Activation & onboarding review
Can the model find the friction that matters most and prioritise the fixes?
The PM job
Reviewing a signup and onboarding flow that is losing users.
Why it matters
Anyone can list fifty UX nits. The job is finding the two that explain the drop-off, backed by the funnel data supplied.
What good looks like
- Ties each issue to the funnel data
- Prioritises by likely impact
- Distinguishes activation from mere completion
Deliberately not measured
- Accessibility audit completeness
- Visual redesign
Consequential critique
A generic UX checklist
Decision model, LLM judge and blind PM review
Results
Every setup we’ve tested on this task, across all cases and repeats.
| # | Model · Harness | Task score | Decision model | LLM judge | PM review | Runs | Critical failures | Cost / run | Latency |
|---|
Case viewer
Read the brief, then put up to three outputs side by side. The outputs are the point; the scores just tell you where to look.
Review the first-week experience of our fitness app, described below, and recommend the changes you would make, in priority order, as a memo to the growth PM. Keep it under 500 words.
Focus on getting new users to three workouts in week one (shorter first workouts, a same-day first session, catch-up options, earlier progress feedback) rather than onboarding and paywall polish.
v1.2 · synthetic · consumer, mobile