The item_id in your system rules must exactly match the item_id in your product catalog. Any mismatch breaks the connection between your analytics data and your catalog, preventing Smart Recommender algorithms from functioning correctly. Things might go wrong when item_id values do not match:
Recommendations fail or degrade
Smart Recommender algorithms rely on item_id to identify and rank products. If the item_id passed by your system rules does not match the one in the catalog, algorithms cannot correctly identify top sellers, best-matching products, or category leaders. This results in no recommendations being generated or low-quality recommendations that do not reflect actual product performance.
Ghost products appear in the feed
Analytics events, such as purchases and page views, are attributed using the item_id collected by system rules and passed to the hit. If this value does not match the item_id in your XML feed, the analytics data cannot be matched to the correct catalog entry. The result is ghost products: catalog items that have been updated via XML but carry no analytics history, making them invisible to algorithm scoring.
How to resolve item_id mismatches
Update your XML feed so that every item_id value matches exactly what your system rules collect and pass. Once the values are aligned:
Analytics events will be correctly attributed to the matching catalog products.
Smart Recommender algorithms will have accurate data to generate and rank recommendations.
Top seller and category-based algorithms will reflect real product performance.
After updating your XML feed, allow sufficient time for the catalog sync and algorithm jobs to run before validating the fix. Check algorithm health on the Recommendation Algorithms page to confirm the feed is populating correctly.