Hyper-Personalization for Retail

West Loop Strategy helps retailers turn Amazon Personalize into a revenue engine, paired with Amazon OpenSearch for high-quality discovery. We build clean Users, Items, and Interactions datasets, stream real-time click and purchase events into the Personalize Event Tracker, then use OpenSearch for fast text and facet retrieval, including k-NN for vectors. Results are re-ranked by Personalize to blend intent and behavior, which improves relevance for home pages, product detail pages, email, and on-site search.

We select the right recipes, apply business rules such as diversity, price and brand constraints, and stock awareness, then deploy low-latency Campaigns for real-time inference plus Batch Inference for marketing lists. Everything runs in a serverless architecture with Terraform, API Gateway and Lambda with caching, and an MLOps cadence for retraining. We enforce consent and least-privilege access, add observability and A/B testing, and deliver dashboards that tie precision and recall to conversion, average order value, and revenue so you can iterate quickly on true hyper-personalization.