How Mojo Increased ARPU 60% In Just Five Months – Michal Parizek, Mojo

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