Use Case
Machine Learning for Predictive Rescan Accuracy
A machine-learning predictive engine improves the experience of retailers by reducing theft and shrinkage and of customers by preventing interruptions from rescans.
Where: international
Where: international
Mission
Enhance self-scanning reliability by predicting high-risk transactions before checkout. The goal is to reduce unnecessary rescans, prevent losses, and maintain a smooth shopping experience for customers
Solution
MarketSuite's predictive rescan engine continuously learns from fresh data, including new items and evolving customer behaviors. Updates occur automatically and can be as frequent as daily, ensuring the model reflects current trends. Installed engines download the latest model and apply it instantly for incoming requests. This approach minimizes false positives, reduces operational friction, and delivers a consistent, effortless shopping experience.
Digital Ecosystem
Actions
Digital Ecosystem
We implemented a machine-learning engine that analyzes transaction patterns and shopper behavior. It updates models daily based on new data, ensuring accurate predictions.
Expected results
Improved fraud detection accuracy
Enhanced customer satisfaction and trust
Automated model updates without manual intervention
Scalable solution for handheld and mobile self-scanning
Technologies
AI & Data
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