Searchspring Launches Personalized Recommendations
Searchspring today introduced a Personalized Recommendations feature to display hyper-relevant products. The product is currently in beta and is expected to be generally available early next year.
"Searchspring's vision for personalization is to equip merchandisers with the most productive combination of AI and human creativity," said company CEO Peter Messana in a statement. "With personalized recommendations, merchandisers can tailor their sites to the individual shopper at a scale that wouldn't be possible without this technology, while still retaining complete control over their online stores."
Ecommerce merchandising teams using Searchspring's Personalized Recommendations will gain deep insight into behavioral data and automatically curate product recommendations site-wide. AI models learn from shopper history, real-time behavior, and preferences to do the following:
- Personalize product recommendations, displaying top items for each shopper based on purchase and browsing behavior;
- Drive cross-sell and upsell, recommending complementary items to the product being viewed or suggesting similar products with higher price points;
- Activate return purchases, recommending recently viewed items and items similar to recent purchases;
- Curate high-performers, boosting trending products based on category or site-wide top sellers; and
- Control which products are displayed in the moment, boosting recommendations of preferred brands or product lines based on specific attributes.
Merchandisers can analyze the business impact of recommendations with product performance and shopper insights, revealing segments of customers who are most likely to respond to retargeting.
This release comes as a result of Searchspring's recent acquisition of 4-Tell and its artificial intelligence-driven personalization engine.
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