Product data today supports filters, not questions. Shoppers and AI agents increasingly ask about outcomes and fit. Current data lacks the depth needed for confident answers. Forrester finds 89% of consumers use answer engines to research products. Merchants must shift from attributes to applications in product data. They should identify recurring customer questions about use cases. They must define relevant product applications by category. They should test data against answers, not just attribute completion. They need feedback loops to monitor and improve performance.
What changed
Product data was built to describe products, not answer questions about outcomes or fit.
What it unlocks
Answering shopper questions about real-world use and compatibility with product data.
- 89% used answer engines to research products or services
Sources