This is like having a smart digital salesperson for every single shopper that instantly figures out what offer or promotion will convince them to buy right now—based on what they’re doing, what they’ve bought before, and what similar people responded to in the past.
Traditional promotions are broad and inefficient—companies overspend on discounts that don’t move the needle and miss chances to convert high-intent customers. This solution aims to tailor offers in real time at the individual level to boost response rates, average order value, and loyalty while reducing wasted promo spend.
Proprietary first-party customer behavior and transaction data combined with ongoing experimentation/optimization and integration into core marketing and commerce workflows.
Hybrid
Feature Store
High (Custom Models/Infra)
Real-time scoring latency and maintaining low-latency access to fresh behavioral features across channels (web, app, in-store, email).
Early Majority
Focus on real-time, individual-level offer selection and optimization rather than static campaign segments, with tighter linkage between behavioral signals and promotion economics (margin, inventory, elasticity).