Build a Retail Product-Recall Compliance Feed

A useful compliance feed does more than copy recall titles into a spreadsheet. It preserves source structure, supports catalog matching, records changes, and gives reviewers enough context to explain a decision later. The CPSC Product Recalls Scraper supplies the official recall records for that pipeline.

Model the data for change

Store one canonical notice per CPSC recall ID. Put products, companies, hazards, remedies, incidents, images, and countries into structured child tables or arrays rather than concatenating them into one opaque string. Maintain a separate table linking each recall to the queries that matched it. That distinction prevents duplicates while preserving watchlist provenance.

Add collection time and a content hash. When a later run returns the same recall with changed remedy text, consumer contact, companies, or product details, create a version event and update the current view. Reviewers can then see both the latest instruction and the history they originally acted on.

Match the feed against normalized catalog attributes: brand, manufacturer, model number, product type, sale period, and image. Candidate generation can be automated, but confirmation should use the official notice and documented evidence. Store match status, reviewer, timestamp, and reason. Rejected candidates are valuable training data for improving rules, provided retention and access are governed.

Run a recent-window collection daily and a full or category-specific backfill periodically. Monitor source failures, zero-result anomalies, duplicate IDs, missing source URLs, and sudden schema changes. Alerting on these pipeline conditions is as important as alerting on a recall because silent collection failure creates false confidence.

Keep enforcement and customer communication in controlled downstream systems. The feed should emit evidence and workflow state, not autonomously decide legal scope. With explicit keys, versioning, source links, and human confirmation, retail teams gain a repeatable safety intake layer that can scale across brands and categories while remaining explainable during internal or regulatory review.