Evergage Decisions™ includes industry-leading machine learning that automatically determines and delivers the optimal promotion, offer, image, or complete experience to individual website visitors, application users, and email recipients. The first algorithm included in the Evergage Decisions module is Contextual Bandit, which utilizes sophisticated machine learning to evaluate both the likelihood of someone engaging with a particular offer as well as the business value of the offer to the company. For example, if your company has 15 different homepage hero images it could show someone, the model considers each image and all the data available about the person, and then delivers in real-time (<20 milliseconds) the most relevant experience with the highest potential value to the company.
This article details how Evergage Decisions (specifically the Contextual Bandit algorithm) works individually and with Evergage Recommend.
Rather than spend time defining rules about which experiences to show different audiences, Contextual Bandit lets you focus on creating powerful messaging and offers. This means, you don’t need to worry about associating audience segments to particular personalization campaigns. The machine-learning capabilities of Contextual Bandit figures out the optimal experience each time, for each visitor by: