Bloomreach, the world’s #1 Commerce Experience Cloud, announced Bloomreach Discovery has launched Contextual Merchandising, an algorithm enhancement that allows merchandisers to tailor relevant product recommendations on product detail pages — without technical support — in order to maximize cross-sell and upsell strategies. By selecting different attributes to fuel Bloomreach Recommendations algorithms, merchandisers can train AI to display items that are both relevant to customers and optimized for merchandising goals, driving revenue while showing customers more of what they want to see.

Relevant product recommendations on a product page can offer substantial opportunities for a business to drive additional purchases. With Contextual Merchandising, those opportunities can be built to meet specific merchandising strategies, while still remaining relevant to the customer and the context of the page. Consider a customer looking at a specific brand of handbag. While personalized recommendations on that page would show them other products they may like based on their browsing history, Contextual Merchandising would allow a merchandiser to show items they may like that also match the brand of the handbag the customer is browsing. The recommendations would be highly relevant to the customer while also allowing the merchandiser to drive sales of that specific brand.

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Importantly, merchandisers have the autonomy to create this more relevant experience for customers without the need for technical assistance. A simple adjustment of the attribute selected in the algorithm (such as brand), will automatically adapt the recommendations displayed. This not only provides merchandisers with more control over conversion opportunities, it also offers greater flexibility to adapt merchandising strategies as trends or promotions impact what is relevant to shoppers.

“Bloomreach Discovery offers an ideal balance of AI-driven automation and merchandiser control, and Contextual Merchandising is a great example of what that looks like in practice,” said Aditya Singh, Head of Product, Bloomreach Discovery. “Merchandisers can use their expertise to dictate what a relevant recommendation looks like based on certain customer contexts and merchandising goals, then set the rules that tell AI to do the rest. And they can do it without depending on technical teams. This is going to give merchandisers the control they deserve, customers the experience they want, and businesses the revenue they need.”

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