Searchspring, a site search and merchandising provider, has launched its Personalized Recommendations feature to increase personalization options. This AI-powered tool aims to help online retailers optimize the digital journey by delivering an intuitive and connected shopping experience through enhanced personalization capabilities.
Personalized Recommendations utilizes machine learning to provide retailers with insight into behavioral data, while automatically curating product recommendations sitewide. AI models can learn from shopper history, real-time behavior and preferences to:
- Personalize product recommendations: Display top items for each shopper, curated based on purchase and browsing behavior;
- Drive cross-sell and upsell: Recommend complementary items to the product being viewed or suggest similar results with a higher price point;
- Activate return purchases: Recommend recently viewed items and items similar to recent purchases;
- Curate high performers: Boost trending products based on category or sitewide top sellers; and
- Control which products are displayed in the moment: Boost recommendations of preferred brands or product lines based on specific attributes.