Marketplace Discovery & Search Expansion

Context

A marketplace product had strong supply and demand, but discovery quality was creating friction. Users could search, browse categories, and filter listings, yet the product needed a clearer path from intent to relevant results.

The work focused on marketplace search expansion, category structure, listing quality signals, and the operational patterns needed to keep discovery improving after the first technical pass.

Challenge

Marketplace discovery problems rarely live in one layer. Query handling, taxonomy, listing metadata, ranking rules, moderation workflows, and product analytics all influence whether users find what they came for.

The technical challenge was to improve relevance and coverage without overfitting to one surface, creating a brittle rules engine, or exposing operational complexity to users.

Approach

• Clarified the highest-value search and browse journeys.
• Reviewed category and attribute structures for gaps, ambiguity, and inconsistent metadata.
• Identified where AI-assisted workflows could improve listing interpretation, query expansion, and content normalization.
• Separated quick product wins from deeper search infrastructure decisions.
• Created a phased execution plan that a product and engineering team could ship safely.

Outcome

The work produced a clearer discovery strategy, a more maintainable technical roadmap, and a stronger connection between marketplace operations and product search quality.

Privacy note

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