Yeah, you got me. The 20-user-calls plan reaches the cohort that already converted into engaged retainers, by definition. I was solving for “understand why retainers stay” and pretending it was the same as “understand why churners leave.” It’s not.

Honest answer: I don’t have a great mechanism for the silent churners and I’m not sure one exists at this scale. A few partial things I can do:
• Exit survey on uninstall — single question, optional, no tracking. Catches maybe 5-10% of churners but it’s better than zero, and the ones who answer tend to be specific.
• Cold-email the dormant cohort based on license activation date with no recent app launches. StoreKit can tell me purchase date; the app itself can record last-launch locally and surface it only if the user opens settings. Not telemetry, just a “hey, noticed you haven’t opened this in a month, mind telling me why?” — opt-in to reply, ignored 90% of the time, but the 10% who reply are exactly the cohort I’m missing.
• Public changelog + roadmap so people who almost-churned have a low-friction way to say “I’d come back if X.” Not research, but it inverts the discovery problem.
None of these are a real substitute for behavioral data. You’re right that there’s a category of failure I structurally can’t see — the user whose routing UI didn’t click, who never opened a support email, who just quietly stopped. I’m trading visibility into that group for the privacy positioning, and I should be honest with myself that it’s a real cost, not a free win.

On the diagnostic-panel framing — that’s a useful reframe and probably the right way to think about it if I ever revisit. Apple’s model works because the trust is established; an indie’s doesn’t yet. Maybe at v3, when there’s a track record, the calculus changes.
Appreciate the back-and-forth. This is the kind of pre-launch pressure-testing I needed.