Case Study — Retail

Powering Personalized AI Shopping Agents with Real-Time Context

A major retailer deployed mantle to unify customer data across POS, ecommerce, loyalty, and inventory systems — giving AI shopping assistants deep personalization context in real time.

The Challenge

Customer data existed in 14 separate systems: point-of-sale terminals, the ecommerce platform, a loyalty program database, inventory management, marketing automation, and customer service records. Each system had its own view of the customer.

AI shopping assistants could recommend products but had no way to know a customer had just purchased a similar item in-store, returned a product last week, or had specific loyalty tier benefits. The result was generic recommendations that eroded customer trust.

The Solution

mantle unified all 14 data sources and resolved customer entities across online and offline touchpoints. The knowledge graph connected purchase history, browsing behavior, loyalty status, inventory availability, and service interactions into a single customer context.

AI shopping agents now deliver hyper-personalized recommendations informed by the complete customer journey. Real-time inventory awareness ensures agents never recommend out-of-stock products, and loyalty tier context enables personalized offer generation.

Results

14

Sources connected

3.2x

Conversion rate lift

<80ms

Context delivery

200+

Entity types resolved

“Our AI assistants went from generic to genuinely helpful overnight. Customers notice when you actually know their history — mantle made that possible at scale.”

— Chief Digital Officer, Major US Retailer