Sub Club by RevenueCat

On the podcast: the product-driven growth loop behind the #1 VPN app in the world, why they intentionally leave money on the table, and how the prettiest design often loses in their A/B tests.Top Takeaways:📐 Your top-of-funnel is a product decision, not a marketing oneThe apps that dominate app store search aren't winning because of ad spend; they're winning because frictionless, high-quality free experiences generate the ratings volume and engagement signals that compound into organic dominance.💸 A low conversion rate can be a sign of a great free productIf your free tier is genuinely excellent, your conversion rate will look bad on paper. That's not a problem to fix — it's a trade-off to own deliberately, especially if volume and LTV math still works.🛡️ Restraint in monetization is a growth strategy Aggressive paywalls, forced ads on first install, and dark patterns erode the trust that drives word-of-mouth and ratings. Leaving money on the table in the short term protects the flywheel that generates far more over time.🔧 Service quality is the moat that marketing can't replicate The first 85% of any app is a commodity. The last 15% — the edge cases, the network transitions, the offline states — is where category leaders are built and where competitors quietly give up.🗂️ Put customer support inside the product team When support reports to product rather than a separate org, the feedback loop from user pain to product fix closes in days, not months. The slower the loop, the more quality debt you accumulate.📸 Your A/B test data will humble your design instincts The prettier, more modern screenshot almost always loses. Users gravitate toward what they already recognize, and familiarity beats novelty in app store conversion tests far more often than designers expect.About Tanuj Chatterjee:🚀CEO, Super Unlimited, a global leader in building trusted VPN, eSIM, and security products that put users' privacy first.👋LinkedIn📲Super Unlimited Careers PageFollow us on X: David Barnard - @drbarnardJacob Eiting - @jeitingRevenueCat - @RevenueCatSubClub - @SubClubHQEpisode Highlights:[0:00] The Super Unlimited Journey: From product acquisition to global success.[3:15] Building a Billion-Download VPN: How Super Unlimited achieved such rapid growth.[6:50] The Freemium Philosophy: Why Super Unlimited offers a powerful free version of their app.[10:00] Monetization and User Trust: How they balance free and paid models without over-monetizing.[14:30] Service Quality Over Design Trends: The surprising reason Super Unlimited keeps it simple.[20:45] User Privacy: How Super Unlimited protects users while scaling.[25:10] The Power of Organic Growth: How word-of-mouth and product-driven growth led to massive success.[30:00] Handling Global Challenges: The complexities of serving users in different regions.[35:00] The Future of Super Unlimited: What’s next for Super Unlimited as they expand their product suite.[40:02] Lessons for Entrepreneurs: What Tanuj has learned along the way and the advice he’d give to new founders.

On the podcast: hitting $1M ARR in four months with no paid ads, why trial extensions beat discounts for saving cancellations, and why you should be hiring content creators, not influencers.Top Takeaways:📈 Momentum is oxygen — get to revenue fast Reaching your first dollars quickly, even with a minimal product, creates a flywheel of confidence and capital that compounds over time.🎯 Frame your product as a solution, not a toy Content that positions your app as the answer to a real problem converts; content that makes it look fun and novel does not.🤝 Hire content creators, not influencers Follower counts are irrelevant in the age of algorithmic distribution. Look for creators with 5K followers and a Gmail address, avoid influencers repped by an agency.⏳ Trial extensions beat discounts for saving cancellations When a user tries to cancel during a free trial, offering more time converts better than offering a lower price, and it avoids devaluing your product.🚪 Move login to after the paywall Forcing account creation before users have experienced any value is a silent conversion killer. Removing it from the front of onboarding can cut drop-off by 10% or more.About Brett Bauman & Zack Hargett:🚀Brett Bauman & Zack Hargett, Co-founders, Coconote, an AI-powered note-taking app revolutionizing how students engage with lectures.👋 Brett Bauman LinkedIn👋 Zack Hargett LinkedIn💬Brett on X - @brttbmn💬Zack on X- @zackhargett🖥️ Quizlet website 📩 Quizlet careers Follow us on X: David Barnard - @drbarnardJacob Eiting - @jeitingRevenueCat - @RevenueCatSubClub - @SubClubHQEpisode Highlights:[0:00] Introducing Coconote: The AI note-taking app that scaled to millions in ARR[2:15] The founding insight: Why students desperately needed better notes[5:05] Launch momentum: Hitting $100K ARR in the first 45 days[7:40] From idea to $1M ARR in just four months[10:12] Why most founders misunderstand marketing early on[12:31] The key distribution insight: Where your customers actually spend time online[15:22] Creator marketing vs influencer marketing: Why the difference matters[18:05] How short-form content became Coconote’s primary growth engine[21:40] Turning viral attention into real revenue with better messaging[24:25] Premium pricing for students: Why Coconote charged $99+ per year[27:11] Building trust when your product affects exams and grades[30:03] Improving conversions: The onboarding experiments that increased trial starts[33:20] Removing friction: Why login moved after the paywall[36:05] Retention lessons: Why trial extensions beat discounts[39:00] The psychology behind cancellations and keeping users subscribed[42:10] Managing explosive growth while keeping the team small[45:35] Acquisition conversations with Quizlet begin[48:10] Keeping acquisition talks confidential while running the company[51:05] The emotional moment when the acquisition finally closed[54:01] Reflecting on the journey from scrappy startup to exit[56:22] Final lessons for founders building AI products today

On the podcast: how ElevenLabs turns every new feature launch into a growth engine, how they're deploying over a hundred million dollars in paid ads, and why directing AI agents is quickly becoming a core skill for marketers and solo founders.This conversation is shorter than usual and will be featured in RevenueCat’s State of Subscription Apps report. Each episode in this series will explore one crucial topic and share actionable insights from top subscription app operators.Top Takeaways:🚀Turn every feature launch into a full-funnel growth engineDon't just ship and announce. Coordinate each release across organic posts, landing pages, and refreshed ad creative simultaneously so earned attention compounds into paid efficiency.💰 Train a custom GPT on your own winning ad copyFeed your top and bottom performing Meta and Google copy into a custom GPT, then use it to rapidly translate brand messaging into proven high-performing ad formats. It turns institutional knowledge into a scalable creative tool.🤖Directing AI agents is the new core marketing skillThe future of marketing isn't just using AI tools but directing agents to handle messaging, storyboarding, ad creation, and localization, all grounded in your creative taste and brand direction.About Luke Harries:🚀Growth / Engineering at ElevenLabs, is an AI research and product company transforming how we interact with technology. Their vision is to make communication and creation with technology seamless.👋 LinkedInFollow us on X: David Barnard - @drbarnardJacob Eiting - @jeitingRevenueCat - @RevenueCatSubClub - @SubClubHQEpisode Highlights:[0:00] Introduction to Luke Harries, Growth Lead at ElevenLabs[1:05] ElevenLabs' approach to growth through "growth engines"[2:20] The power of AI to unlock viral moments during product launches[3:34] How ElevenLabs maximizes attention through paid ads alongside earned media[4:41] The role of AI in optimizing ad copy and creative for paid campaigns[5:42] Balancing AI-generated content with UGC and in-house production[7:32] Why ElevenLabs stays away from AI influencers for product endorsements[8:51] Leveraging user-generated content (UGC) for effective campaigns[10:30] How ElevenLabs plans to spend over $100M in paid ads and approach campaign scaling[11:38] The importance of localization and segmentation in paid advertising[12:56] How ElevenLabs measures success and uses data to adjust their budget allocation[13:18] Blending brand-building with performance marketing[14:53] The future of marketing with AI-driven creative direction[16:39] How AI could enable solo founders to create billion-dollar startups[17:45] ElevenLabs' upcoming product, Flows, and recruitment efforts

On the podcast: why app economy disruption won't happen as fast as everyone seems to think, how AI is just as useful for defending against copycats as creating them, and why the real barrier to app success is still distribution, not code. This conversation is shorter than usual and will be featured in RevenueCat’s State of Subscription Apps report. Each episode in this series will explore one crucial topic and share actionable insights from top subscription app operators.Top Takeaways: 📲Distribution is the moat, not codeAs AI lowers the barrier to building apps, it raises the barrier to getting discovered. More software competing for attention means user acquisition becomes harder and more expensive, not easier.🛡️Use AI to defend against copycats, not just to build fasterUse AI to scan the app store daily for copycat apps, monitor rising competitors, and track their ads. Build automated defense processes that keep you ahead of clones.📊App economy disruption won't happen as fast as everyone thinksNo-code tools, game engines like Unity, and now vibe coding have all promised to democratize app building. None eliminated the real barriers: distribution, product intuition, and the compounding advantage of iterating on user feedback over years.About Eric Seufert:🚀 Founder of Mobile Dev Memo, a mobile advertising and freemium monetization trade blog.👋 LinkedInFollow us on X: David Barnard - @drbarnardJacob Eiting - @jeitingRevenueCat - @RevenueCatSubClub - @SubClubHQEpisode Highlights:[0:00] Introduction to Eric Seufert, Founder of Mobile Dev Memo[1:00] Why disruption in the app economy is taking longer than expected[2:00] The real barrier to app success: Distribution over code[3:15] How AI is reshaping app development and marketing[4:30] Eric’s thoughts on why AI won’t eliminate the need for great apps[5:45] Standing out in a saturated app market: How to break through[7:00] The role of customer feedback in driving growth[8:15] Why vibe coding isn’t sustainable for scalable app development[9:30] Using AI defensively against copycats in the app economy[10:45] The importance of scalable user acquisition strategies[12:00] The long-term impact of AI on app monetization[13:15] Balancing revenue and user experience in app monetization[14:30] Why building a successful app requires technical expertise and distribution[15:45] The evolving app economy and AI’s future role in scaling[17:00] Closing thoughts on staying competitive in an ever-changing market

On the podcast: product-driven retention as the foundation for lifecycle marketing, working backwards from results to nail activation, and why talking to individual users can lead you astray.This conversation is shorter than usual and will be featured in RevenueCat’s State of Subscription Apps report. Each episode in this series will explore one crucial topic and share actionable insights from top subscription app operators.Top Takeaways:🎯 Product-driven retention is the foundation for lifecycle marketingLifecycle marketing hacks and perfect push notifications won't save you if the core product doesn't deliver results. Work backwards from what users say in five-star reviews to identify the results that matter, then build the product loop around consistently delivering those results.📊 Teach features in the moment, not in onboardingUsers adopt features at far higher rates when coached during the action itself. In-context prompts while users are actively engaged are far more effective than FAQs or standalone tutorials.⚡ Surveys beat user interviews for consumer product decisionsIndividual interviews with five to ten users can lead you astray in diverse consumer markets. Large-scale recurring surveys provide stronger signal and reduce the risk of over-indexing on outlier feedback.About Ben Gammon: 🚀 VP of Product at Ladder, a fitness app dedicated to providing the world's best strength training plan from the world's best coaches, every single day.👋 LinkedInFollow us on X: David Barnard - @drbarnardJacob Eiting - @jeitingRevenueCat - @RevenueCatSubClub - @SubClubHQEpisode Highlights:[0:00] Introduction to Ben Gammon, VP of Product at Ladder[1:08] Ben explains product-driven retention at Ladder[1:55] Retention is the key metric for Ladder's success[2:50] Activation: Work backward from user results to simplify the experience[3:53] Introducing the journal feature to track progress and boost retention[6:10] The journal as a reinforcement loop for ongoing user engagement[6:37] The widget: A powerful external tool for retention and reminders[7:30] Using subconscious interactions with the widget to maintain user engagement[8:09] Balancing user feedback with business goals and company vision[9:23] Collecting feedback through chat, surveys, and AI tools[10:19] Using feedback to create a positive feedback loop for improvements[11:47] Nutrition tracking: The next major retention challenge[14:15] Hybrid users (workout + nutrition) show higher retention rates[15:03] Secondary product-market fit: How nutrition complements fitness goals[17:03] User expectations vs. behavior: Asking for features but not always using them[18:08] AI and data help guide product iteration and decision-making[19:02] Ladder's vision for product expansion and retention growth[19:33] Ben discusses building a product-first team and a strong culture[20:01] Closing thoughts on user-focused product development

On the podcast: what the explosion in new apps means for the market, how the top 10% of apps grew 306% while the median barely beat inflation, and why hard paywalls convert 5X better than freemium.This conversation is focused on RevenueCat’s State of Subscription Apps report. Head to https://www.revenuecat.com/state-of-subscription-apps to download the report.Top Takeaways:📊 The app economy is a sorting machine The top 10% of apps grew 306% while the median grew just 5.3%, and that gap is only widening as AI raises the ceiling for the best-positioned apps.💰 Hard paywalls crush freemium on conversion, but context matters Hard paywalls convert five times better than freemium (10.7% vs 2.1% download-to-paid by day 35) with nearly identical year-one retention, but freemium remains the right call when free users drive word of mouth, network effects, or long-term brand scale.⚡ Day zero is your best shot at converting a user The first session is when users decide both whether to pay and whether to stay. The majority of trial cancellations happen on day zero, meaning users who don't see value immediately rarely come back to find it.🤖 AI apps sell, but they don't stick AI-powered apps generate 41% more revenue per customer but people churn 30% faster. Apps that solve that retention problem early will own their category; those that don't are just riding a wave of consumer curiosity.📈 The App Store is experiencing a supply shock The number of new subscription apps launching each month has grown 7X since 2022, creating a hyper-competitive environment where distribution, not just features, is the primary barrier to success.About RevenueCat: 🚀Jacob Eiting, CEO at RevenueCat.👋LinkedIn🚀David Barnard, Growth Advocate at RevenueCat.👋LinkedInFollow us on X: David Barnard - @drbarnardJacob Eiting - @jeitingRevenueCat - @RevenueCatSubClub - @SubClubHQEpisode Highlights:[0:27] Unpacking the key findings from the 2026 State of Subscription Apps Report[2:52] How “vibe coding” and new AI development tools have dramatically lowered the barrier to building apps[5:42] The emerging “supply shock” in the app economy as cheaper development leads to a flood of new apps competing for the same users[20:13] Breaking down the SOSA report methodology and why low-traffic apps were excluded from the dataset[21:57] Why the report separates AI apps from non-AI apps—and how AI apps tend to generate higher revenue per paying user[23:15] The explosion of new subscription apps, with launches increasing roughly 7× since 2022[25:33] Why iOS now accounts for about 77% of new subscription app launches, and what that says about platform economics[30:19] The “power law” reality of the app economy: the top 10% of apps grew 306%, while the median app barely grew[39:20] A key finding from the report: hard paywalls convert about five times better than freemium models[45:42] Trial behavior insights: over half of free-trial cancellations happen on day zero[47:40] The “billion-dollar leak” on Google Play: a large share of cancellations come from involuntary billing failures[51:21] The AI app paradox: AI apps generate higher revenue per payer but also churn faster than traditional apps[54:51] Why longer free trials appear to convert better—and why the data may reflect correlation rather than causation[1:00:54] How AI agents could change how developers analyze subscription business data

On the podcast: breaking free from the paid acquisition treadmill, how to repurpose offline events into millions of online impressions, and why a celebrity partnership can go viral but still completely flop.This conversation is shorter than usual and will be featured in RevenueCat’s State of Subscription Apps report. Each episode in this series will explore one crucial topic and share actionable insights from top subscription app operators.Top Takeaways:🎯 Measure brand campaigns by search uplift, not cost per installComparing offline and other brand campaign CPAs to paid acquisition CPAs kills creativity before it starts. Track branded search lift and run awareness surveys instead.📹Design every offline moment for online distributionBring ad creatives to your events and plan for UGC from the start. An in-person activation that reached 15,000 people generated over 4 million impressions once repurposed across ads, social, and even LinkedIn.⚠️Celebrity reach without audience fit is wasted spendA famous partner whose audience doesn't overlap with your ICP will move zero needles. Calm's LeBron James partnership was their most expensive and worst-performing campaign because his fans care about basketball, not better sleep.About Larissa Morimoto: 🚀 Senior Growth Manager (Special Projects) at PhotoRoom, the best AI photo and design platform for e-commerce.👋 LinkedInFollow us on X: David Barnard - @drbarnardJacob Eiting - @jeitingRevenueCat - @RevenueCatSubClub - @SubClubHQEpisode Highlights:[0:00] Introduction to Larissa Morimoto, Senior Growth Manager at PhotoRoom[1:10] Why PhotoRoom is turning to offline marketing for growth[2:35] How offline experiences create real human connections with users[3:50] The importance of building brand love over chasing growth metrics[5:10] Turning offline interactions into user-generated content (UGC)[6:25] Why UGC is a key driver of PhotoRoom's digital strategy[7:40] The success of PhotoRoom’s London campaign and key learnings[9:05] How PhotoRoom uses creative campaigns to amplify brand awareness[10:20] The role of brand awareness in scaling beyond paid acquisition[12:15] Balancing offline and online efforts to maximize ROI[13:05] How PhotoRoom’s focus on emotional connections leads to long-term growth[13:45] The impact of celebrity partnerships and influencer marketing on brand perception[15:01] PhotoRoom’s strategy for turning offline events into online assets[16:20] Why PhotoRoom believes in repurposing content from offline campaigns for digital platforms[17:05] The importance of testing and experimenting with new marketing strategies[18:02] PhotoRoom’s creative offline campaigns[19:29] Larissa shares upcoming initiatives and job openings at PhotoRoom

On the podcast: why web onboarding should sell the problem instead of the solution, how discounted paid trials are beating free trials, and why creative that flopped for app ads might crush it for web funnels.This conversation is shorter than usual and will be featured in RevenueCat’s State of Subscription Apps report. Each episode in this series will explore one crucial topic and share actionable insights from top subscription app operators.Top Takeaways:🎯Web funnels should sell the problem, not the solutionApp onboarding works by rushing users to an "aha moment" because they already want a solution. Web audiences are higher in the consideration phase, so effective web funnels go deeper on helping users recognize and personalize the problem before introducing the product.💰Discounted paid trials outperform free trials on webRise found that offering a heavily discounted first month instead of a free trial improves both conversion quality and ad optimization. Free trials often attract users who cancel immediately, polluting the signal that ad platforms use to find high-value customers.🎨Creative that flops on app campaigns can crush it on web, and vice versaWeb funnels attract a different audience than app install campaigns, often older and more e-commerce minded. Rise runs creative across both channels separately and regularly finds winners on one side that failed on the other, effectively doubling the chances of finding a hit from every creative concept.About Leon Sasson: 🚀 Leon is Co-Founder and CTO at Rise Science. RISE is the first energy management app that makes it easy to improve your sleep and daily energy to reach your potential. 👋 LinkedInFollow us on X: David Barnard - @drbarnardJacob Eiting - @jeitingRevenueCat - @RevenueCatSubClub - @SubClubHQEpisode Highlights:[0:00] Introduction to Leon Sasson, Co-Founder & CTO at Rise Science[1:05] Leon discusses the evolution of web funnels and their unique challenges[2:10] The difference between app onboarding and web onboarding strategies[3:15] How Leon’s team pivoted to improve web funnels and found success[4:25] The shift in consumer behavior: Web audiences vs. app users[5:50] Insights on why discounted paid trials work better than free trials on the web[7:00] Balancing the user experience with a smooth billing process[8:20] How to test and optimize creatives for both web and app funnels[9:35] Leon’s approach to personalizing funnels based on user personas[10:40] Lessons learned from handling subscription billing outside Apple’s ecosystem [11:55] The future of hybrid monetization and web/app funnel strategies [12:30] Closing thoughts on evolving marketing and product strategies through testing and iteration

On the podcast: how Tinder's ML-powered paywalls drove millions in new revenue, the art of selling features à la carte without killing subscription revenue, and why Tinder Select flopped despite users saying they'd pay for it.This conversation is shorter than usual and will be featured in RevenueCat’s State of Subscription Apps report. Each episode in this series will explore one crucial topic and share actionable insights from top subscription app operators.Top Takeaways:🤖Users need fewer options, not moreDecision overload kills conversion. Tinder saw multimillion-dollar annual revenue gains by using ML to predict and surface the single best product for each user instead of showing every tier and plan at once.🎯Anchor a la carte prices to subscriptions to prevent cannibalizationUnbundling features can capture non-subscribers, but pricing too low steals from subscription revenue. Tinder priced its standalone Passport feature equal to the weekly equivalent of a full-featured subscription, making the subscription the obvious better deal.🧠 Design for emotional decisions, not logical onesUsers don't read every feature comparison and weigh their options rationally. They decide in seconds based on feeling. Observe how users actually behave, not how you assume they should, and build your purchase flows around that.About Shawn Gong: 🚀 Product Growth & Monetization at Tinder, the world's most popular dating app, with over 55 billion matches made across 190+ countries since launching in 2012.👋 LinkedInFollow us on X: David Barnard - @drbarnardJacob Eiting - @jeitingRevenueCat - @RevenueCatSubClub - @SubClubHQEpisode Highlights:[0:00] Introduction to Shawn Gong, Product Leader in Monetization & Growth at Tinder[1:05] The challenge of decision overload and how Tinder tackled it with dynamic pricing[2:47] How machine learning helps Tinder predict and serve the right product for each user[4:25] Simplifying user choices: Reducing overwhelming options for better conversion[5:48] Shifting from static to dynamic pricing: The role of AI in optimizing Tinder’s paywall[7:06] A/B testing the dynamic pricing model: How Tinder validated the ML model's effectiveness[8:12] Unbundling features like Passport mode: Meeting specific user needs without subscriptions[9:33] The impact of pricing changes on conversion rates and subscription cannibalization[10:57] Long-term retention metrics: Measuring the success of dynamic pricing beyond just revenue[12:00] Tinder Select: Lessons from launching a high-end tier and why it didn’t work[13:18] The importance of aligning product offerings with user emotions for better decision-making[14:25] How Tinder continues to optimize pricing strategies through iterative testing and learning[15:48] Shawn’s advice for startup founders: Focus on retention and building better product decision design

On the podcast: testing prices from $5 all the way to $120 per year, why rising CACs forced a pricing rethink, and how raising the price allows them to discount more aggressively.This conversation is shorter than usual and will be featured in RevenueCat’s State of Subscription Apps report. Each episode in this series will explore one crucial topic and share actionable insights from top subscription app operators.Top Takeaways:💰 Retest prices you've already ruled out Market conditions shift constantly. A price point that couldn't beat the control for years can suddenly break even as competitors raise prices and consumer expectations change.📈A higher base price unlocks more aggressive discounting Going from $40 to $80 creates room for steeper percentage discounts that drive higher conversion, even when the absolute dollar price is still higher.🔒Rising CACs demand pricing that funds acquisition At $40/year, paid UA math barely worked. Doubling the price gave the marketing team room to compete on acquisition channels where costs keep climbing.About Patrick Rills: 🚀 Chief Product & Technology Officer at Lose It!, the app-based weight loss program mobilizing the world to achieve a healthy weight.👋 LinkedInFollow us on X: David Barnard - @drbarnardJacob Eiting - @jeitingRevenueCat - @RevenueCatSubClub - @SubClubHQEpisode Highlights:[0:00] Introduction to Patrick Rills, Chief Product & Technology Officer at Lose It![1:05] How pricing changes unlocked new growth opportunities at Lose It![2:12] Balancing customer acquisition costs (CAC) with retention through pricing strategy[3:25] Key insights from years of price testing, ranging from $5 to $120 per year[4:42] Raising prices to enable deeper discounting and improve conversions[5:58] Aligning product value with pricing to retain loyal users[7:06] The role of the freemium model in keeping users engaged after price increases[8:02] Using smart pricing and AI to drive growth[9:14] Leveraging data to fine-tune pricing decisions[10:27] How customer feedback and product data shape pricing strategies[11:38] Challenges and benefits of raising prices for an established product[12:33] Future plans for pricing tiers and new monetization strategies[13:18] Patrick shares iOS developer hiring opportunities at Lose It![13:41] Final thoughts on driving sustainable growth and user value

On the podcast: how Duolingo prioritizes clarity over persuasion on their paywalls, why they offer users multiple free trials instead of just one, and how adding friction to their trial reminder flow actually boosted conversions.This conversation is shorter than usual and will be featured in RevenueCat’s State of Subscription Apps report. Each episode in this series will explore one crucial topic and share actionable insights from top subscription app operators.Top Takeaways: 🎯 Prioritize clarity over persuasion on your paywallsShow users a timeline of exactly what happens during their trial, when they'll be charged, and how refunds work. Duolingo found that removing uncertainty about the purchase process drives more conversions than trying to sell harder.⚡Shorter trials compound experimentation velocityCutting their free trial from 14 days to 7 doubled Duolingo's experimentation velocity. Faster feedback loops let the team kill losing tests sooner and run significantly more experiments per quarter.🔬Adding friction to trial reminders can boost conversions Duolingo tested letting users pick which day they get their expiration reminder. The extra step signaled transparency, built trust that they wouldn't be surprised by a charge, and gave them time to experience real value before deciding.About Anmol Tiwari:🚀 Director of Product Management at Duolingo, the world's most popular way to learn a language.👋 LinkedIn🖥️Carers at DuolingoFollow us on X: David Barnard - @drbarnardJacob Eiting - @jeitingRevenueCat - @RevenueCatSubClub - @SubClubHQEpisode Highlights:[0:00] Introduction to Anmol Tiwari, Director of Product at Duolingo [1:05] Anmol discusses Duolingo’s focus on clarity in free trials and product offerings [2:10] How transparency in trial terms and refunds builds confidence and boosts conversions [3:45] The benefits of shorter trials for faster experimentation and better user engagement [5:10] Why Duolingo offers multiple trials to cater to different user life stages [6:30] Using machine learning to personalize subscription offers and in-app ads [7:40] How Duolingo uses contextual paywalls to increase conversions [8:50] Regional differences in trial strategies, especially in markets like China [10:10] The impact of "free tastes" and trial-like experiences in premium tiers [11:30] Using timers and reward-based copy to clearly communicate trial benefits [13:00] How Duolingo reduces day-zero cancellations and builds trust with users [14:15] Personalizing paywalls based on individual user behavior [15:30] Experimenting with new creative strategies to promote subscriptions [16:40] The role of AI in optimizing engagement and conversions [17:50] Understanding global trial preferences, particularly in China [19:10] How trust drives conversions and prevents cancellations [19:55] Closing thoughts on how transparency, experimentation, and personalization fuel growth

On the podcast: the experiments behind Mojo's 60% lift in ARPU, why a winning paywall in Japan completely failed in the US, and why not relying on day one for most of your revenue is actually a strength.This conversation is shorter than usual and will be featured in RevenueCat’s State of Subscription Apps report. Each episode in this series will explore one crucial topic and share actionable insights from top subscription app operators.Top Takeaways:🌍Show free users a paywall every week after onboardingTriggering a paywall on app open once per week for free users drove 15% of new revenue with no backlash. The more generous your free tier, the more users tolerate the ask.💪A winning paywall in one region can completely fail in anotherA long, detail-rich paywall lifted revenue 20% in Japan but flopped in the US, where cleaner designs with punchy copy outperformed. Always retest winners in each market before rolling out globally.⚡Experiment velocity is a huge unlock for revenue optimizationRunning parallel paywall tests across geo segments on a weekly cadence compounds gains fast. More iterations mean shorter feedback loops, faster learning, and fewer months leaving revenue on the table.About Michal Parizek🚀 Senior Growth Product Manager at Mojo, a mobile-first content creation platform that empowers businesses and creators to produce professional, animated social media content in minutes.👋 LinkedInEpisode Highlights:[0:00] Introduction to Michal Parizek, Senior Growth Product Manager at Mojo[1:02] How Mojo achieved a 60% increase in average revenue per user[2:16] The impact of paywall design experiments on Mojo's revenue[3:31] Why the same paywall design worked in Japan but failed in the US[4:45] Mojo’s global pricing strategies and the role of regional differences[5:45] How Mojo optimized early revenue with the 7-day ARPU metric[7:02] The role of customer feedback in shaping Mojo’s growth strategies[8:15] Testing different pricing models: How Mojo decided on the $79 price point[9:30] Why focusing on new revenue, rather than renewals, was crucial for Mojo’s growth[10:45] The benefits of running paywall campaigns for existing users[12:02] How Mojo balances customer experience with aggressive monetization strategies[13:15] The importance of experiment velocity and fast iteration in scaling Mojo[14:34] Surprising results: Mojo’s success with paywall strategies for existing users[15:41] Closing thoughts on scaling an app with data-driven experimentation and customer focus

On the podcast: about the cost of not tracking your experiments and decisions, how refunds and chargebacks quietly erase your paywall wins, and why stacking A/B test wins should compound your growth, but almost never does.This conversation is shorter than usual and will be featured in RevenueCat’s State of Subscription Apps report. Each episode in this series will explore one crucial topic and share actionable insights from top subscription app operators.Top Takeaways:💸 Map your revenue history before running new experimentsChart revenue across new subscribers, upgrades, renewals, and win-backs over time. Matching spikes and dips to past decisions reveals what actually moved the business and prevents you from re-learning expensive lessons.🤫 Refunds and chargebacks are silent killersA paywall “win” can quickly become a net negative if you aren’t tracking the downstream effects of cancellations, refunds, and chargebacks, which often hide the true cost of a seemingly successful experiment.📈If your A/B test wins aren't showing up in top-line growth, something is wrongStacking 5% and 10% experiment wins should compound, but many teams see modest growth despite a long list of "winners". Set calendar reminders to recheck winning cohorts at 3 and 6 months, especially for price changes, to catch lifts that don't hold.About Sara Grana: 🚀 Revenue Strategy Lead at Yousician, a revolutionary music platform for anyone to learn, play, create, and teach music. 👋 LinkedInFollow us on X: David Barnard - @drbarnardJacob Eiting - @jeitingRevenueCat - @RevenueCatSubClub - @SubClubHQEpisode Highlights:[0:00] Introduction to Sara Grana, Revenue Strategy Lead at Yousician[1:05] The importance of tracking experiments and business decisions in subscription apps[2:19] Mapping revenue and understanding its evolution across different user segments[3:06] Tracking revenue changes and connecting them to business decisions[4:34] The pitfalls of focusing too much on early funnel metrics and ignoring long-term impacts[5:26] The impact of chargebacks and refunds on paywall performance and customer retention[7:20] Why understanding downstream effects is crucial for making smart pricing decisions[8:44] The challenges and opportunities of introducing new subscription plans (e.g., lifetime subscriptions)[9:43] How commercial strategy influences churn rates and renewals[13:13] The importance of rechecking experiments after months to measure long-term impact[14:52] Sara's advice on when to revisit experiments based on their impact on pricing and user behavior[15:49] Tracking cohort data for subscription retention and understanding renewal trends[16:21] Why surprising lifts in experiments may require deeper investigation[17:13] The mismatch between short-term experiment results and long-term growth expectations[18:02] Final thoughts on driving sustainable growth, tracking, and adapting strategies over time

On the podcast: the tailwinds driving a boom in non-game app revenue, how vibe coding and AI workflows are fueling growth in categories that have nothing to do with AI, and why people predicting the "death of apps" have never been more wrong.This conversation is shorter than usual and will be featured in RevenueCat’s State of Subscription Apps report. Each episode in this series will explore one crucial topic and share actionable insights from top subscription app operators.Top Takeaways: 🚀 The app revenue boom isn't just about AI appsNon-game in-app purchases grew 21% year over year, but only $3.5 billion came from generative AI. Billions more flowed into short dramas, social media, utilities, entertainment, and other categories.💰 ChatGPT helped reset what consumers will pay Pre-AI, most consumer subscriptions topped out around $60 a year. ChatGPT normalized $20 a month, and usage-based pricing is pushing some users into hundreds monthly. AI apps monetize at 2x pre-AI ARPU.🎯 Vertical, opinionated products beat thin AI wrappers Build deep products around a specific use case bigger platforms won't prioritize. The litmus test: your product should get better, not fear for its life, when the underlying models improve.About Olivia Moore:🚀 AI Partner at Andreessen Horowitz (a16z), a venture capital firm that backs bold entrepreneurs building the future through technology.👋 LinkedIn👋 @omooretweets on XFollow us on X: David Barnard - @drbarnardJacob Eiting - @jeitingRevenueCat - @RevenueCatSubClub - @SubClubHQEpisode Highlights:[0:00] Introduction to Olivia Moore, AI Partner at Andreessen Horowitz[1:05] Olivia discusses the role of AI in transforming startup growth strategies[2:10] The importance of aligning product development with user needs and market demands[3:15] How Olivia helps portfolio companies leverage AI to scale effectively[4:25] The challenge of balancing innovation with user experience and feedback[5:50] Olivia shares insights on identifying and seizing AI-driven market opportunities[7:00] Navigating the complexities of integrating AI solutions into existing business models[8:20] The importance of long-term growth strategies over quick wins[9:35] Olivia talks about the evolving role of AI in user retention and engagement[10:40] Discussing the ethical considerations of AI implementation in growth initiatives[11:55] Olivia’s thoughts on the future of AI in the startup ecosystem[12:30] Closing thoughts on driving innovation and growth through AI

On the podcast, I talk with Michael and Mark about the boom in hardware-enabled subscriptions, why nothing worked until they stopped optimizing and started building a better product, and how they doubled their price to $79 even though the data said they could charge more.Top Takeaways:📱 Hardware-enabled subscriptions need daily usage to work Devices that sit unused make subscription value harder to justify, but products that become the heartbeat of daily routines (like a family calendar) naturally create subscription demand.🎯 Stop optimizing when you should be buildingLimited resources force careful prioritization, and sometimes the biggest wins come from building genuinely valuable features rather than running endless conversion experiments.💰 Price based on customer emotion, not just dataTesting showed $99 would maximize revenue, but qualitative research revealed $79 felt fair while $99 approached "disgust territory," so they chose the lower price for long-term goodwill.🏗️ Build a great product before scaling marketingSkylight tried to scale Calendar in 2021-22 but the product wasn't ready, leading to wasted marketing spend and false negatives until they focused on getting to 40+ NPS first.🛍️ Retail partnerships are the ultimate influencerBeing in Costco and Best Buy provides a stamp of quality that can't be underestimated, and multi-channel distribution drives higher overall growth despite lower subscription attach rates in some channels.About Michael Segal & Mark Ungerer:🚀 CEO, Skylight📱 Michael Segal is the CEO of Skylight, a family tech company best known for its digital frames and calendars. Michael, a former venture capitalist, brings a unique perspective to Skylight’s growth strategy, focusing on balancing growth with profitability. He shares anecdotes about Skylight’s journey from hardware to subscription models, the importance of understanding customers' emotions about pricing, and how the team navigates the challenges of scaling both hardware and software.👋 LinkedIn🚀 CPO, Skylight📱 Mark Ungerer is the Chief Product Officer at Skylight, where he leads product strategy, development, and design. With a keen focus on creating seamless user experiences, Mark discusses Skylight’s approach to subscriptions, how they test and refine features based on user feedback, and the key role retail partnerships play in building trust and credibility. 👋 LinkedInFollow us on X: David Barnard - @drbarnardJacob Eiting - @jeitingRevenueCat - @RevenueCatSubClub - @SubClubHQEpisode Highlights:[0:00] The balance between growth and profit: Making decisions based on business goals[3:22] Timing the introduction of subscriptions: Skylight's early adoption and consumer reception[5:35] The hardware-enabled subscription boom: Market maturity and Skylight’s position[8:00] Unique challenges of marketing hardware-enabled subscriptions: Overcoming consumer skepticism[10:52] How Skylight integrates hardware with daily family life to drive subscription value[12:47] Pricing strategy: The magic behind Skylight’s price increase and minimal subscriber loss[17:43] Challenges in scaling growth: How Skylight navigates its multi-channel strategy[24:15] Shifting from free trials to subscription: The evolution of Skylight’s approach to testing[27:35] The importance of talking to customers: Using qualitative feedback to guide decisions[30:00] Retail partnerships as a growth strategy[33:45] Subscription dynamics: How pricing and subscription models shape Skylight’s business[36:25] Scaling with limited resources: Skylight’s approach to growth without a dedicated growth PM[38:40] Navigating hardware, software, and subscription moats[42:00] Biggest win: The success of the $79 subscription price increase[44:05] Biggest fail: Learning from free trial experiments and the need for more growth testing[46:01] Growth would be easier with more resources and strategic price adjustments for wider market reach[48:30] The importance of reducing friction in onboarding for increased conversions[52:30] The challenges of balancing customer acquisition with retention efforts[55:02] Skylight's vision for long-term customer value and growth[57:45] The impact of reducing friction in purchasing: How simple changes can dramatically increase conversion rates[59:10] Closing thoughts on growth strategy: Aiming for long-term success, not short-term wins

On the podcast we talk with Tanmay and Jack about how earned media can drive paid performance, building features that make for good tweets, and why stripping out your onboarding quiz might beat optimizing it.Top Takeaways:📊Pricing should match how users think — not how AI worksOne of the biggest wins came from simplifying pricing. For ElevenReader, selling listening time instead of tokens or credits dramatically improved clarity and conversion. Abstracting away AI complexity for consumers is not dumbing things down — it’s good product sense.🏎️Small, autonomous “pods” enable speed to become the moatInstead of one massive org, ElevenLabs operates like 10–12 startups inside the company. Small teams with full ownership can ship fast, iterate relentlessly, and make real product decisions without waiting on heavy processes — a critical edge in fast-moving AI markets.💸Earned media compounds — and fuels paid performanceElevenLabs treats launches as compounding assets. Each launch earns attention, which boosts branded search, improves paid efficiency, and makes future launches stronger. Growth isn’t just ads vs. organic — it’s a flywheel where story, brand, and performance reinforce each other.🕊️Start launches with the “tweet thread,” not the featureBefore building launch assets, teams write the Twitter/X thread first. If a feature can’t be explained clearly and compellingly in a short narrative, it’s a red flag. This keeps teams focused on real user value instead of shipping “flashy but hollow” features.🌐 Consumer apps are a strategic advantage for platform companiesElevenLabs doesn’t see consumer apps as competing with its API customers — they’re a force multiplier. Being their own best customer helps them build better APIs, understand real user needs, and strengthen brand affinity across creators, consumers, and developers.About Tanmay Jain & Jack McDermott🚀 Mobile Growth Lead, ElevenLabs 📱 Tanmay Jain leads mobile growth for the core ElevenLabs app, focused on translating ElevenLabs’ powerful web + API capabilities into a mobile-native experience that’s simple, fast, and creative-first. He brings a founder mindset from previous roles (including Canva), and shares how ElevenLabs ships through small, autonomous pods — moving quickly, running experiments (like pricing + paywalls), and holding teams accountable to what actually improves the user experience.👋 LinkedIn🚀 Mobile Growth Lead, ElevenReader 📱 Jack McDermott leads mobile growth for ElevenReader, ElevenLabs’ consumer app that turns PDFs, articles, and books into lifelike audio — powered by a massive catalog of high-quality voices. He breaks down how ElevenLabs uses earned media to amplify paid performance, why launches start with the “tweet thread” narrative, and how simplifying pricing (selling listening time instead of tokens) can dramatically improve consumer conversion.👋 LinkedInFollow us on X: David Barnard - @drbarnardJacob Eiting - @jeitingRevenueCat - @RevenueCatSubClub - @SubClubHQEpisode Highlights:[0:00] Why consumers won’t pay in “tokens” — they pay in outcomes[2:13] The case for building consumer apps and an API (without competing with customers)[4:10] ElevenLabs’ operating system: 10–12 “speedboat” pods shipping in parallel[7:20] The Canva spin-out lesson: award-winning product ≠ distribution or retention[12:07] Monetization that matches intent: “hours of listening” vs creator credits[13:30] Two growth modes at once: compounding earned-media launches + steady paid UA[16:27] Why earned media makes paid cheaper (branded search + trust lift)[19:30] The launch playbook: write the Twitter thread first → turn it into a video[32:20] “Speed is the moat” — and how they avoid shipping gimmicks[36:57] Don’t copy Spotify Wrapped — find your product’s natural shareable moment[43:31] ElevenReader’s “aha”: bring your own PDF/ebook + pick a voice worth sharing[56:58] Biggest fail: over-optimizing onboarding instead of testing the “strip it back” base case

On the podcast, I talk with Cem about the premium trap many apps fall into, why free trials work even for freemium products, and how ‘try for $0.00’ actually outperforms ‘try for free’.Top Takeaways:💡 Protect the free moat — always Short-term revenue tricks like paywalling free features make metrics spike — then stall. Sustainable freemium growth depends on preserving free value. It’s not just ethical; it’s strategic. Pulling back too much invites competitors to offer what you took away, weakening both your brand and your growth loop.🧪 A/B test relentlessly — but know when to lead with intuition Testing is essential, but not infallible. With 400+ experiments running at once, you’ll often see trade-offs between revenue and user experience. The art of product management is knowing when to ignore short-term data and make the long-term call that preserves user trust and helps achieve strategic goals.🔁 Freemium is a growth engine, not a trade-off Your free users aren’t freeloaders — they’re your marketing engine. When you improve the free experience, you strengthen organic growth through word of mouth. Growth slows when you nickel-and-dime; it compounds when you delight.💰 Monetize with empathy, not extraction Introducing monetization requires a cultural shift. The key is measuring everything — retention, reviews, complaints per DAU — and optimizing for user experience, not just ARPU. Test cautiously, communicate transparently, and say no to anything that erodes trust.🧠 Build for everyone, not a persona In large-scale apps, personas can be counterproductive. People learn, play, and engage for wildly different reasons. Designing for inclusivity and broad appeal helps scale from millions to billions of users without alienating key segments.💡 Strategic and Creative Use of Ads Ads at Duolingo were introduced carefully with the goal of balancing monetization with a positive user experience. The focus is on surfacing ads at non-intrusive moments, such as after completing a lesson, and on carefully controlling ad content. Duolingo even partners with advertisers to integrate elements of Duolingo branding into third-party ads. About Cem Kansu:🚀Chief Product Officer at Duolingo📱 Cem Kansu is the former VP of Product at Duolingo, where he led the company’s monetization strategy, introducing ads and subscriptions that turned Duolingo into a sustainable business. With deep expertise in product development and user experience, he helped grow subscriptions to over 80% of revenue, while keeping the core product free and mission-driven.👋 LinkedInFollow us on X: David Barnard - @drbarnardJacob Eiting - @jeitingRevenueCat - @RevenueCatSubClub - @SubClubHQEpisode Highlights:[0:00] Cem discusses balancing profitability with long-term goals[0:36] Duolingo’s first monetization strategy: ads[2:02] The pivot from crowdsourcing translations to new monetization models[3:49] Streak repair as Duolingo’s first in-app purchase experiment[5:43] Shifting company culture to embrace monetization[7:20] The influence of investors on Duolingo’s monetization[8:00] Introducing ads without harming user experience[10:31] Handling user complaints and data-driven adjustments[12:07] Ensuring ad quality through strict control[13:53] Direct ad partnerships to improve user experience[16:30] Ads vs subscription: monetization strategy decision[18:43] The impact of free trials on subscription growth[20:22] Evolution of Duolingo’s subscription offerings[22:39] Adding features like offline learning and ad-free experiences[24:22] Pivoting from separate apps to integrating topics in one[26:43] Overcoming design challenges to fit new topics[28:55] Duolingo’s competition with other screen time apps[32:00] Leveraging AI to enhance the language learning experience[35:18] The role of AI in Duolingo’s growth[37:32] Balancing free vs paid features for growth[40:24] Decisions on adding/removing premium features[43:35] Lessons from the failed human tutor feature[45:10] Challenges in scaling a large product like Duolingo[47:12] Long-term growth focus and user base expansion[49:30] Design, testing, and iteration at Duolingo[54:10] Ongoing improvements in learning efficacy and retention[57:15] Duolingo’s future plans and expansion goals