Case Study: Top 10 U.S. Retailer achieves 10%+ revenue uplift with Session AI

AI-Based Personalization Provides 10%+ Revenue Uplift

Top 10 U.S. Retailer, a national retailer with 1,000+ stores and $15B+ in revenue, faced rising cart abandonment and low conversion because it lacked in-session customer data to drive relevant, real-time engagement. To close that gap the retailer engaged Session AI, deploying an Intelligent Customer Engagement (ICE) solution to capture in-session behavior and enrich it with cross-channel customer context.

Session AI implemented an AI-driven intelligence layer that continuously analyzed each shopper’s Customer DNA and used ML to predict intent and trigger personalized in-session interventions. The deployment boosted personalized-offer redemption by 50%+, achieved up to 90% accuracy in predictive models, and produced meaningful revenue gains (reported net lifts up to ~12% and relative per-visitor lifts up to 22.6%), demonstrating Session AI’s ability to increase conversions and reduce abandonment.