Dynamic Yield Launches Ranking for Product Listing Pages

Dynamic Yield today launched its deep learning-based Ranking engine, allowing e-commerce companies to personalize their product listing pages.

Designed to automatically generate the optimal sorting order of items across listing pages, Dynamic Yield's Ranking engine uses a self-training deep learning model that predicts which products an individual is most likely to purchase based on past behaviors, in-session activity, and trends across the site at any given moment.

"As COVID-times have created an unprecedented surge in online shopping, serving consumers with the products they have been looking for faster has grown in importance,"said Liad Agmon, CEO of Dynamic Yield, in a statement. "Using Dynamic Yield's Ranking engine to personalize product listing pages, brands can tailor some of their most high-trafficked pages according to each visitor's interest and in-the-moment needs, directly increasing product clicks, add-to-cart rates, and most important, average revenue per user."

During a pilot, e.l.f. Cosmetics saw a 29 percent increase in revenue per user for those who purchased items that were discovered through a personalized listing page, compared to items bought with the default sorting order.

"Listing pages can be cumbersome to navigate. With Dynamic Yield, we have made them fully contextual and adaptive based on who the shopper is during a critical phase of the buying journey," said Ekta Chopra, chief digital officer of e.l.f. Cosmetics, in a statement. "Now, products displayed are more interesting and relevant to the individual, allowing for not only simpler but deeper exploration."