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‘Learning’ search engine recommends products to web users

February 26, 2014

SLI Systems has added a Learning Recommendations tool to its site search system, letting advertisers offer product suggestions based on onsite behavior.


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 learning engine, which aggregates customer behaviour 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.
Retailers can expect these recommendations to increase average order value, ultimately resulting in bottom line improvement.
“In general, recommendations tools are shown to generate an average lift in revenue between five and fifteen percent,” said Blair Cassidy, vice president 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.”
Learning Recommendations offers retailers many opportunities to present product suggestions, 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.
Online shoe retailer Footwear Etc. was an early tester of Learning Recommendations and has already benefited from a lift in conversion.
“Based on early use of SLI’s new Learning Recommendations product, we’re already seeing that the feature has improved how customers find products of interest on our site, and we’re confident it will have a solid impact on our sales and revenue,” said Mike Baranov, vice president of e-commerce for Footwear Etc.
http://www.sli-systems.com/solutions/learning-recommendations

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