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• Value-Driven Growth: LinkedIn's Billion-Dollar Subscription Strategy — Ora Levit, LinkedIn

  On the podcast we talk with Ora about LinkedIn’s value-driven growth philosophy, how they personalize experiences and plan offerings based on user intent, and the complexity of running over a thousand experiments a year.Top Takeaways:🌱 Growth follows valueThe surest path to long-term growth is adding features and benefits that genuinely help people achieve their goals. Growth tactics may bring a spike, but sustainable revenue comes from a product that keeps evolving so members find new reasons to return. When value creation is continuous, acquisition and retention become self-reinforcing.🎯 Personalize by intentNot all users are looking for the same outcome. Job seekers, small business owners, and learners need different experiences. Matching plans, features, and paywalls to their specific intent—whether expressed directly or inferred from behavior—makes the product feel relevant and worth paying for. The alternative is irrelevance, which guarantees churn.📊 Test like a scientistScaling experimentation changes the culture: debates give way to data. By running over a thousand tests a year, teams learn faster, spot what actually resonates, and avoid relying on intuition alone. The goal isn’t just to optimize pricing or layouts—it’s to build a habit of constant learning that compounds into growth.🔄 Retention isn’t linearChurn doesn’t always mean goodbye. Many users return months or years later when their needs change—“boomerang” behavior that can become a meaningful revenue stream. Win-back offers, refreshed trials, and simply continuing to add new value all help capture these returning customers and turn them into long-term loyalists.🤖 AI is a tool, not the storyArtificial intelligence should quietly power better outcomes, not become the headline. Helping users write a stronger profile, find the right lead, or save time drafting a job description creates tangible value. Positioning AI as a behind-the-scenes helper keeps the focus where it belongs: solving the user’s problem.About Ora Levit: 👨‍💻 Vice President of Product Management at LinkedIn.📈 Ora manages LinkedIn’s billion-dollar online subscription businesses, growing both the free weekly active user base and adding value for LinkedIn Premium subscribers.💡“Our offering changes over time, and as I mentioned, we believe in value-driven growth. We add a lot of value. And so the Premium that you've seen if you subscribed two years ago is not the Premium of today. It's a very different product, and I want you to try it out.”👋 LinkedInFollow us on X: David Barnard - @drbarnardJacob Eiting - @jeitingRevenueCat - @RevenueCatSubClub - @SubClubHQEpisode Highlights:[0:51] Value add: How LinkedIn centers value-driven growth in their product development.[8:40] The long game: The importance of optimizing for and measuring long-term revenue.[9:57] Pay to play: Where to draw the line between free and paid features.[17:59] Put it to the test: Ora and her team prioritize A/B testing and user feedback over internal debates about feature ideas.[23:32] Take it personally: The role of AI and LLMs in personalizing in-app experiences.[27:47] Here today (and tomorrow): Strategies for retaining users in the long term and winning back churned users.[34:52] The AI touch: LinkedIn’s philosophy on incorporating AI features to add value to their product.[39:44] Two (or three) for one: Leveraging strategic partnerships to add bundled perks to a premium subscription offering.[41:43] Pulse check: Monitoring earnings calls, reports, books, and podcasts to stay in step with the current state of the subscription app industry.

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• The Post-Attribution Playbook for Growth — Eric Seufert, Mobile Dev Memo

  On the podcast I talk with Eric about how measurement dysfunction paralyzes growth, why diversifying channels for the sake of diversification actually hurts performance, and the futility of trying to interpret why ads win.Top Takeaways: 📊 Broken measurement kills growthThe biggest pitfall isn’t creative or channel choice—it’s disorganized measurement. When finance, product, and UA each use different models, growth stalls. The fix isn’t another dashboard; it’s alignment. Build one coherent, incrementality-aware framework everyone trusts, with clear definitions of success and outputs that meet each team’s needs.🌊 Don’t diversify just to diversifySpreading budget across more channels feels safer but often reduces performance after integration, creative, and reporting overhead. Start with a waterfall method: max out your primary channel until ROAS hits your threshold, then move to the next. Diversify for scale or cross-channel effects—not optics.🎲 Stop asking why an ad workedWinners often defy tidy explanations. Treat individual ad outcomes as stochastic and largely uninterpretable. Put your energy into the system: feed diverse concepts, automate prospecting/synthesis, and measure whether your process is increasing the rate of wins over time. Learn from inputs and process—not post-hoc stories about outputs.⚡ Ship speed over certainty earlyYou won’t have fully baked LTV or incrementality in week one. Push spend methodically: kill obvious losers immediately, let plausible winners age, track cohort ROAS at day-7/30/60, and widen budgets as curves support it. Iterative frontier-pushing beats premature “terminal LTV” guesswork.🧩 Engineer better signalsAlgorithms optimize to the signals you send. Create intentional, high-intent events (light “hurdles” that correlate with LTV) and send those back to platforms. Better signals shift spend toward durable users and compound efficiency, especially as automation on major platforms accelerates.About Eric Seufert: 👨‍💻 Quantitative marketer, media strategist, investor, and author.📈 Eric shares expert advice on the Mobile Dev Memo blog and is an investor at Heracles Capital.💡 “The way I approach creative testing is trying to identify losers as quickly as possible. The winners take time to prove out, but the losers are pretty quick to prove out.”👋 LinkedInFollow us on X: David Barnard - @drbarnardJacob Eiting - @jeitingRevenueCat - @RevenueCatSubClub - @SubClubHQEpisode Highlights: [1:00] Intelligent design: How to effectively incorporate AI into your business strategy.[4:52] I, Robot: Machine learning =/= generative AI.[8:36] AI Pitfalls: AI works best for automating tasks and coming up with ideas — not generating brilliant creative assets.[17:29] Predictive AI: Brand-specific, full-fidelity video ads generated by AI could be a reality within 18 months.[33:25] Risky business: How to effectively diversify across advertising channels to optimize ROAS-adjusted spend.[37:43] Measure of success: Above all, make sure your measurement system is coherent and has cross-team alignment.[42:04] Tortoise vs. hare: To balance speed and efficiency, identify your ad “losers” as quickly as possible.[44:43] Missed opportunity: Good marketing comes down to embracing some uncertainty and minimizing the rest.[49:23] Human touch: Why generative AI creative tools probably aren’t a worthwhile investment right now.

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• Signal Engineering: Strategic Data Filtering for Better Ad Performance — Thomas Petit, Independent Consultant

  On the podcast I talk with Thomas about using signal engineering to optimize ad spend, how AI is changing creative testing, and why most people should avoid app2web… for now.Top Takeaways:🧠 The biggest AI opportunity in ads is smarter analysis, not faster productionAI is now good enough to produce ad-quality video and variants at scale — but that’s where 95% of the industry focus stops. The underused frontier is AI for analysis: spotting winning hooks, predicting performance, and even pre-testing creatives with “AI humans” before spend. The teams that combine rapid AI production with AI-driven analysis can iterate faster and scale what works more reliably.🔍 Signal engineering starts with fixing broken dataIf the events you send to ad networks are inaccurate or poorly mapped, you’re sabotaging the algorithms. First step: make sure event counts match internal analytics within ~5–10% (not 30–50%). Then move from “normal” to “sophisticated” by filtering for quality — for example, optimizing to high-LTV trial signups instead of all trials — and sending value-adjusted revenue that reflects predicted LTV, not just day-one spend.⚖️ Balance exploitation of winners with exploration of new conceptsWhen a creative crushes it, it’s tempting to flood your account with variations. But over-reliance on a single concept speeds fatigue and leaves you exposed when performance drops. Keep iterating on winners and testing new hooks in parallel — especially on fast-moving platforms like TikTok, where trends expire in weeks.🌐 App-to-web works best for big brands with deep resourcesMoving checkout to the web can bypass app store fees, but it’s a high-commitment experiment. Success usually requires brand trust, team bandwidth, and a well-tested flow — often with different plan structures than in-app. For most smaller teams, the opportunity cost outweighs the benefit. “Saying no to good ideas” is often the smarter prioritization.💳 Hybrid monetization is powerful, but not plug-and-playCombining subscriptions with one-time or usage-based purchases can capture more revenue from different segments — especially for AI-powered apps with real compute costs. But designing it to avoid cannibalizing subscriptions is complex. Treat hybrid as a later-stage lever: exhaust easier wins in pricing, packaging, and paywall optimization first, then experiment, possibly starting with Android or non-US markets. About Thomas Petit: 👨‍💻 Independent app growth consultant helping subscription apps like Lingokids, Deezer, and Mojo.📈 Thomas is passionate about helping subscription apps optimize their ad spend and increase ROI through smarter testing.💡 “The whole idea of signal engineering and optimization of the data that you're sending back is: send the network something better, and they're gonna do a better job. They are doing a better job — it's you who are not doing yours.”👋  LinkedInFollow us on X: David Barnard - @drbarnardJacob Eiting - @jeitingRevenueCat - @RevenueCatSubClub - @SubClubHQEpisode Highlights: [1:21] Testing smarter: How AI may be changing the game for testing ads.[13:09] Untangling the web: App-to-web can work for some, but it’s not a slam dunk.[21:19] Hedge your bets: The benefits of moving away from subscription-only and embracing hybrid monetization strategies.[26:50] Going global: When and why to consider experimenting with hybrid monetization outside the US.[31:15] Signal vs. noise: The signal engineering framework for sending the most valuable user interaction data to ad platforms.[44:47] Multi-platform: Optimizing your data and event mapping for multiple ad networks.[53:01] Low-hanging fruit: Scoring easy wins with signal engineering.[1:08:04] Hands-off: Why ad networks likely won’t (and maybe shouldn’t?) implement built-in signal engineering tools for app marketers.[1:14:05] Going deep: Advanced signal engineering techniques.[1:26:09] Volume vs. quality: Why sending fewer events to ad networks may actually yield better results.

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• Optimizing Funnels, Pricing, and Retention at Zumba — Nicole Page & Lucy Levy, Zumba

  On the podcast I talk with Lucy and Nicole about how customer-driven iteration led Zumba from VHS tapes in 2001 to launching an app in 2024, their app2web experiments that boosted LTV by 17%, and how they are able to charge for content when countless Zumba classes are available for free on YouTube.Top Takeaways:🗣️ Listening has driven 24 years of product evolutionEvery Zumba breakthrough — from instructor certifications born out of VHS buyer calls, to an app tailored for shy beginners — came directly from customer insights. The roadmap is data-led, not intuition-driven, ensuring they're always building what users genuinely want.🎯 Subscribers pay for structured programs, not endless contentZumba realized users were overwhelmed by free YouTube videos. By creating curated, goal-oriented programs, subscribers now watch twice as many videos and retention doubled. People will pay for guidance and curation — not just more content.🚀 Your growth ceiling depends on beginner retentionWith 70% of new users identifying as beginners, Zumba redesigned onboarding and UX to quickly move them toward completing three classes. Annual-plan signups reached 60%, and churn dropped dramatically. Early milestones for beginners unlock long-term growth.🌐 Web checkout can lower conversion yet raise revenueZumba shifted paywall taps to a simplified web checkout with Apple Pay and Google Pay. Immediate conversions dropped 25%, but higher annual plans, better retention, and no store fees drove a 17% lift in LTV. Optimize for long-term value, not just instant conversions.🔁 Speed of iteration beats legacy processes every timeZumba’s lean, agile team tests and pivots relentlessly — from paywall pricing to removing unsuccessful features. Daily checks in Mixpanel dictate what scales or what’s cut. Moving quickly and iterating beats established practices and keeps growth steady.About Nicole Page & Lucy Levy: 📱 Nicole Page is Senior Product Manager at Zumba, leading app development with a focus on user research and fast iteration. From onboarding experiments to web-first paywalls, she brings a data-driven mindset to every launch.💡 “Every launch is a hypothesis we’re testing, and we’re never afraid to pivot if the numbers tell us to.”👋 Nicole🚀 Lucy Levy is Chief Consumer Officer at Zumba, guiding the brand from VHS to app, boosting LTV 17% along the way with innovative strategies and beginner-focused design.🌍 Together, they’re modernizing Zumba’s global community.👋 LucyFollow us on X: David Barnard - @drbarnardJacob Eiting - @jeitingRevenueCat - @RevenueCatSubClub - @SubClubHQEpisode Highlights: [00:02:44] From VHS to app store: How three Albertos turned dance fitness into a global brand.[00:06:26] Community is the product: Why Zumba built its business around instructors, not just workouts.[00:11:01] Research at scale: How hundreds of interviews revealed why “The Shy Beginner” is their most important user.[00:14:30] Better churn than never: Why people leaving the app for live classes still counts as a win.[00:15:54] Can’t compete with free? Yes you can: The Zumba app’s curated programs outperform YouTube.[00:17:25] Double the value: Adding structured programs led to twice the content engagement and better retention.[00:20:04] Cracking community: Why their first chat-based social feature failed and what they’re planning next.[00:22:56] Test everything: Zumba’s app team operates with a growth mindset inside a 24-year-old company.[00:25:22] Data before breakfast: Why daily Mixpanel check-ins drive fast iteration and culture change.[00:26:09] App-to-web win: How a 25% drop in conversion still led to a 17% lift in LTV.[00:30:19] Checkout optimization: Using Stripe, Apple Pay, and Google Pay to simplify the paywall experience.[00:35:07] Push, don’t annoy: The team’s smart notification timing strategy based on user habits.[00:38:44] Beginner, please: 75% of users identify as new to fitness, so the app is built just for them.[00:39:01] Add friction, raise conversion: How a longer onboarding flow improved paywall success.[00:40:51] One class to hook them: Why Zumba offers just one free class before locking the app.[00:43:25] Three’s the magic number: Users who complete three classes are much more likely to stick.[00:44:56] No trial, no problem: Ditching the monthly trial increased upfront revenue and annual plan adoption.

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• The Past, Present, and Future of Building on Apple — John Gruber, Daring Fireball

  On the podcast I talk with John about the fascinating 40-year history of Apple’s developer relations, how almost going bankrupt in the 1990s shaped today’s control-focused approach, and why we might need an ‘App Store 3.0’ reset.Top Takeaways:🕹️ The 1980s: Apple’s developer DNA was born  Apple’s earliest wins came from nurturing third-party developers, even spinning off its own apps to avoid competing with outsiders.💸 Microsoft saved Apple (literally)  Apple’s near-bankruptcy in the ’90s made them both humble and wary—forever shaping how they deal with developers and competition.🍎 From “please build for us” to “we choose you”  WWDC 2008 saw Apple begging for apps and evangelist emails on slides; today, it’s the other way around.🖥️ The “Delicious Era” fueled iPhone success  Mac indie devs (Panic, Delicious Monster, Bare Bones) built a design-obsessed, passionate community—setting the stage for the iPhone App Store boom.🚪 App Store 1.0: A new world for indies  For the first time, solo developers could launch businesses from home. No server costs, no payments hassle—just build, submit, and sell.🏦 Apple’s rules got stricter as the App Store grew  As the App Store became a services giant, the partnership vibe faded. Developers went from partners to “users” of Apple’s marketplace.📉 App Store math now feels upside down  Today, indie devs can pay Apple millions, while giants like Meta pay almost nothing. The fee logic and incentives don’t fit 2025.⏳ The platform needs an “App Store 3.0” reset  John and David call for a new era: lower fees, clearer rules, and Apple acting as a true platform partner—not just a toll booth.🔄 Developer enthusiasm is Apple’s long-term moat  Apple risks becoming a “legacy only” giant if it loses developer goodwill. The most important apps are still built by outsiders.👥 A generational handoff is coming  With Apple’s senior leadership nearing retirement, now is the time to set new priorities: empower developers, invest in the ecosystem, and ensure Apple’s platforms stay vibrant for decades to come.About John Gruber: 🚀 Author of the Daring Fireball blog, host of The Talk Show, and co-creator of Markdown.🍎 John is a lifelong Apple fan and is passionate about discussing all things iPhone, App Store, and developer relations.💡 “I feel like Apple is dwelling on the success and the innovation that completely revolutionized the phone industry […] for too long and that they should move on and build something else new.”👋  Daring Fireball Resources: Bill Gates in 1984 promoting Apple Macintosh Bill Gates on stage with Steve Jobs in 1983The Macintosh Way — Guy KawasakiCocoa Programming for Mac OS X — Aaron HillegassDaring FireballFollow us on X: David Barnard - @drbarnardJacob Eiting - @jeitingRevenueCat - @RevenueCatSubClub - @SubClubHQEpisode Highlights: [0:00] Apple Kremlinology: Why understanding Apple requires a special kind of obsession - and a long memory.[4:58] Fanboys unite: David shares how his love of Apple led him from audio engineer to App Store developer.[8:48] Turning point: John’s link to David’s iPhone mileage app in 2008 helped jumpstart his indie career.[13:37] Joz, Phil, and Eddy: The developer relations and most of the App Store are overseen by three Apple execs who joined in the ‘80s.[17:01] The crossroads: How Apple’s early decision to unbundle first-party apps in the ‘80s encouraged third-party innovation.[21:25] Hands off: Why Apple’s decade-long retreat from building software paved the way for a thriving developer ecosystem.[27:07] Vision parallels: John compares Vision Pro’s slow start to the original Mac - and explains why it doesn’t have to be perfect (yet).[30:32] Betting on the future: How Apple playing the long-game is their biggest advantage in launching and sustaining new platforms.[33:55] What comes after the Mac: The ‘90s were filled with failed next-gen Apple platforms - and it almost killed the company.[36:47] Burned by success: Apple’s trauma from near-bankruptcy shaped their need to control developer relationships.[41:13] The App Store revolution: Why the 2008 launch of the App Store wasn’t just a business move, it was a turning point for software itself.[45:07] Developer momentum: How passionate indie devs and Mac software of the 2000s primed the iPhone for success.[53:46] iPhone jailbreakers: Why the jailbreak community may have pushed Apple to launch the SDK sooner than expected.[57:39] App Store 2.0: In 2016, Apple dropped some commission rates, opened up subscriptions, and kicked off a new era.[1:03:03] Time for 3.0: Why David believes the App Store needs another reset - and a shift in mindset.[1:08:26] Humility and hardware: Steve Jobs’ 1997 apology to a developer at WWDC still echoes - and it’s exactly what developers need to hear in 2025.[1:13:30] Holding on too tight: How Apple’s fear of losing control is costing them developer goodwill.[1:26:35] A legacy worth protecting: The iPhone isn’t going anywhere - but without change, Apple could become a legacy business as other platforms take over.[1:32:06] Red flags on Vision Pro: Why developers aren’t building for Apple’s newest platform - and why that should worry Apple.[1:39:18] The indie paradox: How small developers pay millions to Apple, while giants like Meta pay almost nothing.[1:41:39] Fluke of history: Schiller once floated capping App Store revenue at $1B. What if Jobs had said yes?[1:44:35] The trust gap: Could a more generous App Store policy bring Netflix and others back?[1:47:08] It’s not too late: Why Apple should proactively change the App Store instead of waiting on regulation.[1:57:26] Developer vibes: A simpler App Store (with clearer rules and lower fees) could renew trust and drive innovation.[2:00:29] Bigger than profit: Making great soft...

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