What is Product Data Enrichment?
Product data enrichment is the process of adding missing structured attributes to product records by extracting data from live pages, external sources, or AI inference.
Why Enrichment Matters
Product feeds typically contain 20% of the data available on the live product page. Specifications, ingredients, size guides, warranty information, and care instructions exist on your website but not in your feed. Missing data means missing signals for search ranking and AI agent recommendations.
Enrichment Methods
- Web scraping: Crawl live product pages to extract specification tables, ingredient lists, and structured data
- AI inference: Use language models to extract attributes from unstructured descriptions
- Category gap detection: Compare products within the same category to identify missing attributes
Impact
Enrichment typically improves average health scores by 15-25 points. Specification coverage rises from 45% to 87%. Products with complete structured data are cited 3x more by AI shopping agents.
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