Sub Club by RevenueCat

On the podcast: the month they went from $1M to $12M ARR, selling Brazil on career upgrades instead of English lessons, and why you shouldn’t tell influencers how to do their job.
Top Takeaways:
🔍 Filter creators by reach, not following 
Under 5,000 followers but tens of millions of views means the algorithm has already picked them and nobody else has priced them yet.
🙅 Don't tell influencers how to do their job 
The creator video the CEO didn't like did 30M views across three platforms and took ARR from $1M to $12M in a single month.
🧱 Keep the creator program and paid acquisition as separate streams 
Creators keep generating angles the in-house team has run out of, and paid reproduces whichever video goes viral.
🎓 Staff the program with ex-creators, not managers 
The influencer lead and the country coaches were all making videos first, and each coach now rotates a roster of 20 or 30 creators.
💼 Sell the outcome, not the activity 
A $100-a-year subscription sold in a market with weak purchasing power because the claim was a better job, not better English.
🚧 Growth can be unhinged; the product can't 
Cursing avatars went viral upper-funnel, then users rejected them inside the app, so product rules now live on a one-pager whilst creators keep almost unlimited freedom.

About Adam Turaev:
🗣️ Co-founder of Praktika, an immersive language learning app with generative AI Avatars, empowering the next billion learners to overcome language barriers and seize new opportunities.
👋 Linkedin

💬Adam Turaev on X

🖥️Learn more about Praktika
Follow us on X: 
David Barnard - @drbarnard
Jacob Eiting - @jeiting
RevenueCat - @RevenueCat
SubClub - @SubClubHQ

Episode Highlights:
[00:00] Introducing Adam Turaev of Praktika
[01:26] Why Adam Left Enterprise Chatbots for Language Learning
[04:22] Betting on Conversational AI Before the LLM Boom
[06:45] How Early Chatbot Experience Shaped Praktika
[08:53] Competing With Duolingo by Targeting Career Growth
[10:03] Why Brazil Became Praktika’s First Target Market
[12:23] Selling Better Jobs Instead of English Lessons
[14:07] Building AI Language Tutors Before the Technology Was Ready
[18:41] Will Real-Time AI Translation Make Language Learning Obsolete?
[21:07] Why Speaking a Language Is About More Than Translation
[23:09] What Separates an AI Coach From ChatGPT Voice
[26:10] Why the Job to Be Done Should Drive Product Decisions
[29:16] How AI Could Help Human Tutors Reach More Students
[30:51] Why Praktika Uses Animated Avatars to Reduce Speaking Anxiety
[34:19] Finding Micro-Influencers With High Reach and Low Followings
[37:15] The Correction Video That Took Praktika From $1M to $12M ARR
[40:19] Replicating a Viral Format Across Countries and Creators
[41:49] Hiring Gustavo and Giving Creators Freedom
[43:58] Building an Influencer Program With Over 100 Creators
[46:41] How Praktika Pays Creators and Turns Wins Into Paid Ads
[48:47] When Unhinged AI Avatars Backfired Inside the App
[50:36] Setting Different Creative Boundaries for Growth and Product
[52:25] Reaching $50M ARR With a Team of Just Over 40
[53:14] Building Proactive AI Coaches Beyond Language Learning
[55:13] Balancing AI Inference Costs With Product Quality
[58:04] Why Switching From Flutter to Native iOS Improved Conversion
[01:00:03] Praktika’s Biggest Failed Experiment With AI Avatars
[01:00:35] Why Copycat Competitors Make Growth Harder

On the podcast: the “magic moment” test for whether creators can sell your app, the one number that caps what you can pay them, and why cloning hit apps like Cal AI rarely pays off.
Top Takeaways:
🥊 Choose creator niches by what the viewer wants, not what the creator does
UFC fighters track every calorie, but their audience is on the couch with pizza, and thousands of dollars of posts produced no download spike.
✨ Creator content only sells an app that has a magic moment 
A scan-analyze-result sequence made viewers do a double take; without that, the app’s appearance in a creator’s video reads as an ad and never goes viral.
🧮 Never pay a CPM above your revenue per thousand views, and go flat rate 
Break-even is set by a creator's average views, and the profit sits in the one post that goes mega viral, which a flat fee lets you keep.
🏷️ Keep the price low on purpose when the goal is to be the app everyone has 
$30 a year, among the cheapest in the category, was a deliberate choice to be the easiest app to buy rather than the most profitable per user.
🧬 Sharing the playbook publicly is safe when the edge is a thousand tested details
The clones that copied a public growth story were never going to catch up with a team that was obsessed with small compounding improvements.

About Jake Castillo:
🚀Co-founder of Cal AI, the AI-powered app for easy calorie tracking. Snap a photo, scan a barcode, or describe your meal and get instant calorie and nutrient info
👋 Linkedin
💬 Jake Castillo on X

Follow us on X: 
David Barnard - @drbarnard
Jacob Eiting - @jeiting
RevenueCat - @RevenueCat
SubClub - @SubClubHQ

Episode Highlights:
[00:00] Why the truth is always in the comments
[00:29] How Jake met Zach and joined Cal AI
[06:11] The creator partnership that changed Cal AI's trajectory
[09:45] Why fitness creators were the perfect channel
[13:57] Cal AI's three-step "magic moment"
[17:40] Why Cal AI wasn't afraid of copycats
[19:53] The UFC and mukbang creator bets that flopped
[25:21] How to spot creators who will convert
[28:00] Finding creators before they blow up
[30:12] Pricing creator deals around revenue per 1,000 views
[35:30] Measuring creator performance when attribution gets murky
[39:04] Building the systems to manage hundreds of creators
[43:09] The real secret to signing creators at scale
[46:50] When and how Cal AI added paid ads
[51:59] Keeping the experience consistent from ad to onboarding
[55:07] Why Cal AI kept its price at $30 a year
[58:47] The MyFitnessPal acquisition
[01:03:36] Lightning round: affiliate deals and doing the work

On the podcast: growing for four years on press and organic alone, affiliate deals as an underexplored revenue stream, and why deciding to pivot is the hardest part.
Top Takeaways:
🗞️ A PR retainer can beat paid UA for a mass-market app
A $3–5K monthly retainer produced months with half a million downloads and four years of growth with zero Meta or Google spend.
🤝 Affiliate deals are the revenue stream most subscription apps still ignore
Brands pay commission only on sales, so the pitch to Nike-sized partners is low-risk for them and the deals are reached directly, not invented.
📏 Pick the metric that is the user's outcome and A/B test every feature against it
A walking app that refuses to track time in app and measures steps instead shipped a feature that lifted steps 10% by locking social media behind a step goal.
🌍 A growth playbook that works in one country can fail completely in the next
The PR strategy that pulled 300,000 downloads from a single French TV segment produced nothing in the US, where nobody knew the founder or the app.
⭐ A celebrity works harder as a shareholder than as a spokesperson 
An ambassador-plus-investor deal changed hiring, press replies, CAC and retention at once, though the impact can be difficult to precisely quantify.
⏱️ At scale, app review times are a growth constraint, not an inconvenience
The more parallel A/B tests you run, the more a 24-hour (or five-day) release cycle caps how fast you can learn.

About Yves Benchimol:
🚶 Founder of WeWard, a free mobile app backed by Venus Williams designed to make walking a more rewarding part of people's lives. WeWard’s mission is simple: to get more people walking the world over.
👋 LinkedIn

🚀WeWard 
🖥️ WeWard Careers

💬WeWard on X

Follow us on X: 
David Barnard - @drbarnard
Jacob Eiting - @jeiting
RevenueCat - @RevenueCat
SubClub - @SubClubHQ
Episode Highlights:
[00:00] Meet Yves Benchimol of WeWard
[01:36] Why Yves left B2B retail analytics
[05:04] Shutting down a business to start over
[07:31] Building an app that rewards walking
[09:29] Why WeWard ditched blockchain
[12:24] Choosing user value over technical complexity
[15:55] Loyalty, gamification, and motivational layers
[17:41] Why WeWard measures steps, not screen time
[18:37] Building revenue beyond subscriptions
[21:46] How affiliate marketing fits WeWard
[23:54] Using PR as the first acquisition channel
[25:18] 300,000 downloads in under five minutes
[28:32] Four years without paid UA, and why US press fell flat
[31:12] Why US growth required local credibility
[33:11] Pitching Venus Williams at lunch
[37:47] What Venus Williams brings as ambassador and investor
[42:01] What's next for WeWard's global growth
[43:14] Staying ahead of copycat apps
[46:25] Locking social apps until users walk
[48:27] Motivational layers and staying focused on walking
[50:11] Localizing rewards across 29 countries
[52:35] Why growth strategies change by market
[54:10] Moving to the US to scale WeWard
[57:13] Why big growth requires bigger bets
[1:00:06] Biggest win: rebuilding the onboarding
[1:00:46] Biggest fail: returning to B2B
[1:01:46] Why mobile app iteration is still too slow

On the podcast: scaling to $10M ARR with a team of ten, having every employee do two user interviews a week, and why their hard paywall "win" backfired.

Top Takeaways:
🧪 Trial-start rate is the wrong scoreboard 
A hard paywall and a no-exit discount both lifted trial starts, then refunds spiked by more than the gain; judge paywall tests on net revenue after refunds, on a matured cohort.
🗣️ Every employee does two user interviews a week, engineers included 
Automated invites to a mixed sample of users book whoever has calendar space, so the whole team hears customers directly instead of through a PM.
💳 Charge from day one to find out who you're building for 
A plain $10-a-month paywall with a one-week trial at launch filtered for willingness to pay and freed the team to work on onboarding and the core product instead of pricing tests.
🧩 Mixing other apps' playbooks is the worst strategy of all 
Duolingo's freemium base only works because it teaches the basics of everything to hobby learners; a product for high-intent professionals should ignore that base entirely.
📅 Lead with annual to know your channel ROI the week the trial ends 
Annual cash lands after the seven-day trial, so payback per channel is visible immediately and can be reinvested; monthly leaves you guessing between one month and 24.
🧑‍💻 $10M ARR with 10 people runs on owners, one meeting a week, and everyone shipping
Hire founder-type doers, hold a single Monday sync, and let AI coding tools turn the whole team, including a non-technical CEO, into builders.

About Anada Lakra:
Anada Lakra is the Co-Founder and CEO of BoldVoice, an AI accent and speech coach for the billion people who speak English as a second language. The app provides real-time feedback powered by our proprietary speech models and lessons from Hollywood accent coaches.
👋 LinkedIn
🗣️BoldVoice 

Follow us on X: 
David Barnard - @drbarnard
Jacob Eiting - @jeiting
RevenueCat - @RevenueCat
SubClub - @SubClubHQ

Episode Highlights:
[00:00] Building a subscription app by focusing on product value over paywall hacks 
[01:12] Anada's personal experience with communication barriers 
[08:53] The early founding story of BoldVoice 
[13:30] Why BoldVoice charged from day 1 
[16:36] Why over-optimizing paywalls distracts teams from improvement 
[18:40] Why mature net revenue after refunds is an important metric 
[22:04] How hard paywall experiments backfired once refunds were factored in 
[24:17] BoldVoice's reverse-trial freemium model & why it ignored the Duolingo playbook 
[33:32] How BoldVoice found its real ICP: professionals over students 
[36:42] Keeping customer obsession alive with user interviews 
[43:29] How Accent Oracle drove a major viral growth moment 
[48:33] BoldVoice's approach to paid growth and annual plans 
[50:45] How BoldVoice reached $10M ARR with 10 people 
[55:02] The expansion from accent training to spoken-English fluency 
[1:00:37] The stigma around accents and how BoldVoice hopes to change that

On the podcast: scaling Meta ads from zero to $100,000 a month, why they waited a year after launch before buying ads, and how a pricing page experiment shifted users toward annual subscriptions.

Top Takeaways:

📉 A big audience buys you a launch spike, not a growth engine
Even 7 million subscribers produce a bump at launch and a steady trickle after; durable growth still came from paid ads, SEO, and a product that converts cold traffic.
🧱 Fix trial-to-paid before you spend a dollar on ads 
A full year of product work before the first ad lifted the conversion floor for every channel, because paid traffic always converts colder than organic.
🧲 Cold traffic converts better on a quiz than in the App Store 
A long, personalized web quiz educates users, overcomes objections, and raises perceived value — and it beat direct-to-store traffic in a head-to-head test, which is why 90% of traffic goes there.
💰 Show annual first and shrink the perceived risk, not the price 
Presenting annual upfront with a day-by-day trial timeline and a promised day-12 reminder shifted plan choice from 60/40 to 75–80% annual, with no price change.
👯 A two-person plan is retention insurance disguised as a discount 
15% off for adding a workout partner gets 15% of trial starts to take it, raising order value and keeping both users subscribed longer.
🔬 70% of experiments fail on the first try — winners come from documenting why 
Locking in the problem before brainstorming solutions, and writing every test down, turns failures into iterations instead of dead ends.

About Ethan Ethier:
🏋️Head of Growth and Operations at Built With Science, a science-based fitness app founded with YouTuber Jeremy Ethier. Personalized workout plans, nutrition guidance, and AI-powered coaching designed to help users train with research-backed methods.
👋 LinkedIn
🚀 Built with Science 
🖥️ Built with Science Careers

Follow us on X: 
David Barnard - @drbarnard
Jacob Eiting - @jeiting
RevenueCat - @RevenueCat
SubClub - @SubClubHQ