Key Capabilities & Engine Configuration

Before deploying recommendations in templates, configure the global rules governing the recommendation model.

Core Configuration Settings

• Training Start Date: Defines how far back into your store's sales history the engine looks to learn customer preferences.

• Product Hierarchy Level: Sets the granularity for AI reasoning (e.g., Department, Class, Subclass, or Item Category).

• Fallback Settings (Lookback Days): If personalized recommendations fall short, the model automatically backfills slots with top-selling products from the designated lookback period.

• Exclusion Filters: Prevents restricted items, clearance goods, or specific categories from appearing in recommendations.