“White Box” Solution
Unlike the “black box” approach of traditional solutions, with Evergage Recommend, marketers can see and understand how their recommendation strategies actually work. They can create and customize “recipes,” A/B test them against each another and refine them as needed. They can also preview what specific visitors would see before deploying.
Understand True Intent
Clicks lie! If a visitor quickly clicks on an item but then immediately clicks away, that shows disinterest, not interest. While other solutions rely only on clickstream data, Evergage tracks active time spent and engagement levels for each individual, providing a more accurate understanding of true interest and intent. These insights are then fed into Evergage’s machine-learning algorithms.
Deeper data and algorithms that accommodate marketer-defined boosters and filters enable Evergage-powered recommendations to consider individual affinities, preferences and intent – along with information from other customer data sources – resulting in greater relevancy and effectiveness.
No Catalog Feed Required
Evergage does not require companies to integrate with product or content catalogs via APIs. Instead, catalog data is collected in real time as visitors browse the site so everything is current and accurate. You don’t have to wait for newly added products to be promoted or worry about recommending out-of-stock items.