marketplace-pre-member-personalisation

name

marketplace-pre-member-personalisation

description

Pre-member journey of a two-sided trust marketplace — from anonymous landing through onboarding, registration, and the paid-membership paywall. Covers anonymous signal inference, what pet owners specifically need to validate before paying (safety, availability, competence, effort, local cost comparison), what pet sitters specifically need to validate (opportunity, first-stay path, daily commitment, hidden costs), information-asymmetry closure, progressive profile building, social proof, conversion psychology, onboarding intent capture, identity stitching, and pre-member measurement. Triggers on tasks involving visitor-to-member conversion, anonymous personalisation, onboarding flow design, paywall timing, pre-member ranking, or any question about what a pet owner or pet sitter needs to see before paying. Use this skill BEFORE marketplace-personalisation and marketplace-search-recsys-planning.

Marketplace Engineering Two-Sided Pre-Member Personalisation Best Practices

Comprehensive design and diagnostic guide for the pre-member journey of a two-sided trust marketplace. Covers anonymous signal inference, side-specific validation (what pet owners and pet sitters each need to see before paying), information-asymmetry closure, progressive profile building, social proof, conversion psychology, onboarding intent capture, identity stitching, and pre-member measurement. Contains 53 rules across 10 categories, ordered by cascade impact, every rule grounded in published consumer-trust and decision research.

When to Apply

Reference this skill when:

• Designing or reviewing the anonymous landing page and first-render experience
• Choosing what to show a visitor before they have registered or paid
• Designing the onboarding flow and deciding which questions to ask in what order
• Planning the paywall moment — timing, copy, triggers, price anchoring
• Diagnosing a conversion funnel that is leaking between visit and paid membership
• Choosing how to persist visitor state across the anonymous → registered → member transition
• Measuring pre-member experiments and deciding whether to ship an intervention