SLI Launches Learning Recommendations Service to Deliver Highly Relevant Product Suggestions and Boost Online Sales
Autonomous Learning Engine Uses Shopper Behavior to Present Products Visitors Are Demonstrated Likely to Buy – on Webpages, in Marketing Emails and on Mobile Devices
SAN JOSE, CA – February 19, 2014 SLI Systems (www.sli-systems.com) today announced the launch of its first-of-kind Learning Recommendations product, an add-on to its flagship 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.
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. Retailers can expect these recommendations to increase average order value, ultimately resulting in bottom line improvement.
Built on SLI Systems’ autonomous learning engine, the Learning Recommendations service follows the same highly successful approach that has made its Learning Search product into the most chosen SaaS search offering among leading online retailers. SLI’s full-service orientation and intimate client knowledge make it easy for retailers to be up and running with recommendations in as little as a few days.
“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.
Learning Recommendations is available immediately. For more information, visit http://www.sli-systems.com/solutions/learning-recommendations.
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About SLI Systems
SLI Systems (SLI.NZ) provides leading SaaS solutions that help online shoppers connect to the products they’re most likely to buy, directly driving increased sales and higher customer satisfaction for online retailers. With offerings that include site search, navigation, merchandising, mobile, product recommendations and user-generated SEO, SLI Systems is the most chosen SaaS-based site search provider to Internet Retailer Top 1,000 retailers. The company’s patented technology continuously learns from the behavior of visitors to deliver the most relevant results possible. Whether via PC, tablet or phone, a site powered by SLI delivers the kind of satisfying search experience that increases conversion rates, secures brand loyalty and results in higher order values. SLI Systems operates on five continents. For more information, visit www.sli-systems.com.