Benchmarks to know

• Hard paywall median: $3.09, top quartile above $5.50.
• High-priced median: $0.94, growth continues post-D14.
• Low-priced median: $0.11, modest gains from D14.

What stands out

• Hard paywalls grow 33% from D14 to D60.
• Gap between tiers persists through the funnel.
• Low-priced apps see only $0.03 increase from D14.

What’s monthly revenue per paying customer?

Realized lifetime value (RLTV) per payer after 1 month by category

App category

Swipe chart

Key takeaway

Health & Fitness leads month 1 RLTV at $24.23 median, nearly 3× Gaming’s $8.41.

Benchmarks to know

• Health & Fitness median: $24.23, top quartile above $39.00.
• Business median: $18.76, strong B2B positioning.
• Gaming median: $8.41, lower pricepoints but higher volume.

What stands out

• 3× spread between top and bottom categories.
• Health & Fitness top performers exceed $60 RLTV.
• Travel and Utilities cluster in the middle tier.

What’s yearly revenue per payer?

Realized lifetime value (RLTV) per payer after 1 year by category

App category

Swipe chart

Key takeaway

Health & Fitness apps lead yearly RLTV at $35.64 median, more than 3× Gaming’s $11.22.

Benchmarks to know

• Business median: $35.48, top quartile above $69.19.
• Health & Fitness median: $35.64, strong retention value.
• Gaming median: $11.22, lower annual commitment.

What stands out

• The best Business apps see over $120 RLTV per payer after Y1.
• 3× spread from top to bottom categories.
• Productivity ($24.95) and Education ($22.82) form solid mid-tier.

How does monthly RLTV vary by geography?

Realized lifetime value (RLTV) per payer after 1 month by geography

Region

Swipe chart

Key takeaway

Western Europe leads monthly RLTV at $17.89 median, 69% higher than IN/SEA’s $10.59.

Benchmarks to know

• North America median: $17.02. top quartile above $28.
• Europe median: $17.89, outperforms NA.
• IN/SEA median: $10.59, lowest but still substantial.

What stands out

• Tighter geographical spread than revenue per install (RPI) metrics.
• Europe spends more per payer, but converts at a lower rate.
• All geographies  show significant upside in top quartile.

How does yearly RLTV vary by geography?

Realized lifetime value (RLTV) per payer after 1 year by geography

Region

Swipe chart

Key takeaway

Western Europe leads yearly RLTV at $26.64 median, 38% higher than IN/SEA’s $19.32.

Benchmarks to know

• North America median: $26.07 — top quartile above $46.
• Europe median: $26.64 — just above NA.
• IN/SEA median: $19.32 — lowest annual value.

What stands out

• Geographical  gaps narrower for payers after Y1.
• Top quartile shows 2× upside across all geographies.
• NA, APAC, and Western Europe make up Tier 1.

How does pricing affect monthly RLTV?

Realized lifetime value (RLTV) per payer after 1 month by pricepoint

Pricepoint

Swipe chart

Realized lifetime value (RLTV) per payer after 1 month by access method

Access method

Swipe chart

Key takeaway

High-priced apps generate $35.89 monthly RLTV median, 5.4× higher than low-priced apps at $6.67.

Benchmarks to know

• High-priced median: $35.89, top quartile above $56.
• Mid-priced median: $15.78, balanced positioning.
• Low-priced median: $6.67, volume-dependent.

What stands out

• 5.4× spread from high to low pricing tiers.
• Mid-priced performs at roughly half of high-priced.
• Hard paywall generates close to double revenue vs. freemium.

What’s the yearly revenue opportunity?

Realized lifetime value (RLTV) per payer after 1 year by pricepoint

Pricepoint

Swipe chart

Realized lifetime value (RLTV) per payer after 1 year by access method

Access method

Swipe chart

Key takeaway

High-priced apps dominate yearly RLTV at $62.19 median, nearly 6× low-priced apps at $10.69.

Benchmarks to know

• High-priced median: $62.19, top quartile above $109.64.
• Mid-priced median: $28.75, less than half of high-priced.
• Low-priced median: $10.69, up $4.02 from month 1.

What stands out

• High-priced Y1 RLTV is 79% higher than month 1.
• 6× spread between pricing tiers.
• Low-priced sees the smallest % lift from month 1 to Y1.

Which categories show best post-launch traction?

Monthly revenue 1 year after launch by category

App category

Swipe chart

Key takeaway

Cross-category median is ~$72, but the top 10% pull $2,500+, a 36× gap that defines this metric’s extreme right skew.

Benchmarks to know

• If you’re at ~$72/mo, you’re at the overall median 1 year post-launch.
• If you’re above $429, you’re in the top quartile.
• If you’re above $2,574, you’re in the top 10% across all categories.
• Photo & Video leads category medians at $124; Travel trails at $35.

What stands out

• Gaming’s top 10% reaches $4,554, nearly 2× the all-category top 10%, despite a below-median center ($56).
• The middle 50% spans $16–$429 overall, a 27× spread, unusually wide for a revenue metric.
• Travel is the most compressed category: top 10% at just $822 vs. $3,600+ for Photo & Video.

The boom in non-game app revenue and what’s driving it

How long does it take apps to reach monthly revenue milestones?

Median number of days from launch to revenue milestones

App category

Revenue milestone

Swipe chart

• $1K MR
• $2.5K MR
• $5K MR
• $10K MR

Key takeaway

Gaming reaches $1K monthly revenue fastest (32 days median), while Business takes 113 days, a 3.5× difference.

Benchmarks to know

• Gaming to $1K: 32 days → to $10K: 53 days.
• Social & Lifestyle to $1K: 45 days = fast early traction.
• Business to $1K: 113 days = slower but higher lifetime value (LTV).

What stands out

• Gaming’s speed advantage persists through $10K milestone.
• Shopping shows erratic progression (59 → 238 → 296 days).
• All Categories median: 58 days to $1K, 109 days to $10K.

What share of apps hit monthly revenue milestones?

Share of newly-launched apps that hit revenue milestones in their first 2 years

App category

Revenue milestone

Swipe chart

• $1K MR
• $2.5K MR
• $5K MR
• $10K MR

Key takeaway

Photo & Video leads with 21.4% hitting $1K monthly revenue, while only 4.6% of all apps reach $10K.

Benchmarks to know

• Photo & Video: 21.4% hit $1, 7.3% hit $10K.
• Gaming: 20.0% hit $1K, 8.9% hit $10K (highest $10K rate).
• All Categories: 17.3% hit $1K, 4.6% hit $10K.

What stands out

• Gaming has highest $10K hit rate despite mid-tier $1K rate.
• Business: 14.7% hit $1K but only 1.6% reach $10K.
• ~75% drop-off from $1K to $10K milestone across categories.

How to repurpose offline events into millions of online impressions

Store and revenue economics: key takeaways

Across the subscription ecosystem, revenue concentration is the defining theme. Time-to-revenue varies by more than 3x between categories. Only 4.6% of newly launched apps reach $10K in monthly revenue within two years. Pricing architecture drives a 3x+ spread in realized lifetime value (LTV). Geography creates up to 5x differences in revenue per install (RPI) by D60. And web revenue, while strategically important, remains just 3.2% of total revenue globally.

The pattern is consistent: outcomes cluster tightly around modest medians, with a long tail of high performers driving category economics. If you’re benchmarking performance, the median tells you viability. The upper quartile tells you whether your model scales.

What stands out

Speed-to-revenue is category-dependent: Gaming reaches $1K MRR in 32 days (median), while Business takes 113 days. Only 4.6% of apps reach $10K MRR within two years.

Pricing power compounds: High-priced apps generate $34.82 monthly realized lifetime value (RLTV) per payer, versus $10.69 for low-priced apps, showing a 3.3x spread. At Y1, that gap widens to $62.19 vs. $10.69.

Retention and category model matter more than early ARPU: Health & Fitness leads D14 RPI at $0.48 and D60 at $0.66, nearly 5x Gaming at D60 ($0.14).

Geography shapes ceiling outcomes: North America reaches $0.55 median RPI by D60, vs. $0.11 in IN/SEA — a 5x gap. Regional spreads narrow at annual LTV but remain material.

Revenue mix is highly concentrated: Monthly plans dominate in categories like Productivity (77%), while Health & Fitness captures 68% from annual plans. Web revenue accounts for 3.2% globally, but 4.9% in North America and just 0.8% in IN/SEA.

Funnel performance

How does D30 download-to-trial conversion vary by app category?

Download-to-trial by category

App category

Swipe chart

Key takeaway

Business leads trial conversion at 9.1% median, more than 2× Gaming’s 4.4%.

Benchmarks to know

• Business median: 9.1%, top quartile above 16.2%.
• Other high performers include: Health & Fitness (6.9%), Education (6.5%), and Utilities (6.5%).
• Media & Entertainment (4.0%) and Travel (4.1%) show lower median conversion than Gaming (4.4%).

What stands out

• Most non-Gaming categories convert between 5-6% from download-to-trial.
• 2× gap between top and bottom categories.
• Health & Fitness top performers convert over 23%.

How does D30 download-to-trial conversion vary by geography?

Download-to-trial by geography

Region

Swipe chart

Key takeaway

Download-to-trial rates differ 2× or more across geographies, with North America and Asia-Pacific leading.

Benchmarks to know

• North America median: 7.1% (top quartile above 15.0%).
• Asia-Pacific median: 5.7% (top quartile above 13.5%).
• Western Europe median: 5.0%.
• All other geographies (IN/SEA, LATAM, MEA, and ROW) median between 3.0-3.7%. 

What stands out

• North America’s median is ~2x most of the rest of the world.
• Bottom quartile apps in North America perform similarly to the median in many other geographies.
• Top performers still manage above 14% in every geography.
• Gap widens at higher percentiles: North America’s top 10% reaches nearly 25% — 10% higher than ROW.

How does time-to-paid differ by access method?

Time-to-paid freemium vs. hard paywall

Time

Access method

Swipe chart

• Freemium
• Hard paywall

Key takeaway

More than 60% of conversions happen by Day 7 for both models, but hard paywalls show a pronounced Day 4-7 spike (25.7%) while freemium apps have a longer tail (beyond 6 weeks).

Benchmarks to know

• 1/3 of all conversions happen on day zero for both methods.
• 60%+ of conversions happen within 1 week.
• For freemium apps, 23% of conversions do not occur until 6+ weeks after download.

What stands out

• Hard paywall Day 4-7 spike (25.7%) is driven by 7-day trial expirations.
• Freemium has 1.5× higher late-stage conversions (Week 6+).
• Middle weeks (2-5) are quiet for both models (~1-2% each).
• Implication: Set conversion windows differently by access method — hard paywalls concentrate early, freemium spreads long.

How does download-to-trial conversion vary by pricepoint?

Download-to-trial by pricepoint

Pricepoint

Swipe chart

Key takeaway

Higher-priced apps convert downloads to trials at nearly 2× the rate of low-priced, though with wider variability.

Benchmarks to know

• High-priced median: 8.9% (top quartile above 16.5%).
• Mid-priced median: 5.4% (top quartile above 11.6%).
• Low-priced median: 4.4% (top quartile above 10.3%).

What stands out

• Top 10% of high-priced apps reach 27.0% conversion.
• Price tiers follow a consistent ~1.5–2× step pattern at each percentile.
• Upper quartile rates are ~2x the median at every pricepoint.

Pricing strategy is playing into user psychology

How quickly do users in each app category start trials after downloading an app?

Time to trial by category

Time

App category

Swipe chart

• Business
• Education
• Gaming
• Health & Fitness
• Media & Entertainment
• Photo & Video
• Productivity
• Shopping
• Social & Lifestyle
• Travel
• Utilities

Key takeaway

Nearly all trial starts happen on Day 0 across categories — users who don’t try immediately rarely try at all.

Benchmarks to know

• Business: 89.9% on Day 0 (highest).
• Health & Fitness: 82.1% on Day 0.
• Gaming: 81.5% on Day 0.
• Productivity: 78% on Day 0 (lowest).

What stands out

• Business apps lead with nearly 90% same-day trial starts.
• Productivity (ironically) shows the highest ‘delayed trial’ rate at 22%.
• Day 1–3 captures most remaining starts: 5–12% across categories.
• After Day 3, trial starts drop below 5% in all categories.

How does trial-to-paid conversion vary by app category?

Trial-to-paid by category

App category

Swipe chart

Key takeaway

Travel and Health & Fitness lead with the highest median trial-to-paid conversion rates; Photo & Video and Gaming lag significantly.

Benchmarks to know

• Travel median: 43.5% (top quartile above 62.4%).
• Health & Fitness median: 37.7% (top quartile above 51.4%).
• Photo & Video median: 22.2% (lowest; top quartile above 33.1%).
• Gaming median: 25.0% (top quartile above 39.8%).

What stands out

• Travel, Shopping, and Health & Fitness apps boast the highest floors, with high conversion across all percentiles.
• Media & Entertainment has widest spread: 11.5% to 69.5%.
• Categories with wide variance (Gaming, Media & Entertainment, Utilities) suggest highly variable monetization.

How does trial-to-paid conversion vary by geography?

Trial-to-paid by geography

Region

Swipe chart

Key takeaway

North America, Asia-Pacific, and Western Europe lead; IN/SEA trails at less than half their rate.

Benchmarks to know

• North America median: 34.2% (top quartile above 47.9%).
• Asia-Pacific median: 31.9% (top quartile above 45.6%).
• IN/SEA median: 15.2% (lowest; top quartile above 25.0%).
• Western Europe median: 29.7%.

What stands out

• IN/SEA’s top quartile (25.0%) barely exceeds other geographies’ medians.
• North America’s floor (15.6%) matches IN/SEA’s median exactly.
• Top 10% reach 60%+ in North America, Asia-Pacific, and Western Europe.
• Latin America, MEA, and ROW cluster together at ~20–23% median.

Does trial length affect trial-to-paid conversion rate?

Trial-to-paid by trial duration

Trial duration

Swipe chart

Key takeaway

Longer trials convert better: 17–32 day trials outperform short trials by ~17pp at median.

Benchmarks to know

• 17–32 day trials median: 42.5% (top quartile above 59.4%).
• 5–9 day trials median: 37.4% (top quartile above 52.8%).
• ≤4 day trials median: 25.5% (top quartile above 38.5%).

What stands out

• Longer trials show 1.7× better conversion than shortest trials.
• The 10–16 day range has unusual spread: very low floor but strong upper quartiles.
• 5–9 days appears to be a ‘sweet spot’ balancing length and conversion.

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When do users cancel trials, and how does this vary by trial duration?

% of trial cancellations by day and trial duration

Time

Trial duration

Swipe chart

• 30 day trial
• 14 day trial
• 7 day trial
• 3 day trial

Key takeaway

Most users cancel trials immediately: Day 0 dominates cancellations across all trial lengths. Shorter trials see especially front-loaded churn.

Benchmarks to know

• 3-day trials: 55.4% cancel on Day 0.
• 7-day trials: 39.8% cancel on Day 0.
• 14-day trials: 35.7% cancel on Day 0.
• 30-day trials: 31.1% cancel on Day 0.

What stands out

• Over half of 3-day trial cancellations happen within hours of starting.
• 84% of 3-day trial cancellations and 64% of 7-day trial cancellations occur between Day 0 and Day 1.
• 7-day trials show elevated cancellations between Days 3 through 6.

Stop celebrating conversion wins before checking renewals

Which categories best convert downloads into paid users?

Day 35 download-to-paid by category

App category

Swipe chart

Key takeaway

Health & Fitness leads download-to-paid conversion; Gaming trails at roughly one-third the median rate.

Benchmarks to know

• Health & Fitness median: 2.9% (top quartile above 6.2%).
• Business median: 2.6% (top quartile above 5.0%).
• Gaming median: 1.0% (lowest; top quartile above 2.3%).
• Shopping median: 1.3%.

What stands out

• The floor for most categories is fairly consistent (0 – 0.3%), but ceilings diverge sharply.
• Gaming’s top quartile (2.3%) barely exceeds many categories’ medians.
• Top performing categories (Health & Fitness, Education, Business) also show the largest spread between Upper Quartile and Top 10%.

How does download-to-paid conversion vary by geography?

Day 35 download-to-paid by geography

Region

Swipe chart

Key takeaway

North America converts downloads at 4× the rate of IN/SEA; Asia-Pacific follows closely behind.

Benchmarks to know

• North America median: 2.8% (top quartile above 6.0%).
• Asia-Pacific median: 2.4% (top quartile above 5.1%).
• IN/SEA median: 0.7% (lowest; top quartile above 1.9%).
• Globally, median lands at 2.0%.

What stands out

• IN/SEA’s top quartile (1.9%) falls short of most geographies’ medians.
• North America’s top quartile beats most other geographies’ medians.
• Top 10% reach double-digit conversion only in North America (10.9%).

Does access method impact download-to-paid conversion within 35 days?

Day 35 download-to-paid freemium vs. hard paywall

Access method

Swipe chart

Key takeaway

Hard paywalls convert 5× better than freemium, but with significantly wider variance.

Benchmarks to know

• Hard paywall median: 10.7% (top quartile above 20.0%).
• Freemium median: 2.1% (top quartile above 4.5%).

What stands out

• Hard paywall’s floor (4.2%) is 2× the freemium median.
• Top 10% of hard paywall apps reach 38.7% conversion.
• Freemium shows much tighter distribution: 0.3%–8.2% vs.hard paywall’s 4.2%–38.7%.
• Hard paywall’s wide spread suggests execution matters more than model alone.

Maximize conversions with premium positioning and hard paywalls

How does pricing affect download-to-paid rates?

Day 35 download-to-paid by pricepoint

Pricepoint

Swipe chart

Key takeaway

Median high-priced apps convert downloads 2× better than low-priced apps.

Benchmarks to know

• High-priced median: 2.8% (top quartile above 6.1%).
• Mid-priced median: 2.0% (top quartile above 4.4%).
• Low-priced median: 1.4% (top quartile above 3.7%).

What stands out

• Price tiers show consistent ~1.4× step-up at each percentile.
• High-priced apps show widest spread: top 10% reach 13.5%.
• Low-priced floor (0.1%) vs.high-priced floor (0.3%) shows similar minimums.
• Top performers at all pricepoints reach 4-5x the median.

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How quickly do users convert from download-to-paid subscription by category?

Time-to-paid by category

Time

App category

Swipe chart

• Business
• Education
• Gaming
• Health & Fitness
• Media & Entertainment
• Photo & Video
• Productivity
• Shopping
• Social & Lifestyle
• Travel
• Utilities
• All categories

Key takeaway

Half of all conversions happen on Day 0; Productivity leads significantly at nearly 72%, while Travel shows more delayed conversion. 

Benchmarks to know

• Day 0 conversion: 50.6% overall, 71.9% for Productivity.
• Week 6+ conversion: 19.2% overall, 28.2% for Travel.
• Education: 28.5% on Day 0 (lowest immediate conversion).

What stands out

• Conversion timelines are impacted by trial lengths across categories: categories like Education and Health & Fitness, where 7-day trials are common, show increased conversion at the 7-day mark.
• Travel has the longest tail: 28.2% convert after Week 6.
• Media & Entertainment and Social & Lifestyle also show 24–25% late conversion.
• Gaming shows moderate delay: 21.3% in Days 1–3 (second-highest).

How quickly do users convert from download-to-paid by geography?

Time-to-paid by geography

Time

Region

Swipe chart

• Asia-Pacific
• IN / SEA
• Latin America
• MEA
• North America
• ROW
• Western Europe

Key takeaway

MEA shows fastest conversion (63.5% on Day 0); North America has the slowest initial response.

Benchmarks to know

• MEA: 63.5% convert on Day 0 (highest).
• North America: 44.2% convert on Day 0 (lowest).

What stands out

• North America’s Day 0 rate trails MEA by nearly 20 percentage points.
• Days 4–7 account for 15.6% in North America (highest late-week share); likely tied to 7-day trial expirations.
• Western Europe shows longest conversion tail at 21.2% in Week 6+.

The measurement ceiling subscription apps don’t see

Funnel performance: key takeaways

Across subscription apps, performance is heavily front-loaded — but where and how that front-loading happens depends on geography, category, access model, pricepoint, and trial design. D0 dominates both trial starts and paid conversions. North America consistently leads on conversion-to-paid, while IN/SEA lags across most steps of the funnel. Higher pricepoints and longer trials correlate with stronger conversion, but also wider variance. Access model changes timing more than total volume, with hard paywalls concentrating conversion earlier, while freemium spreads it out.

Ultimately, if you benchmark against a single median without accounting for region, pricing tier, or trial length, you risk misdiagnosing performance. Funnel shape matters as much as top-line rate.

What stands out

North America sets the paid conversion ceiling: the median trial conversion varies over 2× by region. D35 download-to-paid median is 2.56% in North America vs. 1.37% in IN/SEA. North America’s 90th percentile reaches 11.3%. 

Trial starts are immediate — or they rarely happen: in most categories, 80–89% of trials start on D0 (Business: 89.9%; Health & Fitness: 82.1%; Education lowest at 78.5%), suggesting delayed starts are a minority behavior.

Longer trials outperform short ones: trial-to-paid median is 25.5% (≤4 days), 37.4% (5–9 days), and 42.5% (17–32 days). The 10–16 day bucket shows unusual dispersion (median 35.4%, floor near zero not fully legible). 

Hard paywalls convert ~5× higher than freemium at download-to-paid: median is 10.7% for hard paywalls converting vs. 2.1% for freemium. But the variance is wide, with the top 10% of hard paywalls reaching 38.7%.

Price scales conversion — with clean step-ups by tier: download-to-paid medians: 1.4% (low), 2.0% (mid), 2.8% (high). Trial conversion medians are 4.4%, 5.4%, 8.9% respectively. Higher tiers also show wider spreads.

Category performance spans nearly 3× at download-to-paid: Health & Fitness median: 2.9%. Gaming: 1.0%. Business leads trial conversion at 9.1% vs Gaming at 4.4%.

Access model changes timing patterns: hard paywalls spike at D4–7 (25.7%), likely driven by seven-day expirations. Freemium sees stronger late conversion (week 6: 22.9% vs. 15.3% hard paywall).

Pricing and packaging

What trial strategy do different app categories favour?

Trial strategy by category

App category

Trial strategy

Swipe chart

• Mixed trial
• No trial
• Pure trial

Key takeaway

Mixed strategies (trials + non-trial options) dominate; Health & Fitness leads at 59%, while Social relies more on no-trial.

Benchmarks to know

• Mixed strategy: 38–59% across categories (Health & Fitness highest).
• No trial strategy: 18–44% (Social & Lifestyle highest at 43.6%).
• Pure trial strategy: 14–31% (Gaming highest at 31.1%).

What stands out

• Health & Fitness has lowest no-trial share at 18.3%.
• Social & Lifestyle is the only category where no-trial exceeds mixed trial strategy.
• Gaming shows most balanced split between all three strategies.

Are trial periods getting shorter?

Trial durations year-on-year

Trial duration

Year

Swipe chart

• 4 days or less
• 5-9 days
• 10-16 days
• 17-32 days

Key takeaway

Short trials (≤4 days) gained share, rising from 42% to 46.5%; mid-length trials (5–9 days) declined.

Benchmarks to know

• Current year: 46.5% use ≤4 days, 39.9% use 5–9 days.
• Previous year: 42.1% used ≤4 days, 43.5% used 5–9 days.
• Longer trials (10+ days): relatively stable at ~14-15%.

What stands out

• ≤4 day trials gained 4.4pp year-on-year.
• 5–9 day trials lost 3.6 percentage points.
• Longest trials (17–32 days) declined slightly from 6.1% to 5.0%.
• The shift toward shorter trials continues despite data showing longer trials convert better.

The moment after the paywall is your best conversion lever

How adding friction to trial reminders boosted conversions

How does trial length differ between different app categories?

Trial durations by category

App category

Trial duration

Swipe chart

• 4 days or less
• 5-9 days
• 10-16 days
• 17-32 days

Key takeaway

Gaming apps favor ultra-short trials (73% ≤4 days); Health & Fitness prefers mid-length (54% at 5–9 days); Photo & Video heavily skews short (68% ≤4 days).

Benchmarks to know

• Short trials (≤4 days): 29–73% across categories (Gaming highest, Health & Fitness lowest).
• Mid-length (5–9 days): 24–54% (Health & Fitness highest, Gaming lowest).
• Longer trials (10+ days): 3–26% range (Shopping highest at ~26% combined).

What stands out

• Gaming’s 73.3% ≤4-day share is the highest of any category, heavily skewing toward ultra-short trials. Photo & Video follows closely, with 68.2% of trials at 4 days or less.
• Travel leads in 5–9 day trials (54.3%), narrowly ahead of Health & Fitness (54.0%).
• Shopping stands out for longer trials, with the highest share of both 10–16 day (15.5%) and 17–32 day (10.3%) periods.
• Education leans mid-length, with half of trials (50.3%) in the 5–9 day range.

How is pricing evolving across subscription lengths?

Pricepoints by plan duration year-over-year

Plan duration

Years

Pricing metric

Swipe chart

• Most common
• Bottom quartile
• Median
• Upper quartile
• P90

Key takeaway

Prices remained remarkably stable; median yearly prices rose slightly from $31.60 to $34.80 while weekly and monthly held steady.

Benchmarks to know

• Weekly: Most common at $5, median $5–$5.90, top percentile at $10 (unchanged YoY).
• Monthly: Most common at $10, median risen from $7 to $8, top performers went up from $20 to $22.70.
• Yearly: Most common at $30, median up from $31.60 to $34.80, the top dropped from $92 to $90.

What stands out

• Most common pricepoints ($5/$10/$30) are sticky psychological anchors.
• Bottom quartile prices increased across all durations — floor is rising.
• Yearly plans show widest spread (from $17–20 to $58–59).
• Monthly top percentile rose 13.5% ($20 → $22.70) — premium tier expanding.
• Weekly pricing is most commoditized with tightest distribution.

What do apps charge by category?

Median price (mid value) per plan duration by category

Plan duration

App category

Swipe chart

Key takeaway

Education commands premium pricing across yearly and monthly plans with Business having the highest weekly plans; Travel price is below market at every tier.

Benchmarks to know

• Weekly median: $4.99–$6.89 (Business highest, Travel/Health lowest).
• Monthly median: $4.99–$9.99 (Education/Health/Social highest at $9.99).
• Yearly median: $20–$44.99 (Education highest, Travel lowest).

What stands out

• Education has highest yearly median at $44.99, 2.2× Travel’s $20.
• Gaming’s $4.99 monthly is unusual and lower than its $5.81 weekly.
• Health & Fitness charges premium monthly ($9.99) but value-prices weekly ($4.99).
• Business prices highest weekly ($6.89) but not highest yearly, suggesting weekly-focused monetization.
• Travel consistently prices lowest across all three durations.

Which geographies show the biggest spread between plan lengths?

Median price per plan duration by geography

Plan duration

Region

Swipe chart

Key takeaway

Western Europe and North America command premiums; IN/SEA prices at ~50% of top markets.

Benchmarks to know

• Weekly median: $4.61–$7.03 (Western Europe highest, IN/SEA lowest).
• Monthly median: $3.75–$9.99 (North America highest, IN/SEA lowest).
• Yearly median: $18.32–$39.99 (North America highest, IN/SEA lowest).

What stands out

• North America is consistently highest for monthly/yearly pricing.
• IN/SEA prices at 46–54% of top-tier markets across all durations.
• Western Europe exceeds North America on weekly but trails on monthly and yearly.
• Latin America prices below MEA at all durations — unusual given GDP differences.
• Asia-Pacific weekly ($6.49) nearly matches North America ($6.99) butyearly and monthly lag behind.

Where do weekly vs. yearly plans dominate subscription sales?

Plan mix (subscriptions sold) by category

App category

Plan duration

Swipe chart

• Weekly
• Monthly
• Yearly
• Other

Key takeaway

Gaming leans weekly (82%); Productivity favors yearly (77%); overall market: 42% monthly, 34% yearly.

Benchmarks to know

• Weekly: 4–47% across categories (Social highest, Health & Fitness lowest).
• Monthly: 13–77% (Gaming highest at 82% combined weekly + monthly, Productivity lowest).
• Yearly: 13–77% (Productivity highest, Gaming lowest at 13%).
• Lifetime/Other: 4–18% (Gaming highest, Health & Fitness lowest).

What stands out

• Gaming’s 82% weekly dominance is extreme and matches its ultra-short
  trial strategy.
• Productivity’s 77% yearly mirrors enterprise/B2B purchasing patterns.
• Health & Fitness is monthly-heavy (68%) despite premium positioning.
• Shopping favors yearly (66%), likely bundled loyalty programs.
• Travel also leans yearly at 66% with one of the lowest weekly (18%), matching seasonal booking patterns.

How does subscription duration mix vary across geographies?

Plan mix (subscriptions sold), by geography

Region

Plan duration

Swipe chart

• Weekly
• Monthly
• Yearly
• Other

Key takeaway

MEA leads monthly (52%); North America balances monthly/yearly at 36%/40%.

Benchmarks to know

• Weekly: 16–29% across geographies (Latin America highest, Asia-Pacific lowest).
• Monthly: 36–55% (MEA highest, North America lowest).
• Yearly: 19–40% (North America highest, MEA lowest).
• Lifetime/Other: <5% universally.

What stands out

• North America is most yearly-skewed (40%), matching annual billing preferences.
• Latin America favours weekly (29%), suggesting emerging market subscription patterns.
• MEA’s 55% monthly is highest, with pay-as-you-go preference in that geography.
• Western Europe mirrors North America closely (35% yearly, 41% monthly).

Pricing and packaging: key takeaways

Subscription pricing is more templatized than it appears, but with meaningful regional and category-level variation. Across geographies, the dominant architecture remains $4.99–$6.99 weekly, $7.99–$9.99 monthly, and $29.99–$39.99 yearly. North America and Western Europe anchor the high end of that range, while IN/SEA consistently prices at ~45–50% of North America’s levels (across all durations).

Year-on-year, median pricing is largely stable. Weekly and monthly medians are flat ($5.99 and $10), while yearly medians ticked up from $31.60 to $34.80. Meanwhile, category differences are more pronounced: Education and Health & Fitness sustain $39.99–$44.99 annual pricing, while Gaming and Travel sit closer to $20–$29.99.

Trial strategy and duration further differentiate packaging: mixed trials dominate (44–59% by category), but short trials (≤4 days) now account for 46.5% of all trials — up 4.4pp YoY.

What stands out

Regional compression with clear ceilings: North America leads on monthly ($9.99) and yearly ($39.99), closely followed by Western Europe ($39.44 yearly). IN/SEA sits at $3.75 monthly and $18.32 yearly — roughly half of North American pricing across durations.

Annual pricing drifted up — weekly/monthly did not: median yearly price increased to $34.80 (from $31.60), while weekly ($5.99) and monthly ($10) remained flat. The P90 yearly range expanded (up to $90), suggesting premium tier experimentation at the top end.

Category pricing power varies materially: Education leads yearly at $44.99. Health & Fitness clusters at $39.94 yearly and $9.99 monthly. Gaming is structurally lower at $4.99 monthly and $24.99 yearly — a distinct pricing posture.

$9.99 monthly is the structural anchor: estimated prices confirm $9.99 as the dominant monthly architecture across most categories. Yearly pricing concentrates at $29.99 or $39.99 in eight of 11 categories.

Short trials are gaining share: ≤4 trials rose to 46.5% (from 42.1%), while longer trials (17–32 days) declined slightly to 5.0%. Despite evidence that longer trials convert better (see Funnel performance chapter), packaging is shifting shorter.

Paywalls and offers

How many plan durations do paywalls offer by category?

Distribution of paywalls by number of plans shown (1/2/3+) by category

App category

Plan count

Swipe chart

• 1 Plan
• 2 Plans
• 3+ Plans

Key takeaway

Two-plan paywalls dominate (41–60% across categories); Shopping is the outlier with 40% single-plan paywalls.

Benchmarks to know

• 1 Plan: 20–40% (Shopping highest, Health & Fitness lowest).
• 2 Plans: 41–60% (Health & Fitness highest at 60%, Gaming lowest).
• 3+ Plans: 6–27% (Travel highest, Shopping lowest).

What stands out

• Shopping’s 40% single-plan rate is 2× the Health & Fitness rate.
• Travel leads 3+ plans at 27%; Shopping trails at 6%.

Which plan durations appear on paywalls by category?

Distribution of plan durations offered in paywalls (weekly, monthly, annual, lifetime) by category

App category

Plan duration

Swipe chart

• Weekly
• Monthly
• Annual
• Lifetime

Key takeaway

Annual plans lead across categories (28–44%), lifetime plans are most common in Gaming (18%), and weekly plans show significant variation (10–33%).

Benchmarks to know

• Weekly shown: 10–33% (Photo & Video highest, Travel lowest).
• Monthly shown: 22–44% (Shopping highest, Photo & Video lowest).
• Annual shown: 28–44% (Health & Fitness highest, Gaming lowest).
• Lifetime shown: 5–18% (Gaming highest, Shopping lowest).

What stands out

• Gaming’s 18% lifetime is 2–3× other categories.
• Photo & Video leads weekly at 33%; Travel trails at 10.5%.

Which paywall UI elements are most widely-used?

Distribution of UI elements in paywalls by category

App category

UI elements

Swipe chart

Key takeaway

Highlighted pricing leads at a 74.5% median. Countdown timers (≤1.4%) and progress bars (≤0.2%) are virtually absent.

Benchmarks to know

• Highlighted pricing: 74.5% median, tight spread (72.6–77.0%).
• Multi-plan options: 59.2% median; below 55.0% puts you alongside Shopping and Gaming.
• Free trial messaging: 54.0% median; Travel (43.6%) is 1.4× below Business (60.0%).

What stands out

• Photo & Video cancel assurance (25.0%) is ~8pp below the next-lowest category.
• Shopping leads testimonials (16.9%), nearly 3× Photo & Video’s 5.9%.
• Countdown timers and progress bars are near-zero in every category.

Dynamic paywalls that drove millions in new revenue

How text-heavy are paywalls by category?

Distribution of paywalls by text density by category

App category

Text density

Swipe chart

• Low
• Medium
• High

Key takeaway

High text density dominates (45–63%); Gaming leads at 63%; Photo & Video uses most low-density paywalls (27%).

Benchmarks to know

• Low text density: 13–27% (Photo & Video highest, Gaming lowest).
• Medium text density: 24–36% (Shopping highest, Gaming lowest).
• High text density: 45–63% (Gaming highest, Shopping lowest).

What stands out

• Gaming’s 63% high-density rate is 18pp above Shopping’s 45%.
• Photo & Video’s 27% low-density is 2× the Gaming rate (13%).

What’s the split between static vs. scrolling paywalls by category?

Share of scrollable paywalls by category

App category

Interaction type

Swipe chart

• Scrolling
• Non-scrolling

Key takeaway

Scrolling paywalls are the majority (59–76%); Travel leads at 76%; Photo & Video is lowest at 59%.

Benchmarks to know

• Scrolling paywalls: 59–76% (Travel highest, Photo & Video lowest).
• Non-scrolling paywalls: 24–41% (Photo & Video highest, Travel lowest).

What stands out

• Travel’s 76% scrolling rate is 17pp above Photo & Video’s 59%.
• Education (72%) and Health & Fitness (70%) cluster near Travel.

What CTA button text is most common?

Distribution of paywall call-to-action language by category

Key takeaway

‘Continue’ dominates CTA buttons; ‘Subscribe’ and ‘Start Free Trial’ follow; dynamic pricing templates are common.

Benchmarks to know

• Top CTAs: Continue, Subscribe, Start Free Trial, Try Free.
• Supporting CTAs: Unlock, Get Started, Upgrade to Premium.
• Dynamic elements: price templates (product.price, product.price_per_period).

What stands out

• ‘Cancel Anytime’ appears prominently alongside primary CTAs
• Dynamic price templating is widespread across apps

More is more… and the devil is in the details

Paywall optimization masterclass by Vahe Baghdasaryan

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What you’ll learn

• How to diagnose why users convert (or don’t)
• How to choose the right monetization model
• How to define a measurable paywall objective
• Where to place paywalls for maximum impact
• How to design paywalls that reduce friction and increase trust
• How to build a sustainable experimentation process

Paywall optimization masterclass

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Course instructor:Vahe Baghdasaryan

How widely are promotional offers used across categories?

Offer usage by category

App category

Offer usage

Swipe chart

• Using Offers
• Not using Offers

Key takeaway

Under 10% of apps use offers overall (9.3%); Health & Fitness leads at 14%; Gaming trails at 3.6%.

Benchmarks to know

• Overall offer usage: 9.3% of apps.
• Range across categories: 3.6–14.0%.
• Leader: Health & Fitness (14.0%).
• Lowest: Gaming (3.6%).

What stands out

• Over 90% of apps don’t use promotional offers.
• Health & Fitness adoption is nearly 4× Gaming’s rate.

What share of new payers come through intro offers?

Share of new payers acquired via an intro offer by category and revenue tier

App category

Revenue tier

Swipe chart

• Tier 1 (Hobby)
• Tier 2 (Early Traction)
• Tier 3 (Indie Business)
• Tier 4 (Scaling)
• Tier 5 (Top-Performing)

Share of new payers acquired via an intro offer by category and revenue tier

App category

Revenue tier

Swipe chart

• Tier 1 (Hobby)
• Tier 2 (Early Traction)
• Tier 3 (Indie Business)
• Tier 4 (Scaling)
• Tier 5 (Top-Performing)

Key takeaway

Overall median is ~30%, but the gap between hobby-tier apps (65–99%) and top-performers (0–10%) is the real story — offer reliance falls sharply as apps scale.

Benchmarks to know

• If you’re at ~30%, you’re at the industry median.
• If you’re above 65%, you’re in hobby-tier territory where nearly all payers enter via offers.
• If you’re below 10%, you’re in top-performer range; offers play a minimal role.
• Gaming spans the widest range: 99% at hobby tier to near-zero at top tier.

What stands out

• The spread between tiers 1 and 5 is ~60–90pp across most categories; an unusually clean inverse pattern.
• Gaming’s hobby-to-top gap is the most extreme in the dataset (~99pp).
• Media & Entertainment and Photo & Video maintain higher offer share even in upper tiers.

Intro and promotional offers are becoming monetization infrastructure

Why a winning paywall in Japan completely failed in the US

How large are intro offer discounts?

Distribution of intro-offer discount levels by category

App category

Swipe chart

Key takeaway

The industry anchors hard at 50% off, with median discount is -50.1% with remarkably tight clustering across categories, though Utilities pulls deepest at -63%.

Benchmarks to know

• If you’re near -50%, you’re at the median across all categories.
• If you’re shallower than -33%, you’re in the top quartile (least discounting).
• If you’re deeper than -79%, you’re in the bottom quartile (heaviest discounting).
• Shallowest medians: Gaming and Health & Fitness at -47%.

What stands out

• Utilities is an outlier at -63% median, ~16pp deeper than the overall median.
• Business shows the widest IQR (~54pp spread), while Gaming’s is among the tightest.
• The gap between shallowest (-47%) and deepest (-63%) category medians is only 16pp, showing unusual uniformity.

Paywalls and offers: key takeaways

Across categories, promotional mechanics and paywall design follow a consistent pattern: most apps do not use intro offers, most paywalls default to two plans, annual pricing dominates presentation, and UI patterns are surprisingly standardized. Variation exists, especially by performance tier and category, but the center of gravity is tight. If you’re benchmarking your paywall, the median experience is simpler than you might assume.

Overall, 9.3% of apps use promotional offers (ranging 3.6–14.0% by category). When intro offers are used, lower-performing tiers rely on them far more heavily (often 65–99% of new payers), while top performers sit closer to 0–10%. Median intro discounts cluster tightly around -50.1%. Two-plan paywalls account for 41–60% across most categories, and annual plans appear on 28–44% of paywalls. Highlighted pricing (74.5% median) and free trial messaging (54% median) are common, while countdown timers (1.4%) and progress bars (0.2%) are nearly absent.

What stands out

Promo offers are the exception, not the norm: only 9.3% of apps use offers. Health & Fitness leads at 14.0% and Gaming is lowest at 3.6%. In practice, over 90% of subscription apps do not use promotional pricing at all.

Heavy intro-offer reliance signals lower-tier performance: overall median share of new payers via intro offers is ~30%. Hobby tiers often sit at 65–99%, while top performers cluster near 0–10%. As apps scale, reliance on discounts drops sharply.

The -50% discount is effectively industry standard: median intro discount is -50.1%, with remarkably tight clustering (most categories within ~3pp). Gaming is the only category where top performers offer -90%, creating wider dispersion.

Two plans is the default structure: across most categories, 41–60% of paywalls show two plans. Shopping is the clearest outlier, with 40% single-plan paywalls. Three-plan layouts range 6–27%, highest in Travel.

Annual framing dominates, but weekly can spike by category: annual plans appear on 28–44% of paywalls. Gaming shows the highest lifetime share at 18%. Weekly presentation varies widely (10–33%), with Photo & Video at 33% and Travel at 10.5%.

UI experimentation is limited: most paywalls look structurally similar. highlighted pricing appears on 74.5% of paywalls and free trial messaging on 54%. Countdown timers (1.4%) and progress bars (0.2%) are almost nonexistent. High text-density paywalls range 45–63% across categories, led by Gaming (63%), and scrolling paywalls are the majority everywhere (59–76%), highest in Travel at 76%.

Retention and billing health

How many subscribers stay for 6+ months?

Retention of weekly and monthly plans 6 months in by category

App category

Plan duration

Swipe chart

• Monthly
• Weekly

Key takeaway

Monthly plans retain 2-5x better than weekly: median 14-26% (monthly) vs. 3-6% (weekly).

Benchmarks to know

• Weekly: median 5-15%, top quartile 7-10%.
• Monthly: median 14-26%, top quartile 30-50%.
• Business category leads (26% weekly/40% monthly); Social & Lifestyle lags (11%/24%).

What stands out

• Monthly generally outperforms weekly by 15-25%.
• The spread between quartiles is significantly higher for monthly plans compared to weekly.

How many subscribers stay for 12+ months?

Retained subscribers after 1 year by plan duration

App category

Plan duration

Swipe chart

• Monthly
• Weekly
• Yearly

Key takeaway

Yearly plans achieve significantly higher Y1 retention: median 20-40% (yearly) vs. 1-2% (weekly) and 6-14% (monthly).

Benchmarks to know

• Weekly Y1: median 1-2%, essentially total churn.
• Monthly Y: median 6-14%, top quartile 11-25%.
• Yearly Y1: median 20-40%, top quartile 32-59%.
• Travel leads yearly (39%); Productivity lags (23%).

What stands out

• Weekly users hemorrhage — lifetime value (LTV) depends entirely on early monetization.
• Travel’s yearly vs. weekly (39% vs. 9%) is a 4x multiplier.

How did Y1 retention change in 2025 compared to 2024?

Year 1 retention 2023 compared to 2024 by plan duration

Period

Plan duration

Swipe chart

• Monthly
• Weekly
• Yearly

Key takeaway

Retention declined slightly across the board from the 2023 cohort to the 2024 cohort.

Benchmarks to know

• Yearly: 31% → 28% median (-3%).
• Monthly: 10% → 8% median (-2%).
• Weekly: 1.7% → 1.2% (-0.5%).

What stands out

• Narrow shrinking of retention is somewhat notable, but at such small percentages it’s likely just noise.

Do pricing tiers affect Y1 retention?

Retained subscribers after 1 year by pricepoint

Pricepoint

Plan duration

Swipe chart

• Monthly
• Weekly
• Yearly

Key takeaway

Low-priced apps retain better on yearly plans: 36% (low) vs. 26% (mid) and 23% (high). The gap narrows on shorter durations.

Benchmarks to know

• Low-priced yearly: 36% median, top quartile 53%.
• Mid-priced yearly: 26% median, top quartile 41%.
• High-priced yearly: 23% median, top quartile 34%.
• Monthly sees a similar drop as price increases.
• Weekly seems much less impacted by price changes.

What stands out

• Low-priced outperforms mid-price by 10-13% & high-price by 13-20%.
• High-priced shows tightest yearly distribution (15-49%): predictable but lower retention.
• Weekly uniformly poor regardless of price (<3% median).

Does freemium vs. hard paywall affect Y1 retention?

Retained subscribers after 1 year by access methods

Access method

Plan duration

Swipe chart

• Monthly
• Weekly
• Yearly

Key takeaway

No meaningful difference: freemium yearly at 28% vs. hard paywall at 27% median.

Benchmarks to know

• Freemium yearly: 28% median, range 17-58%.
• Hard paywall yearly: 27% median, range 17-54%.
• Monthly: 8% (freemium) vs. 9% (hard paywall).
• Weekly: ~1-2% for both.

What stands out

• Access method is not a retention differentiator, 1% gap is noise.
• Both show similar variance — product quality and category matter more.
• Hard paywalls don’t create stickier users despite filtering for higher intent.
• Implication: access method is a conversion choice, not a retention strategy.

Most retention problems aren’t where we look for them

How do weekly renewal rates evolve across billing cycles?

First 3 weekly subscription renewals by category

App category

Renewal

Swipe chart

• 1st
• 2nd
• 3rd

Key takeaway

Weekly renewals improve dramatically: 1st renewal 35-54%, jumping to 68-81% (2nd) and 74-85% (3rd).

Benchmarks to know

• 1st weekly renewal: median 35-58%.
• 2nd weekly renewal: median 67-75%.
• 3rd weekly renewal: median 77-81%.
• Social & Lifestyle lowest across all renewals (35%).

What stands out

• 1st-to-2nd jump (~25-30%) is the critical inflection; surviving week 1 changes everything.
• By 3rd renewal, all categories converge (74-91%), suggesting early selection dominates.
• Social & Lifestyle: low 1st (35%) but mostly catches up to others by 3rd renewal (78%).

How do monthly renewal rates evolve across billing cycles?

First 3 monthly subscription renewals by category

App category

Renewal

Swipe chart

• 1st
• 2nd
• 3rd

Key takeaway

Monthly follows a similar pattern to weekly: 1st renewal 53-61%, improving to 65-77% (2nd) and 73-82% (3rd).

Benchmarks to know

• 1st monthly renewal: median 53-61%.
• 2nd monthly renewal: median 65-77%.
• 3rd monthly renewal: median 73-82%.
• Social & Lifestyle lowest 1st (42%); Business leads (61%).

What stands out

• Social & Lifestyle: weakest early (42%) but strong maturation (73% by 3rd).
• Business tightest distribution with higher overall retention each month.

How do annual renewal rates evolve across billing cycles?

First 3 annual subscription renewals by category

App category

Renewal

Swipe chart

• 1st
• 2nd
• 3rd

Key takeaway

Annual plans start lower but build loyalty: 1st renewal 24-47%, climbing to 52-70% (2nd) and 60-79% (3rd).

Benchmarks to know

• 1st annual renewal: median 23-40%.
• 2nd annual renewal: median 44-64%.
• 3rd annual renewal: median 56-70%.
• Productivity lowest 1st (23%); Business leads (40%).

What stands out

• Annual 1st renewals lower than weekly/monthly — 12-month window creates more churn opportunities.
• Survivors retain a much higher rates by 3rd renewal (60-79%).

The art of driving retention through product

How do median renewal rates compare by duration between 2024 and 2025?

Median renewal rates by subscription duration, compared to the previous period

Period

Plan duration

Renewal

Swipe chart

• 1st
• 2nd
• 3rd

Median renewal rates by subscription duration, compared to the previous period

Plan duration

Renewal

Period

Swipe chart

• Previous period
• This period

Key takeaway

Renewal rates declined slightly across the board, but not much.

Benchmarks to know

• Yearly 1st renewal dropped 3.6% — largest decline; 3rd renewals barely moved (~1%).
• Weekly and monthly 3rd renewals land at 77–79%; yearly lags at 62.5%.
• The 1st-to-2nd renewal jump spans 18–27% — the critical retention inflection point.

What stands out

• Monthly 1st renewal rates with the biggest change, up to 3.6%.
• 3rd renewal rates barely changed at all.

How do renewal rates vary by geography and subscription duration?

Median subscription renewal rates by geography

Region

Plan duration

Renewal

Swipe chart

• 1st
• 2nd
• 3rd

Key takeaway

North America and Asia-Pacific lead early renewals. IN/SEA trails by 10 to 15 percent on 1st renewals but every geography generally converges by the 3rd renewal.

Benchmarks to know

• Weekly 1st renewal: North America 55%, Western Europe 42%, IN/SEA 37%, Latin America 44%.
• Monthly 1st renewal: North America 55%, Western Europe 55%, IN/SEA 46%.
• Yearly 1st renewal: North America 26%, Western Europe 28%, IN/SEA 22%.
• By the 3rd renewal, all geographies are within 5 to 10%.

What stands out

• IN/SEA 1st weekly renewal (37%) is 13% below North America.
• Convergence by 3rd renewal suggests quality users exist everywhere, just harder to find initially.
• Geographical gaps are largest on weekly, smallest on yearly — committed annual buyers behave similarly globally.

How do renewal rates vary by pricing tier and subscription duration?

Median subscription renewal rates by pricepoint

Pricepoint

Plan duration

Renewal

Swipe chart

• 1st
• 2nd
• 3rd

Key takeaway

Low-priced apps show better 1st renewals, but the gap narrows significantly by 3rd renewal. Gaps are more pronounced on yearly plans.

Benchmarks to know

• Weekly 1st: Low 51%, Mid 46%, High 45%.
• Monthly 1st: Low 60%, Mid 55%, High 51%.
• Yearly 1st: Low 37%, Mid 27%, High 24%.
• 3rd renewal converges to 68-81% across tiers.

What stands out

• Price impact largest on yearly: low-priced 37% vs. high-priced 24% at 1st renewal.
• High-priced lose more users early but retain survivors equally, showing 3rd renewal parity.
• Monthly shows smallest price sensitivity (51-60% range).

How do active renewal rates compare by category and plan duration?

Active renewal rate by category and plan duration

App category

Plan duration

Swipe chart

• Weekly
• Monthly
• Yearly

Key takeaway

Yearly plans renew at 83.4% overall — more than 4x weekly (18.7%) and roughly 2x monthly (39.2%). Across every category, yearly retention materially outperforms shorter durations.

Benchmarks to know

• Weekly: 18.7% overall; above 25% is top-tier.
• Monthly: 39.2% overall; below 35% signals weak retention.
• Yearly: 83.4% overall; above 85% is strongest territory.

What stands out

• Health & Fitness (86.4%) and Productivity (85.6%) lead yearly retention, both above 85%.
• Productivity monthly retention (28.2%) is the clear laggard — 11pp below the 39.2% benchmark.
• Every category shows yearly > monthly > weekly, reinforcing annual plans as the highest-quality billing relationship.

Segment benchmarks for retention

What are typical refund rates by category?

Refund rate by app category

App category

Swipe chart

Key takeaway

Productivity leads at 4.7% median refund rate while Travel apps see lowest refunds at 2.5%, a 2.2% spread across categories.

Benchmarks to know

• Most categories cluster between 3-4% refund rate.
• Outlier apps can reach 9–18% refund rates.

What stands out

• Productivity, Business, and Photo & Video’s higher refund rate (including higher p75 & outlier) may reflect that cohort better understands the refund procedure on the stores.
• Travel and Gaming both have lower median rates, but also a tighter spread across the quartiles.

How much variance exists in geographic refund rates?

Refund rate by geography

Region

Swipe chart

Key takeaway

IN/SEA leads with a 7.7% median refund rate; North America’s is significantly lower at 3.4%.

Benchmarks to know

• Outliers refund rates in Asia-Pacific, IN/SEA, Latin America, and Middle East-Africa are in the 30s.
• P25–P75 range: 2–8% for all geographies.

What stands out

• North America shows tightest distribution (3.4% median, 14.2% max) — most predictable market.
• Emerging markets (APAC, LATAM, IN/SEA) show widest variance — highly app-dependent outcomes.

Does pricing tier affect refund rates?

Refund rate by pricepoint

Pricepoint

Swipe chart

Key takeaway

Price increases do clearly correlate to higher refund rates (2.2% increase from low price to high price).

Benchmarks to know

• Low-priced median: 2.7%.
• Mid-priced median: 3.9%.
• High-priced median: 4.5%.
• Outlier refund rates: 11–16% across tiers.

What stands out

• Higher price = higher refund rate: each tier step adds ~1% to median.
• High-priced apps show widest distribution.
• Low-priced tier has tightest distribution.
• Premium apps reaching 16% refunds might represent overpriced subscriptions.

Does access method impact refund rates?

Refund rate by access method

Access method

Swipe chart

Key takeaway

Hard paywall apps show 2.5% median refund rate vs. freemium’s 2.9%, probably just noise.

Benchmarks to know

• P25–P75: 1.5–5.3% (freemium) vs. 1.3–5.6% (paywall).
• Max refund rates: ~9% for both models.

What stands out

• Distribution shapes nearly identical; access method isn’t a refund rate lever.

Why do subscriptions end on each platform?

Cancellation reasons by App Store

Cancellation reason

Store

Swipe chart

• App Store
• Play Store

Key takeaway

Billing errors account for 32.2% of Google Play cancellations versus 15.2% on the App Store — more than a 2x gap. 

Benchmarks to know

• App Store: 82.9% unsubscribe, 15.2% billing error.
• Google Play: 66.3% unsubscribe, 32.2% billing error.
• Developer-initiated, price increase, and pauses each represent ≤0.5% on both platforms.

What stands out

• Voluntary unsubscribes dominate on both platforms, especially on the App Store (82.9% vs. 66.3% on Play).
• Billing errors are structurally higher on Google Play — a 17pp gap versus iOS.
• Non-user-driven cancellations (developer-initiated, price changes) are statistically negligible (<1%), meaning churn is overwhelmingly user choice or payment failure.
• The primary platform difference is not unsubscribe behavior — it’s billing reliability.

Why do users cancel subscriptions?

Google Play churn survey answers by category

App category

Cancellation reason

Swipe chart

• Cost related
• Not enough usage
• Found better app
• Technical issues
• Other

Key takeaway

Price and not enough usage are dominant, but it varies by category.

Benchmarks to know

• ‘Cost Related’ churn reasons are between 25-45% for all categories.
• ‘Not Enough Usage’ churn reasons are between 26-40% for all categories.
• Technical issues are generally not the primary cause of churn, 3-7% for most categories.

What stands out

• Productivity seems most price sensitive (or apps are overpriced) with 44% ‘Cost Related’.
• Travel has highest ‘Not Enough Usage’ – perhaps reflecting the shorter term use case of Travel-related apps.

When do annual subscribers cancel during their first year?

Cancellation timeline for annual subscriptions

App category

Month

Swipe chart

• Month 1
• Month 2
• Month 3
• Month 4
• Month 5
• Month 6
• Month 7
• Month 8
• Month 9
• Month 10
• Month 11
• Month 12

Key takeaway

Month 1 accounts for 35% of all annual cancellations overall, decaying to ~5% mid-year before a Month 12 uptick (11%).

Benchmarks to know

• Month 1: 23–50% of annual cancellations (varies widely by category).
• Month 2: 8–10%; Months 3–11: 3–7% each.
• Month 12 (pre-renewal): 9–14% across categories.

What stands out

• Shopping’s Month 1 share of cancellations (~50%) is roughly 20% higher than Education (~30%).
• Month 12 uptick is universal; all categories show 9–14%.

We built an AI agent to talk to our own data

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You will be able to set up your own agent very soon. Stay tuned!

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Retention and billing health: key takeaways

Across billing intervals, early retention remains structurally strong — but year-on-year compression is visible, especially on annual plans. Weekly subscriptions still convert into high second/third-cycle renewals (median ~68–81% and 74–85%), and monthly follows a similar arc (53–75% 1st renewal to 74–86% by third). Annual plans start lower (24–47%) but climb meaningfully by renewal two and three (52–70% and 60–79%).

The bigger signal: Y1 retention has declined vs. the previous period. Annual median fell from 31% to 28% (–3pp), monthly from 10% to 8% (–2pp), while weekly remains ~1%. Annual still anchors lifetime value (LTV), but it’s also where the softening is most visible. Pricing tier and access model show far less impact on retention than duration and category.

What stands out

Annual drives LTV, but is slipping: annual Y1 median retention is 28% (down from 31%). By contrast, weekly sits near 1% and monthly at 8%. Long-duration plans still define value capture, but pressure is emerging at the top.

Renewal curves steepen after cycle one: weekly 1st renewal is ~35–54%, jumping to 68–81% on renewal two. Monthly shows the same pattern (53–75% → 72–83%). The 1st renewal remains the critical inflection point.

Duration outweighs pricing and access model: low-, mid-, and high-priced annual plans cluster at 36%, 26%, and 23% year-one median retention, respectively. Freemium (28%) and hard paywall (27%) are nearly identical — access model is not a retention lever.

Category dispersion is wide: Travel annual retention reaches ~39%, while Social & Lifestyle sits near 25%. Media & Entertainment shows the widest annual variance (~37–68%). Category dynamics materially shape renewal ceilings.

Refund and billing health vary more by platform and region than model: Google Play billing errors (32.2%) are more than 2x the App Store’s (15.2%). Refund medians cluster around 3–5% across pricing tiers and access models, with geography driving wider variance (e.g. IN/SEA higher spread, North America tighter).

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Reactivation and post-churn behavior

How often do churned subscribers reactivate?

Reactivation rate within 1 year by app category

App category

Plan duration

Swipe chart

• Weekly
• Monthly
• Yearly

Key takeaway

Monthly plan churners reactivate at 20% overall; weekly at 9%, annual at just 5% — shorter commitments enable winbacks. Productivity apps (largely AI apps) demonstrate an extreme reactivation rate.

Benchmarks to know

• Weekly reactivation: 3–16% by category.
• Monthly reactivation: 6–36% by category.
• Annual reactivation: 3–8% by category.

What stands out

• Productivity’s 36% monthly reactivation is exceptional; SaaS ‘come back when needed’ behavior.
• Shopping weekly reactivation (16%) 5x its annual rate (3%) shows transactional, seasonal usage patterns.
• Travel shows lowest weekly (3.4%) but strong annual (8%); users return for next big trip.
• Gaming churners rarely return (6–8% across durations), once lost, gone forever.
• Photo & Video monthly (20%) outperforms annual (8%) with project-based workflows vs. committed hobbyists.

Users reactivate when the problem comes back, not when your win-back email lands

Does user location influence the reactivation rate?

Reactivation rate within 1 year by geography

Region

Plan duration

Swipe chart

• Weekly
• Monthly
• Yearly

Key takeaway

Monthly plans (often led by AI apps) consistently drive the highest reactivation across every geography, with a relatively tight band (18.0% – 23.9%), while yearly plans cluster narrowly around ~5%. 

Benchmarks to know

• Weekly: 7–10% across geographies.
• Monthly: 18–24% across geographies.
• Annual: 5–6% across geographies.

What stands out

• Geographical variance is surprisingly narrow; reactivation behavior is more universal than acquisition or retention.
• Asia-Pacific’s 24% monthly + lowest yearly (5%) suggests higher churn tolerance in exchange for flexibility.
• North America’s 18% monthly is the global floor: US users are more decisive/permanent about cancellations.
• Annual reactivation converges globally (4.9–5.9%) — churned annual subscribers rarely return regardless of geography.

Does pricing tier affect the likelihood of a user reactivating?

Reactivation rate within 1 year by pricepoint

Pricepoint

Plan duration

Swipe chart

• Weekly
• Monthly
• Yearly

Key takeaway

Monthly subscribers are the most likely to come back. High-priced apps see the strongest winback on monthly plans.

Benchmarks to know

• Weekly: 8–9% across price tiers.
• Monthly: 12–29% by tier.
• Annual: 4–6% by tier.

What stands out.

• High-priced monthly (29%) vs. annual (4%) is the widest gap .
• Low-priced apps show most balanced reactivation (8/15/6%): price isn’t the friction for return.
• Mid-priced monthly (12%) underperforms both ends, likely a ‘stuck in the middle’ value perception challenge.
• Weekly rates flat across tiers (8–9%): price irrelevant for ultra-short commitment winbacks.
• High-priced annual churners (4.4%) are truly lost; they made a considered decision and won’t revisit.

Reactivation and post-churn behavior: key takeaways

Reactivation is meaningful, but highly plan-dependent. Globally, monthly plans show reactivation rates from 18–24% across regions, while weekly plans cluster around 7–10%. Annual plans sit much lower at 4–6%. Category spread is wide: monthly reactivation ranges from 6–36% depending on vertical. Geography matters just as much: Asia-Pacific leads on monthly reactivation (24%), while North America lags (18%). Pricing tier also shapes behavior: high-priced monthly subscriptions show 28.9% reactivation, vs. 15.4% for low-priced plans. Annual reactivation remains tightly constrained across regions and tiers (~4–6%), suggesting that long-term churn is structurally harder to reverse. Overall, reactivation benchmarks are drastically impacted by plan mix, region, and price band.

What stands out

Monthly plans dominate reactivation: across every geography, monthly reactivation (18–24%) materially exceeds weekly (7–10%) and annual (4–6%). Shorter commitments appear easier to restart, but not all short plans perform equally.

Category variance is extreme: monthly reactivation ranges from as low as 6% in some categories to as high as 36.1% in Productivity. Shopping weekly reactivation reaches 15.7%, well above the 7–10% regional weekly range.

Asia-Pacific leads; North America trails: Asia-Pacific has 24% monthly reactivation with 5.1% annual. North America shows 18% monthly and 5.0% annual — suggesting stronger cancellation finality in mature markets.

High-priced monthly plans win back best: high-priced monthly subscriptions reactivate at 28.9%, versus 15.4% for low-priced and 12.4% for mid-priced. By contrast, high-priced annual reactivation is just 4.4%.

Annual churn is largely permanent: whether by region (4.9–5.9%) or price tier (4.4–5.6%), annual reactivation remains consistently low. Once annual subscribers leave, very few return within a year.

Categories, segments, and regions

How does D60 RPI vary across stores and geography?

Day 60 revenue per install (RPI) by store and geography

Region

Store

Swipe chart

• App Store
• Google Play

Key takeaway

The App Store generates 2.6x higher D60 RPI globally, with a median of $0.42 compared to $0.16 on Google Play. North America leads performance on both stores, while IN/SEA trails behind on both iOS and Android.

Benchmarks to know

• Global median: App Store $0.42, Google Play $0.16.
• North America highest: iOS $0.65, Android $0.26.
• IN/SEA lowest: iOS $0.15, Android $0.04.

What stands out

• iOS premium holds across all seven geographies without exception.
• North America shows widest gap with 2.5× ratio at median.
• Top-tier iOS in North America reaches $1.47, nearly 6× its Android counterpart.

Does the App Store advantage persist in long-term payer value?

Realized lifetime value (RLTV) per payer after 1 year by store and geography

Region

Store

Swipe chart

• App Store
• Google Play

Key takeaway

Y1 RLTV largely converges across stores. Globally, the median App Store lifetime value (LTV) is $23.38 vs. $21.62 on Google Play — an ~8% difference. This is a sharp compression from the ~2.6× gap seen at D60, suggesting monetization differences narrow materially over time.

Benchmarks to know

• Global median: App Store $23.38, Google Play $21.62.
• Western Europe leads across both stores: $27.08 (Google Play) and $26.47 (iOS).
• IN/SEA has the lowest medians: $17.46 (iOS) and $11.52 (Google Play).

What stands out

• ROW shows near-parity: $19.66 vs. $19.32.
• Top-tier Android payers in North America and Asia-Pacific exceed iOS ($85.70 and $77.03 respectively).
• Western Europe’s Google Play slightly exceeds iOS at the median, reversing the early iOS advantage seen at D60.

What share of revenue comes from App Store vs. Google Play in each geography?

Platform revenue split by geography

Region

Platform revenue share

Swipe chart

• Google Play only
• Less than 50% App Store
• 50% to 70% App Store
• 70% to 80% App Store
• Over 80% App Store

Key takeaway

Across every geography, 66-75% of projects derive over 80% of their revenue from the App Store. North America is the most iOS-concentrated (75.1%), while IN/SEA and Latin America are the least concentrated — though still with ~66% of projects heavily skewed toward iOS.

Benchmarks to know

• Over 80% iOS revenue share: 66–75% of projects, depending on geography.
• Android-leaning projects (<50% iOS share): 11–17% across geographies.
• 70–80% iOS tier is thin: roughly 2–4% of projects sit in this middle band.

What stands out

• Binary distribution: apps rarely split evenly between platforms, with a majority being iOS-dependent.
• IN/SEA and Latin America have the highest Android-leaning share (~17%), though iOS still dominates overall.
• MEA mirrors North America rather than other emerging markets, with 70.3% of projects deriving >80% of revenue from iOS.

Does the store gap persist in trial-to-paid conversion?

Trial conversion-to-paid by store and category

App category

Store

Swipe chart

• App Store
• Google Play

Key takeaway:

Trial conversion is nearly identical with App Store 32.6% vs. Google Play 32.5% median. The iOS monetization premium seen earlier in the funnel disappears at the trial stage.

Benchmarks to know

• Global median (all categories): 32.0% iOS vs. 32.5% Google Play.
• Travel leads overall, with 39.7% median on iOS and 53.0% on Google Play.
• Gaming is lowest on iOS at 27.3%, while Photo & Video is lowest on Google Play at 17.1%.
• Top-tier Travel apps reach 75–76% trial conversion on both stores.

What stands out

• Parity is striking given download-to-paid’s 2.9× iOS advantage.
• Android matches or exceeds iOS at the median in Education and Travel.
• Travel shows the largest cross-store divergence, with Google Play leading iOS.
• Upper-tier performance is tightly clustered across stores, with most categories topping out in the 60–70% range.

How do D35 conversion rates compare between categories and stores?

Day 35 download-to-paid conversion by store and category

App category

Store

Swipe chart

• App Store
• Google Play

Key takeaway

The App Store converts at roughly 2.9× the rate of Google Play globally (2.6% vs. 0.9% median), and the iOS advantage holds across every category shown. While conversion gaps narrow in certain verticals, there is no category where Google Play surpasses iOS at the median.

Benchmarks to know

• Global median (all categories): 2.6% iOS vs. 0.9% Google Play.
• Health & Fitness leads on iOS at 3.5% median, followed closely by Education (3.1%) and Business (3.0%).
• Gaming has the lowest median conversion at 1.3% on iOS and 0.4% on Google Play.
• Travel upper-quartile apps reach 5.4% (iOS) vs. 3.4% (Google Play).

What stands out

• The iOS premium is universal across categories: even in lower-converting verticals like Gaming, iOS maintains a clear lead.
• Category spread is significant: median conversion ranges from 1.3% (Gaming) to 3.5% (Health & Fitness) on iOS.
• Top-tier iOS apps dramatically outperform the median: in leading categories like Education and Health & Fitness, upper-end conversion reaches 12–14%, highlighting wide performance dispersion within verticals.

Lifecycle strategy for apps by Alice Muir Kocourková

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What you’ll learn

• How to map users to lifecycle stages
• How to design onboarding that drives activation
• When to trigger upgrades
• How to reduce churn and re-engage drifting users
• How to build CRM flows that increase LTV
• How to treat lifecycle marketing as a revenue system

Lifecycle strategy for apps

StartApp School

Course instructor:Alice Muir Kocourková

How ElevenLabs turns feature launches into a growth engine

How do median subscription prices differ by store and geography?

Median price per plan duration by store and geography

Plan duration

Store

Region

Swipe chart

Key takeaway

Pricing is identical across stores in North America ($6.99 weekly, $9.99 monthly, $39.99 yearly), but diverges in emerging markets — especially on annual plans, where MEA shows a $27.22 vs. $18.85 gap and IN/SEA drops to $14.64 on Play Store.

Benchmarks to know

• North America: identical across stores — $6.99 weekly, $9.99 monthly, $39.99 yearly.
• Western Europe (App Store): highest weekly at $7.03 and highest yearly at $40.12.
• IN/SEA (Play Store): lowest monthly median at $3.12.

What stands out

• Annual plans drive the largest store gaps: MEA shows an $8.37 annual spread ($27.22 App Store vs. $18.85 Play Store).
• IN/SEA Play Store annual pricing ($14.64) is nearly one-third of Western Europe App Store ($40.12).
• Asia-Pacific is the only geography where Play Store monthly pricing ($7.48) exceeds App Store monthly ($6.69).

How does offer strategy differ between App Store and Google Play?

Offer usage by store and offer type

Store

Offer usage

Swipe chart

• Using Intro Offers
• Using Offer Codes
• Using Promotional Offers
• Using Win-Back Offers
• Not Using Offers

Key takeaway

The App Store deploys a broader monetization toolkit, while Google Play usage concentrates heavily on intro offers, with no usage observed for promo or winback offers. 

Benchmarks to know

• Intro offers: 72.9% Google Play vs. 41.2% App Store.
• Offer codes: 47.6% App Store vs. 27.1% Google Play.
• Promotional and winback offers: 8.6% and 2.5% on iOS; 0% usage observed on Google Play.
• Not using offers: 86.0% iOS, 95.0% Google Play.

What stands out

• iOS shows more diversified offer usage — adoption of offer codes exceeds intro offers (47.6% vs. 41.2%).
• Google Play usage is concentrated on intro offers, with materially lower adoption of other mechanisms.
• Offer penetration is not mutually exclusive, indicating many projects are not leveraging these tools at all.

Do renewal rates differ between the App Store and Google Play?

First 3 renewals by store and plan duration

Plan duration

Store

Renewal

Swipe chart

• 1st
• 2nd
• 3rd

Key takeaway

Store advantage flips by duration at 1st renewal, but disappears by the third: Google Play leads on 1st renewals for monthly (+3.5pp) and annual (+7.6pp); iOS leads weekly (+4.4pp), then all converge by 3rd renewal.

Benchmarks to know

• 1st renewal: weekly iOS 47.7%, Monthly Android 57.6%, Annual Android 49.0%.
• 3rd renewal: weekly/monthly converge to ~78–81% on both stores; annual to ~64%.

What stands out

• The largest early gap is annual 1st renewal, where Android leads by 7.6pp.
• Weekly is the only duration where iOS leads at 1st renewal.
• By the 3rd renewal, store differences effectively disappear, suggesting long-term retention dynamics are platform-neutral once subscribers pass the initial churn window.

Apple vs. Google: key takeaways

Across monetization, pricing, and revenue mix, the App Store maintains a measurable advantage over Google Play — but the magnitude varies by stage. Apple leads on download-to-paid conversion (2.9% vs. 2.6% median), early revenue per install (RPI) ($0.42 vs $0.23 at D60), and Y1 realized lifetime value (RLTV) per payer ($23.38 vs. $21.62).

That said, the gap narrows meaningfully deeper down the funnel. Trial-to-paid show medians are near parity (32.6% vs. 32.5%), and by 3rd renewal, store differences compress to low single digits across durations.

The takeaway is primarily structural: iOS tends to monetize earlier and at higher absolute levels, but long-term retention mechanics and subscription durability are broadly similar across stores. However, it’s worth also considering implications from other chapters, such as Retention and billing health, that shed additional light on Apple vs. Google, i.e. e.g. Google Play’s 2x billing error rate compared to App Store.

What stands out

Conversion advantage starts at the top of the funnel: median download-to-paid conversion is 2.9% on App Store vs. 2.6% on Google Play. No category shows Android outperforming iOS at the median.

Trial parity reshapes the story: trial-to-paid medians are nearly identical (32.6% iOS vs 32.5% Android). The store premium largely disappears once a user starts a trial.

Early revenue gap is material — but compresses over time: D60 RPI is $0.42 on iOS vs. $0.23 on Google Play (1.8x). By Y1 RLTV per payer, the gap narrows to ~8% ($23.38 vs. $21.62).

Retention converges by renewal three: Google Play leads slightly on 1st renewals (e.g. weekly 47.7% vs. 41.4%), but by 3rd renewal, store differences shrink to roughly 1–2pp across durations.

Revenue concentration skews heavily toward iOS: 66–75% of apps generate over 80% of revenue from the App Store, depending on region. Android-leaning revenue mixes (≤50% iOS share) are comparatively rare (5–17%).

Does development framework affect download-to-paid conversion?

Day 35 download-to-paid by framework

Framework

Swipe chart

Key takeaway

React-Native shows the highest median conversion at 2.5% — 25% above Native (2.0%) and ~39% above Flutter (1.8%). However, the absolute spread between frameworks is modest compared to within-framework variation.

Benchmarks to know

• React-Native median: 2.5% (upper quartile ~5.7%).
• Native median: 2.0% (upper quartile ~4.4%).
• Flutter median: 1.8% (upper quartile ~4.3%).
• Lower bound across frameworks: ~0.4–0.9%.

What stands out

• Variance within frameworks (10×–14× from low to high) dwarfs differences between frameworks.
• Native and Flutter medians are nearly identical, suggesting no clear cross-platform penalty at the median.
• Top-end React-Native apps pull ahead, but the dispersion suggests execution matters far more than framework choice.

The framework doesn’t matter — until it does

Does framework choice impact D14 revenue per install?

Day 14 revenue per install by framework

Framework

Swipe chart

Key takeaway

React-Native leads at $0.34 median, 55% higher than Native ($0.22) and ~79% higher than Flutter ($0.19). However, the absolute differences between frameworks are modest relative to the dispersion within each group.

Benchmarks to know

• React-Native median: $0.34; if you’re above $1.04, you’re in the top quartile.
• Native median: $0.22; Flutter median: $0.19.
• ‘Other’ frameworks track closely with Flutter at $0.19 median.

What stands out

• React-Native has the highest upper bound, reaching $2.58 vs. $1.27 for Native.
• Native and Flutter monetize very similarly at the median, suggesting limited framework penalty.
• Within-framework dispersion (roughly 18×–30× from low to high) far exceeds the gap between medians, suggesting execution matters more than stack choice.

How does D60 RPI compare by framework?

Day 60 revenue per install (RPI) by framework

Framework

Swipe chart

Key takeaway

React-Native leads at $0.51 median RPI — 65% above Native ($0.31) and 76% above Flutter ($0.29). As with earlier horizons, dispersion within each framework is far larger than the median gap between them.

Benchmarks to know

• React-Native median: $0.51; if you’re above $1.50, you’re in the top quartile.
• Native median: $0.31; Flutter median: $0.29.
• React-Native’s advantage widens from D14 to D60.

What stands out

• Native and Flutter monetize nearly identically at the median, suggesting no cross-platform revenue penalty.
• React-Native has the highest ceiling, reaching $3.60 at the upper bound vs. $1.71 for Native.
• Within-framework spread (roughly 20×–30× from low to high) materially exceeds differences between medians — stack choice matters less than execution.

React Native + Expo: Native where it matters, fast everywhere

Does framework affect subscriber retention over a year?

Year 1 retention per plan by framework

Framework

Plan duration

Swipe chart

• Weekly
• Monthly
• Annual

Key takeaway

Y1 retention is tightly clustered across frameworks. Annual medians range from 27.0% to 30.6% — a spread of just 3.6pp. Framework choice appears to have minimal impact on long-term retention.

Benchmarks to know

• Annual median: Other 30.6%, Flutter 27.8%, React-Native 27.1%, Native 27.0%.
• Monthly median: 7.4–9.2% across frameworks.
• Weekly median: 0.8–1.8% across frameworks.

What stands out

• Differences are smallest at annual durations, where medians cluster tightly around ~27–31%.
• Flutter and Native are very close at annual retention, though Native leads slightly at weekly and monthly durations.
• React-Native’s monetization lead does not translate to a retention advantage.

Does framework choice impact long-term payer value?

Year 1 realized lifetime value (RLTV) per payer by framework

Framework

Swipe chart

Key takeaway

React-Native apps generate materially higher Y1 RLTV. The median is $31.78, roughly 50%–52% above Native and Flutter, which cluster around $20–21.

Benchmarks to know

• React-Native median: $31.78; if you’re above $95, you’re in the top tier.
• Flutter median: $21.18; Native median: $20.88.
• Native, Flutter, and Others cluster tightly at $20–21.

What stands out

• Native, Flutter, and Others cluster tightly, suggesting little cross-platform penalty in payer value.
• React-Native’s ceiling is 50%+ higher than Native’s.
• Once again, within-framework dispersion exceeds median differences — but React-Native consistently leads at both the midpoint and the top end.

Native vs. cross-platform: key takeaways

Across conversion, early revenue, retention, and Y1 lifetime value (LTV), framework choice matters less than execution — with one notable exception: React Native outperforms at the median on revenue metrics.

Download-to-paid conversion at D35 is tightly clustered (1.8–2.5% medians), and annual retention ranges just 27–31% across frameworks. Native and Flutter track almost identically on most metrics. 

React Native, however, leads on early revenue per install (RPI) ($0.34 at Day 14; $0.51 at Day 60) and Y1 realized lifetime value (RLTV) per payer ($31.78 median). Within-framework variance often exceeds between-framework gaps, suggesting team-level execution and monetization strategy outweigh tooling decisions.

What stands out

Conversion parity across frameworks: median D35 download-to-paid conversion ranges from 1.8% (Flutter) to 2.5% (React Native), with Native at 2.0%. The spread is narrow relative to the roughly 10% within-framework variance shown.

React Native leads early RPI: D14 median RPI is $0.34 for React Native versus $0.22 (Native) and $0.19 (Flutter). By D60, React Native reaches $0.51, compared to $0.31 and $0.29 respectively.

Retention is effectively framework-agnostic: annual retention medians range from 27% (Native) to 30.6% (Other). Monthly retention clusters around 7–9%, and weekly around ~1–3%. No framework shows a structural loyalty advantage.

Long-term payer value diverges at the top: median Y1 RLTV per payer is $31.78 for React Native vs. ~$20–21 for Native, Flutter, and Other. React Native’s upper bound ($95.32) is materially higher than Native’s ($61.81).

Within-framework spread outweighs tooling choice: in multiple charts, the range within a single framework exceeds the gap between framework medians, suggesting performance differences are more execution-driven than stack-driven.

What category footprint do AI apps have?

Share of apps classified as AI-powered by category

App category

AI usage

Swipe chart

• AI
• Non-AI

Key takeaway

Photo & Video and Productivity sit far above every other category. Overall, 1 in 4 subscription apps is AI-powered.

Benchmarks to know

• 27.1%: the all-category average — at this rate, 1 in 4 apps in a given space are AI-powered.
• 40%+: at this level, AI apps approach majority status — only Photo & Video and Productivity reach this bar.

What stands out

• Photo & Video at 61.4% is more than 2× the all-category average — the sharpest outlier.
• Productivity at 41.1% is the only other category over the average by 10+ points.
• Gaming at 6.2% is nearly 4× below the median — a distinct low-end outlier.
• Travel (12.3%) and Business (19.1%) are the next lowest after Gaming.

Why app economy disruption won’t happen as fast as everyone thinks

Do AI apps convert trials better than traditional apps?

Trial start rate by AI vs. non-AI

AI usage

Swipe chart

Key takeaway

AI apps start trials at a higher rate at the median: 8.5% vs. 5.6% for non-AI (+52%).

Benchmarks to know

• AI median: 8.5%; if you’re above 15%, you’re in the top quartile.
• Non-AI median: 5.6% , over 12% is the upper quartile.
• Top end: AI reaches 22.9%; non-AI reaches 20.9%.

What stands out

• The AI advantage is most visible around the middle of the distribution.
• Top performers converge at similar levels — both segments reach ~21–23%, with AI slightly higher (22.9% vs. 20.9%).

Do AI apps monetize downloads more effectively?

Time to first purchase (download-to-paid) by AI vs. non-AI

AI usage

Swipe chart

Key takeaway

AI converts downloads to paid 20% better at the median (2.4% vs. 2.0%), a smaller gap than trial starts.

Benchmarks to know

• AI median: 2.4%; if you’re above 4.8%, you’re in the top quartile.
• Non-AI median: 2.0%.
• Top end: AI reaches 8.3%; non-AI reaches 9.8%.

What stands out

• Non-AI matches (and slightly exceeds) AI at the top end, despite trailing at the median.
• Lower-end performance is similar across segments (floor below ~0.5%, not shown precisely).

How do AI apps structure their subscription durations?

Plan mix (share of subscriptions sold) by AI vs. non-AI

AI usage

Plan duration

Swipe chart

• Weekly
• Monthly
• Yearly
• Other

Key takeaway

AI apps overwhelmingly concentrate on monthly plans (59.8% vs. 26.2% for non-AI). Non-AI apps distribute more toward yearly (41.8% vs. 24%) and weekly (30.3% vs. 15%) durations.

Benchmarks to know

• AI mix: 59.8% monthly, 24% yearly, 15.0% weekly.
• Non-AI mix: 41.8% yearly, 30.3% weekly, 26.2% monthly.
• Monthly skew gap: +33.6pp toward AI.

What stands out

• Monthly is the dominant plan for AI (nearly 60%), but only 26.2% for non-AI.
• Non-AI weekly adoption (30.3%) is ~2x AI (15%).
• AI yearly adoption trails non-AI by 17.8pp (24% vs. 41.8%).
• Non-AI portfolios are balanced across durations; AI portfolios are structurally monthly-first.

How does monetization mix differ between AI and non-AI apps?

Share of AI apps using hybrid monetization vs. subscriptions only

AI usage

Monetization model

Swipe chart

• Subscriptions Only
• Subscriptions + Lifetime
• Subscriptions + Consumables
• Subscriptions, Consumables, and Lifetime

Key takeaway

AI apps skew more subscription-pure (67.7% vs.61.9%). Non-AI diversifies more into lifetime (+7.4pp).

Benchmarks to know

• AI: 67.7% subs-only, 17.9% + lifetime, 12.5% + consumables.
• Non-AI: 61.9% subs-only, 25.3% + lifetime, 10.0% + consumables.

What stands out

• Non-AI lifetime combos run +7.4pp higher (25.3% vs.17.9%).
• AI leads in consumable hybrids (+2.5pp).

Do AI apps extract more value (monthly RLTV) per payer in the 1st month?

Realized lifetime value (RLTV) per payer after 30 days by AI vs. non-AI

AI usage

Swipe chart

Key takeaway

AI generates 39% higher monthly RLTV ($18.92 vs. $13.59 median).

Benchmarks to know

• AI median: $18.92; if you’re above $29.65, you’re in the top quartile.
• Non-AI median: $13.59; top performers reach $42–47 for both segments.

What stands out

• AI premium spans the entire distribution: the floor is $11 vs. $7 for non-AI apps.
• The value gap narrows at top — elite apps converge around $45 regardless of AI status.

Do AI apps maintain their revenue premium over a full year?

Realized lifetime value (RLTV) per payer after 1 year by AI vs. non-AI

AI usage

Swipe chart

Key takeaway

AI sustains a 41% Y1 RLTV premium ($30.16 vs. $21.37 median), slightly larger than the monthly gap (+39%).

Benchmarks to know

• AI median: $30.16; if you’re above $49.26, you’re in the top quartile.
• Non-AI median: $21.37; top performers reach $74–79 for both segments.

What stands out

• Both segments share a $75–80 ceiling where top performers converge.
• AI floor is $17 vs. $10 for non-AI — premium spans the entire distribution.

Do AI apps retain subscribers as well as traditional apps?

Retained subscribers after 12 months by AI vs. non-AI

AI usage

Plan duration

Swipe chart

• Weekly
• Monthly
• Annual

Key takeaway

Retention is mixed by duration. AI underperforms on monthly and annual retention, but outperforms on weekly at the median.

Benchmarks to know

• Weekly: AI 2.5% vs. non-AI 1.7%.
• Monthly: AI 6.1% vs. non-AI 9.5%.
• Annual: AI 21.1% vs. non-AI 30.7%.

What stands out

• The largest gap is monthly, where non-AI leads by 3.4pp (9.5% vs. 6.1%).
• AI’s annual retention also trails materially (21.1% vs. 30.7%).
• Weekly is the exception: AI is higher at the median (2.5% vs. 1.7%).

Do AI apps see more refund requests?

Refund rate by AI vs. non-AI

AI usage

Swipe chart

Key takeaway

AI apps show 20% higher refund rates (4.2% vs.3.5% median), with wider variance and a higher ceiling.

Benchmarks to know

• AI median: 4.2%; if you’re below ~2.2%, you’re in the bottom quartile.
• Non-AI median: 3.5%; best performers reach ~1% for both segments.

What stands out

• AI ceiling is higher: 16% vs.12.5% for non-AI.
• Both segments share a similar floor (~1%).

AI vs. non-AI: key takeaways

Across categories, AI is no longer niche: 27.1% of apps are AI-powered. The largest category concentration of AI apps is in Photo & Video, where AI apps rise to 61.4%. 

But the real question isn’t adoption, it’s performance: AI apps convert trial-to-paid 52% better at the median (8.5% vs. 5.6%) and monetize downloads 20% better (2.4% vs. 2%). They also generate meaningfully higher revenue per payer: +39% in month one ($18.92 vs. $13.59) and +41% over Y1 ($30.16 vs. $21.37).

However, retention is structurally weaker — AI underperforms on 12-month retention across weekly (2.5% vs. 3.4%), monthly (6.1% vs. 9.5%), and annual (21.1% vs. 30.7%) plans, and shows higher refund rates (4.2% vs. 3.5%).

The overarching takeaway is that while AI drives stronger early monetization, sustaining value remains the challenge.

What stands out

Adoption is concentrated — not universal: Photo & Video leads at 61.4% AI penetration. Productivity (41.1%) is the only other category above 40%. Gaming (6.2%), Travel (12.3%), and Business (19.1%) remain low-AI segments.

Conversion advantage is median-driven: median trial-to-paid is 8.5% for AI vs. 5.6% for non-AI apps, but top performers converge (21–23% range shown). AI’s edge is strongest around the middle, not the ceiling.

Revenue premium persists beyond month one: AI’s median first month lifetime value (LTV) is $18.92 vs. $13.59. At Y1, it grows to $30.16 vs. $21.37. The premium spans the distribution (floors and medians are higher) while top-end ceilings are similar.

Retention is consistently lower across durations: AI retains 2.5% weekly, 6.1% monthly, and 21.1% annually at 12 months, compared to 3.4%, 9.5%, and 30.7% for non-AI. The largest gap appears in annual plans.

Refunds are higher and more variable: AI apps’ median refund rate is 4.2% vs. 3.5% for non-AI apps. The upper bound is higher as well (15.6% vs. 12.5%), suggesting greater volatility in realized revenue and deeper issues in user value, experience, and long-term quality.