Sub Club by RevenueCat · 2026-03-06

The 2026 State of Subscription Apps Report

David Barnard and Jacob Eiting (RevenueCat) walk through RevenueCat's 2026 State of Subscription Apps report: new subscription app launches up 7X since 2022 (Appfigures), iOS 77% of launches, 69% of revenue from pre-2020 apps, power-law MRR growth (top 10% +306%, median +5.3%), hard paywalls converting ~5X freemium with similar retention, 55% of 3-day trial cancellations on day zero, Google Play involuntary churn, AI apps earning 41% more per payer but churning faster, longer trials converting better (likely selection bias), and the annual-plan cancellation timeline.

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4 tactics

Duolingo · B2C · language learning app

Let people pick which day you remind them before their free trial ends

Lifted conversion; no numbers given

“now Duolingo experimented with letting people choose what day they want to get the reminder on, which draws attention to, "Hey, we're going to remind you about this free trial." And so they saw a conversion uplift from that.”

Workedpaywallnotifications

Sub Club by RevenueCat · 2026-03-06

Duolingo · B2C · language learning app

Change the paywall button from 'Try for free' to 'Try for $0.00'

Meaningful conversion lift over 'Try for free'; no numbers given

“try for zero dollars and zero cents.”

Workedpaywall

Sub Club by RevenueCat · 2026-03-06

Mojo · B2C · video and story editing app

Offer a generous free tier and show free users a paywall once a week

Over 50% of revenue comes after day one, vs ~80% on day zero for most apps

“they're doing a paywall on launch for freemium users and they're tasteful about it. They only do it once a week and stuff.”

Workedpaywallpricing

Sub Club by RevenueCat · 2026-03-06

Claude · AI chat assistant app

Run a Super Bowl ad for a consumer AI app

App revenue jumped from hundreds of thousands to almost $1M a day

“Claude's on a run. Their Super Bowl ad paid off.”

Workedoffline-ads

Sub Club by RevenueCat · 2026-03-06

Numbers mentioned

Subject	Metric	Value	Quote
marketNew subscription apps launched per month, whole app market (Appfigures data)	count New subscription apps launched in January 2022	2,000 apps/month approximate	“In 2022, in January of 2022, 2,000 new subscription apps were launched per month.”
marketNew subscription apps launched per month, whole app market (Appfigures data)	count New subscription apps launched in January 2026 (7X vs Jan 2022; most growth in the last six months)	14.7K apps/month approximate	“In January 2026, 14,700, over 14,700-”
marketGrowth in monthly new subscription app launches, Jan 2022 to Jan 2026 (Appfigures)	growth rate Multiple of new subscription apps per month vs January 2022	+7 x approximate	“7X increase in the number of”
RevenueCat	new customers RevenueCat new users per month grew ~7X with no increase in support tickets (new devs set up via AI agents)	+7 x/month approximate	“we've got seven times more users per month and same number of tickets”
marketShare of new subscription app launches that are iOS (Appfigures)	share iOS share of all new subscription app launches, up from 67% in 2023	77%	“iOS now accounts for 77% of an all new subscription app launches, and that's up from 67% in 2023”
marketShare of 2025 app store revenue by app release cohort (Appfigures)	share Share of 2025 app store revenue from apps released before 2020	69%/year	“69% of revenue in the app stores is coming from apps that were released before 2020”
marketShare of 2025 app store revenue by app release cohort (Appfigures)	share Share of 2025 revenue from apps released 2020-2021	9%/year	“2020 to 2021 is 9% of the revenue, 2022 to 2023 is 14% of the revenue”
marketShare of 2025 app store revenue by app release cohort (Appfigures)	share Share of 2025 revenue from apps released 2022-2023 (hosts attribute the bump to ChatGPT and other foundation-model apps)	14%/year	“2020 to 2021 is 9% of the revenue, 2022 to 2023 is 14% of the revenue”
aggregateYear-over-year MRR growth, top 10% of apps in RevenueCat dataset	growth rate YoY MRR growth, top decile of apps	+306%/year	“the top 10% of apps grew 306% and the bottom actually lost money and the median app only grew 5.3%”
aggregateYear-over-year MRR growth, median app in RevenueCat dataset	growth rate YoY MRR growth, median app (roughly GDP/inflation level)	+5.3%/year	“the top 10% of apps grew 306% and the bottom actually lost money and the median app only grew 5.3%”
aggregateYear-over-year MRR growth, bottom-performing apps in RevenueCat dataset	growth rate Bottom of the distribution shrank; many are likely abandoned apps	negative (lost MRR)	“the top 10% of apps grew 306% and the bottom actually lost money”
aggregateYear-over-year MRR growth, top 25% of apps in RevenueCat dataset	growth rate YoY MRR growth, top quartile of apps	+80%/year	“the top 25% of apps grew 80% year over year”
aggregateMedian annual-plan year-one retention across subscription apps	retention Median annual retention (host: 'near 30%... I think it's 27')	27%/year approximate	“let's say you have the median retention, which is near 30%. We'll just say 30, I think it's 27.”
Cursor	revenue Cursor announced adding $1B in revenue in a month or a quarter (speaker unsure which), ~2 years after founding	+USD 1,000M approximate	“Cursor just announced yesterday that added a billion in revenue in a month or in a quarter and that company's only two years old”
Claude	revenue Claude app daily revenue before its surge (Appfigures data)	hundreds of thousands of dollars approximate	“Just shared data that the Claude app went from making like hundreds of thousands a month to-”
Claude	revenue Claude app daily revenue reached almost $1M/day (Appfigures data)	USD 1M/day approximate	“Day to over almost a million dollars a day in revenue.”
aggregateDownload-to-paid conversion by day 35, apps with hard paywalls (RevenueCat dataset)	conversion rate Download -> paid by day 35, hard paywall apps	10.7%	“They do 10.7% download to paid by day 35 versus 2.1% for freemium apps.”
aggregateDownload-to-paid conversion by day 35, freemium apps (RevenueCat dataset)	conversion rate Download -> paid by day 35, freemium apps	2.1%	“They do 10.7% download to paid by day 35 versus 2.1% for freemium apps.”
Mojo	share Share of Mojo revenue that does not come on the first day (more than 50%), due to a generous free tier	50% approximate	“their app does more than 50% of revenue not on the first day”
aggregateShare of conversions happening on day zero for most apps (RevenueCat dataset)	share Share of conversions on day zero (first open) for most apps	80% approximate	“most apps see 80% of their conversions on the first day, day zero”
benchmarkDay-one retention considered great	retention D1 retention of 50% would be great	50% illustrative	“You're going to lose half of them in a 50% day one retention would be great.”
aggregateYear-one retention, P90 freemium apps (RevenueCat dataset)	retention Year-one retention, 90th percentile, freemium	58%	“The P90 retention on freemium is 58% and for hardware paywall it's 54, but the median is 27.7 for freemium and 26.8 for yearly”
aggregateYear-one retention, P90 hard paywall apps (RevenueCat dataset)	retention Year-one retention, 90th percentile, hard paywall	54%	“The P90 retention on freemium is 58% and for hardware paywall it's 54”
aggregateYear-one retention, median freemium apps (RevenueCat dataset)	retention Year-one retention, median, freemium	27.7%	“the median is 27.7 for freemium and 26.8 for yearly, kind of a wash in the median”
aggregateYear-one retention, median hard paywall apps (RevenueCat dataset)	retention Year-one retention, median, hard paywall (host says 'yearly' but means hard paywall)	26.8%	“the median is 27.7 for freemium and 26.8 for yearly, kind of a wash in the median”
aggregateTiming of 3-day free trial cancellations (RevenueCat dataset)	share Share of all 3-day trial cancellations that happen on day zero; rising trend	55%	“55% of all three-day trial cancellations happen on day zero.”
aggregateGoogle Play subscription cancellations that are involuntary billing failures (RevenueCat dataset)	share Share of Google Play subscription cancellations caused by involuntary billing failures; more than double iOS	nearly a third approximate	“nearly a third of all subscription cancellations on Google Play are involuntary billing failures”
aggregateAndroid share of revenue across RevenueCat customers	share Android revenue share; rest is iOS and web (CEO's rough guess)	10–15% estimate	“I don't know what our blend is, but it's 10, 15% Android revenue versus the rest iOS probably in web”
aggregateGoogle Play cancellation survey reasons, cost + not enough usage combined (RevenueCat dataset)	share Share of Google Play cancellations citing cost or not enough usage (value proposition); technical issues and 'found a better app' are small	70% approximate	“If you combine the two as a value proposition, I'm not using it enough to be worth the money, that's 70% of cancellations.”
aggregateAI-powered apps vs non-AI apps, revenue per payer (RevenueCat dataset)	arpu AI apps earn 41% more revenue per payer than non-AI apps	+41%	“AI, our powered apps generate 41% more revenue per payer, but they churn 30% faster.”
aggregateAI-powered apps vs non-AI apps, churn speed (RevenueCat dataset)	churn AI apps churn 30% faster than non-AI apps	+30%	“AI, our powered apps generate 41% more revenue per payer, but they churn 30% faster.”
aggregateYear-one retention, AI-powered apps (RevenueCat dataset)	retention Year-one retention, AI apps	21%	“Year one retention is 21% versus 31%.”
aggregateYear-one retention, non-AI apps (RevenueCat dataset)	retention Year-one retention, non-AI apps	31%	“Year one retention is 21% versus 31%.”
aggregateTrial-to-paid conversion, trials of 17+ days (RevenueCat dataset)	conversion rate Trial -> paid, trials of 17 days or longer (70% better than short trials; likely selection bias)	42.5%	“trials of 17 days or longer convert 70% better than short trials, 42.5% versus 25.5%.”
aggregateTrial-to-paid conversion, short trials (RevenueCat dataset)	conversion rate Trial -> paid, short trials; more apps shifted to 3-day trials year over year	25.5%	“trials of 17 days or longer convert 70% better than short trials, 42.5% versus 25.5%.”
aggregateWhen churning annual subscribers turn off auto-renew, all categories (RevenueCat dataset)	share Share of eventual annual churners who cancel in the first month	34%	“34% cancel in that first month and only 11%. So there's a bump because month 11 is 4.7% and it bumps up to 11%.”
aggregateWhen churning annual subscribers turn off auto-renew, all categories (RevenueCat dataset)	share Share of eventual annual churners who cancel in month 11	4.7%	“month 11 is 4.7% and it bumps up to 11%”
aggregateWhen churning annual subscribers turn off auto-renew, all categories (RevenueCat dataset)	share Share of eventual annual churners who cancel in month 12, right before renewal	11%	“month 11 is 4.7% and it bumps up to 11%”