Cold Start and Feature Availability Questions

Handle situations with limited or no historical data for users, items, merchants, or locations. Evaluate strategies such as content based features derived from metadata, fallback heuristics and rule based policies, collaborative approaches with cold start handling, learned embeddings that use side information, exploration policies for bootstrapping labels, and trade offs between personalization and reliability. Discuss engineering and serving implications when preferred features are unavailable at inference time.