NetUp Reco" is a next-generation recommendation engine, designed to offer truly relevant products from the very first interaction with a visitor. Unlike traditional systems that rely on fixed rules, typical average profiles, or global statistics, NetUp Reco" uses inductive AI capable of analyzing the precise situation of each visit in real time and individualizing the recommendation in real time.

Its operation is based on the recognition of similar situations in its memory, based on more than 230 behavioral, contextual, and psychological markers captured during each user action (click, scroll, add to cart, etc.). The AI ​​identifies what worked in comparable contexts and instantly applies the most effective recommendation logic.

Each product suggestion is thus adapted to the user's current situation and not to a statistical generality or a pre-established segment.

During our client deployments, NetUp Reco has demonstrated a +392% conversion outperformance compared to traditional machine learning systems based on user profiles or scoring.

All generated recommendations comply with the business rules defined by the e-retailer, such as stock levels, sales priorities, product exclusions, or minimum margins. And thanks to a processing time of less than 35 milliseconds, recommendations are delivered seamlessly across all platforms, without slowing down the user experience.

NetUp Reco integrates easily into all stacks and all journey contexts: homepage, product page, shopping cart, funnel, empty page, email block, etc.