Solution uses a self-training ranking engine to dynamically transform static, one-size-fits-all listing pages into fully individualized experiences

Dynamic Yield, the Experience Optimization platform, announced the introduction of its deep learning-based Ranking engine, allowing eCommerce brands to personalize their product listing pages (PLPs).

Dynamic Yield has found – by working with global leading retailers for nearly a decade – that about 80% of users go through PLPs before making their final purchase. While crucial to determining what items a user sees and ultimately buys, most listings displayed remain static, with merchandisers arranging the page based on educated guesses in hopes of driving higher conversions. Designed to automatically generate the optimal sorting order of items across listing pages, Dynamic Yield’s Ranking engine uses a sophisticated self-training deep learning model that was developed in the past year, which predicts what products an individual is most likely to engage with or purchase based on past behaviors, in-session activity, as well as trends seen across the site at any given moment.

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“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. “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 importantly, average revenue per user (ARPU).”

During a pilot, e.l.f. Cosmetics experimented with Dynamic Yield’s latest Ranking engine to tailor its PLP experience. Initial tests led to an impressive 29% 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.

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“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, e.l.f. Cosmetics. “Now, products displayed are more interesting and relevant to the individual, allowing for not only simpler but deeper exploration.”

Gradually being rolled out to customers, the solution is part of Dynamic Yield’s adaptive AI system, which is made up of self-training deep learning algorithms that adapt the digital experience to each individual user by extrapolating buying intent from customer data and predicting products they may be interested in.

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