---
title: Personalising the paywall with what onboarding (or the ad) already told you
slug: paywall-personalization-from-onboarding-signals
summary: Carry intent signals into the paywall — Fastic's 20–30-step onboarding (~80% completion) puts the user's target weight on the paywall; Gleam returns a persona scorecard and course picks before asking for money; Apple Ads keyword or ad group can pick the paywall variant.
domain: mobile-apps
tags: [monetization, paywall, onboarding, personalization, intent]
related: [integrated-growth-signal-federation, onboarding-length-long-vs-short, long-paywall-sell-the-outcome, three-screen-pre-paywall-sequence, hard-paywall-by-traffic-source, web-quiz-results-and-email-capture]
sources: [yt:Tid8-QMfpEE, yt:s8Rped5LuWw, yt:_KilixPWX-c]
updated: 2026-10-24
---

# Personalising the paywall with onboarding signals

## TL;DR
- Most paywalls are one tested winner shown to everyone; few apps personalise. The onboarding knows why the user came, the paywall "never finds out".[^1][^2]
- **Fastic** (weight loss): 20–30+ playful onboarding steps with varied inputs (sliders etc.), ~**80% completion**; the paywall then shows the user's **target weight** ("you want to get to 50 kg?").[^3][^4]
- Even **the user's name** on the paywall is a start; implicit signals (screens or features touched in the first session) work too.[^4]
- **Source signals**: the Apple Ads search term or ad group the user came from is intent you can pull into the app to choose the paywall.[^2]
- **Give a personalised artifact before the ask**: Gleam's onboarding ends with a persona scorecard, what to improve and suggested first courses — proof the questions weren't just to get a checkout.[^5]
- Validate every personalisation with an A/B test — "your mileage may vary".[^6]

## Details
**Why it works.** Users now expect long onboardings and notice when answers change nothing; personalising "wows" them and builds trust ([[people/kelvin-zhang]]).[^5] Host [[people/freddy-fang]] says Adapty's study of top-converting onboardings found personalisation was the number-one principle — "this app was tailor-made for me".[^7]

**Signal types to use** (Andy Carvell's framework, [[integrated-growth-signal-federation]]): *intent* (goal, target weight, the keyword searched), *engagement* (features tried), *value* (precursors of purchase).[^8]

**One paywall per entry point (2022).** [[people/dan-burcaw]]: with several custom product pages, it makes sense to run several paywalls aligned with each page's message or campaign — and let marketers change them without an app release.[^9]

**Implementation sketch.**
1. Store onboarding answers and attribution (keyword/ad group/creative) on the user.
2. Template paywall headline and visuals from the top answer ("Reach 65 kg by March").
3. Map acquisition intent → paywall variant (e.g. "edit PDF" keyword → editing-focused paywall).
4. A/B test each against the generic winner on net revenue ([[net-revenue-after-refunds-experiment-metric]]).

## Disagreements / caveats
- Long onboarding isn't free: see [[onboarding-length-long-vs-short]] — Fastic's 80% completion depends on making each step engaging.
- Explicit "just for you" labelling can backfire (TripAdvisor example in that note); personalise quietly.
- No paywall-lift numbers were given for Fastic or Gleam's personalisation.

## See also
- [[long-paywall-sell-the-outcome]]
- [[hard-paywall-by-traffic-source]]

[^1]: yt:Tid8-QMfpEE @ 00:00 — Andy Carvell
[^2]: yt:Tid8-QMfpEE @ 15:46 — Andy Carvell
[^3]: yt:Tid8-QMfpEE @ 17:01 — Andy Carvell
[^4]: yt:Tid8-QMfpEE @ 18:13 — Andy Carvell
[^5]: yt:s8Rped5LuWw @ 42:51 — Kelvin Zhang
[^6]: yt:Tid8-QMfpEE @ 19:03 — Andy Carvell
[^7]: yt:s8Rped5LuWw @ 43:37 — Freddy Fang
[^8]: yt:Tid8-QMfpEE @ 23:56 — Andy Carvell
[^9]: yt:_KilixPWX-c @ 10:12 — Dan Burcaw