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.
