Phil Carter
Growth advisor and angel investor working with Seed–Series C consumer subscription companies (clients mentioned include Tolan and StudyFetch). Author of the “subscription value loop” framework (value creation → delivery → capture) published on Lenny’s Newsletter.
Strong on: frameworks for subscription growth, AI-era onboarding and personalisation, hybrid monetisation (tiers, AI credits), hard paywall → freemium transitions, AI-assisted creative production.
Bias to keep in mind: consultant — case studies are often anonymised clients or other podcast guests’ stories relayed second-hand; sells a Maven course and advisory services.
Sources: sources/youtube/sub-club-by-revenuecat/ (UYIgu02h8cs).
Notes citing Phil Carter
- Creative volume and hit rate — why you need dozens of ads per winnerPaid social for apps is a volume game — one operator saw 1 winner per ~85 videos and ~$800k of $1.5–1.8M spend wasted; teams now ship 400+ concepts/month, test in cheap geos, and treat flat, "stable" performance as a sign they stopped searching for breakout creatives.
- Free tier or not? Freemium vs charging from day oneWhether to offer a free tier at all — RevenueCat data shows no-free-tier apps convert 10.7% vs 2.1% by day 35 with equal retention, but a free tier pays when free users are your marketing (Opal) or your network (Tinder).
- Free web tools (calculators) as SEO/AEO entry points into the quiz funnelAs AI search eroded blog SEO (30–40% of Built With Science's traffic), they built calculators (calories, macros) that rank well in AI answers, deliver value and hand off into the web quiz — converting slightly better than blog posts; plus Reddit as an early AEO lever.
- Hard vs soft paywallsWhen to force users to pay or leave (hard paywall) versus letting them close it (soft), with a case where adding the X halved revenue.
- Judge paywall tests on net revenue after refunds (matured cohorts)Trial-start lifts from forcing tactics (no X, undismissable discount) can be wiped out by refunds — BoldVoice's refunds rose more than trial starts — so score paywall experiments on net revenue after refunds per exposed user on a matured cohort (trial + ~1 week + ≥2 weeks).
- Lead ads with the product's "magic moment" (often an AI feature)Features that make people react — PhotoRoom's AI background removal, Simply Draw bringing a child's drawing to life, Cal AI's photo-to-calories, Pingo's AI roasting pronunciation — make the best ad hooks, cut CAC and can unlock markets that never worked with paid ads.
- Removing the free trial (pay-up-front plans)When dropping the free trial wins — Natal's no-trial monthly grew monthly subs 2,000% (quarterly +46%, annual +21%), Claim went paid-only after 34% trial starts and 50–55% trial-to-paid — and the prerequisites, plus counter-cases (Ladder, Skylight).
- Reverse trials — converting users who closed the paywallGive users who dismiss the paywall a free week of Pro, push them to enable Pro features, then warn that Pro is ending and offer a discount — Momingo's free-user conversion went 0.4% → 4.5%.
- Structure and concepts for paid app video adsThe hook → app demo → offer → App Store end-card structure for paid app ads, why to test distinct concepts per ICP before variations, and how to match ads to custom product pages.
- Subscription funnel benchmarks (trial start, trial-to-paid, install-to-paid, LTV per install)Target numbers for subscription apps — 5–10% install-to-trial (10%+ with a hard paywall), 30–40% trial-to-paid, ~2–3% install-to-paid, and ≥$3 realised LTV per install before scaling Meta.
- The three-screen pre-paywall sequence (explain the free trial)A 2–3 screen sequence before the paywall ("try free", "we'll remind you before it ends", trial timeline) that raised trial starts 56% in one app; Blinkist, Rest of Me, Cal AI variants.
- Using AI to scale app ad creatives (without fake testimonials)Where AI helps app ad production in 2026 — permutations of real-human ads (ElevenLabs voice/translation, Suno music), AI statics, LLM-brainstormed extreme hooks, Veo 3 / Higgsfield video — and why fully synthetic "testimonials" carry FTC and backlash risk.
- What to put behind the paywall (drawing the free/paid line)How to decide which features are free vs paid — keep the core promise free, gate new self-explanatory features, start things behind the paywall (moving out is easy, moving in is painful), meter usage visibly, and watch for "disgust" reactions, not just A/B lifts.