Topic 02
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Foundational answers
A useful taxonomy separates the browsing hierarchy from the attributes used for filtering and comparison. It should reflect customer language, support operational reporting and remain stable enough for analytics and integrations.
Prioritise attributes customers actually use to narrow a choice: category, size, colour, material, compatibility, use case and key performance characteristics. Attribute coverage matters, but consistent values and sensible naming matter just as much.
Measure required-field coverage by category, not with one global score. Weight attributes by customer and operational impact, then track accuracy, consistency and freshness alongside simple completion.
Review text reveals missing attributes, recurring use cases, fit language, quality concerns and customer vocabulary. Aggregate those signals before changing catalogue data, and keep generated conclusions traceable to the underlying evidence.
A product knowledge graph represents products, attributes, categories, people, use cases and evidence as connected entities. It becomes valuable when relationships improve discovery, validation or reuse—not merely because the data is stored as a graph.