SLI Systems has announced the launch of its Learning Recommendations product, an add-on to its Learning Search site search solution, to give e-commerce companies a way to offer highly appealing product suggestions to online visitors based on shopper behavior on site.

According to the company, the Learning Recommendations service presents products known to be likely purchases based on the specifics of the shopper's situation at that point in the shopping trip. These results are powered by SLI's patented learning engine, which aggregates customer behavior to determine the relationships between shopping activity and the products and content these shoppers will ultimately select. Factors such as search terms, pages accessed, and items chosen for purchase combine to drive the individual products presented to the shopper and the order in which they appear.

"In general, recommendations tools are shown to generate an average lift in revenue between five and fifteen percent," said Blair Cassidy, VP of product management for SLI Systems. "Yet, we find that merchants more often than not have failed to add these capabilities to their online stores. By building on our popular set of SaaS e-commerce offerings and taking the hard work out of retailers' hands, we hope to bring the benefit of robust recommendations to the many sites that haven't been able to take advantage of them to date."

The company said Learning Recommendations suggestions can be implemented in multiple places, including home pages, landing pages, product detail pages and shopping cart or check-out pages. Product recommendations additionally can appear on mobile devices, at store kiosks, on printed shipping labels or receipts, in order confirmation emails, and in marketing emails.

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