Sub Club by RevenueCat cover art

Sub Club by RevenueCat

Sub Club by RevenueCat

By: David Barnard Jacob Eiting
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 Interviews with the experts behind the biggest apps in the App Store. Hosts David Barnard and Jacob Eiting dive deep to unlock insights, strategies, and stories that you can use to carve out your slice of the 'trillion-dollar App Store opportunity'.© 2023 RevenueCat Economics Leadership Management & Leadership
Episodes
  • The Post-Attribution Playbook for Growth — Eric Seufert, Mobile Dev Memo

    The Post-Attribution Playbook for Growth — Eric Seufert, Mobile Dev Memo
    Sep 3 2025

    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 growth

    The 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 diversify

    Spreading 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 worked

    Winners 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 early


    You 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 signals


    Algorithms 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.”


    👋 LinkedIn

    Follow us on X:

    • David Barnard - @drbarnard
    • Jacob Eiting - @jeiting
    • RevenueCat - @RevenueCat
    • SubClub - @SubClubHQ


    Episode 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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    55 mins
  • Signal Engineering: Strategic Data Filtering for Better Ad Performance — Thomas Petit, Independent Consultant

    Signal Engineering: Strategic Data Filtering for Better Ad Performance — Thomas Petit, Independent Consultant
    Aug 20 2025
    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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    1 hr and 33 mins
  • Optimizing Funnels, Pricing, and Retention at Zumba — Nicole Page & Lucy Levy, Zumba

    Optimizing Funnels, Pricing, and Retention at Zumba — Nicole Page & Lucy Levy, Zumba
    Aug 6 2025
    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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    48 mins
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