Marketplace Engineering Two-Sided Personalisation Best Practices

Comprehensive guide for designing, building and improving personalisation and recommendation systems in two-sided trust marketplaces on AWS Personalize. Contains 49 rules across 9 categories, ordered by cascade impact on the personalisation lifecycle, plus two playbooks for planning a new system from scratch and diagnosing an existing one.

When to Apply

Reference this skill when:

• Designing the event schema and tracking for a new recommender system
• Choosing an AWS Personalize recipe (USER_PERSONALIZATION_v2, SIMS, PERSONALIZED_RANKING_v2)
• Writing or reviewing candidate-generation and re-ranking code for marketplace search or homefeed
• Handling cold start for new providers, new seekers, or new catalog regions
• Diagnosing a live system that "mostly works but feels stale, unfair, or unpersonalised"
• Planning the next experiment, baseline comparison, or A/B test for the recommender
• Investigating concentration, coverage collapse, death spirals, or training-serving skew
• Adding observability dashboards, drift detection, or online metric slicing