Human-like recommendations
A self-training deep learning system that adapts the digital experience individually to each user by extrapolating buying intent from customer data and predicting products they may be interested in.
Scroll downA self-training deep learning system that adapts the digital experience individually to each user by extrapolating buying intent from customer data and predicting products they may be interested in.
Scroll downSimilar to an in-store salesperson suggesting suitable products for a shopper, the AdaptML™ system mimics human decisioning to present and recommend the most relevant products and offers to each person.
The system breaks down silos between applications and consolidates data to identify in-the-moment buying intent signals, ensuring learnings are shared and applied across channels.
Going head-to-head with decades of human data science experience, AdaptML™ alleviates the need to allocate heavy development resources or build costly in-house algorithms.
Upload a product feed with millions of SKUs to power your deep learning-based recommendations.
Self-learning quickly, frequently, and off a huge amount of data, recommendation results are continuously optimized.
Speed up time to value with an algorithm pre configured based on site trends, user behavior, and customer journey location.
As brands across industries continue to adopt deep learning, learn how it is being adapted for the delivery of product recommendations that enhance the customer experience and generate meaningful revenue.
Tips, strategies, and use cases necessary for closing the Amazon gap.
A guide to effectively deploy product recommendations featuring strategies, best practices, and real-life examples from leading global brands.