Last year’s website redesign produces mixed results.
The shoemaker makes instant style recommendations based on site activity.
The Frye Company, a manufacturer and retailer of leather boots and shoes, relaunched its web store in late August. The company says the new site design provides a better sense of the brand’s heritage, and newly added tools like faceted navigation and instant product recommendations make it easier for consumers to find what they’re looking for.
“Personalization was a key objective in our site relaunch,” says Andrew Tarica, digital director for The Frye Co. “We believe having a recommendations engine will help us achieve that goal.”
RichRelevance, a developer of personalization applications, provides the recommendation engine. The engine is integrated with the e-commerce platform The Frye Co. used to build the new site. Digital commerce agency CreateThe Group provides the platform and led the redesign. Frye’s previous web site, which operated on a platform built and maintained in-house, did not include a personalization tool, says CreateThe Group chief technology officer Alan Kung.
“Frye was concerned that the site did not properly reflect the brand or the richness of the products,” Kung says.
Now the site’s recommendation engine suggests products based on an algorithm with more than 40 data points, which include the consumer’s current and previous on-site activity and the on-site behavior of all visitors. For example, if a consumer is browsing women’s riding boots, the recommendation engine may suggest similar styles of women’s riding boots that other visitors have purchased. If the consumer previously purchased a Frye riding boot, the system may display styles similar to the one she bought. Frye can also fine-tune the algorithm so recommendations align with its current business needs. For example, if stock is running low on a particular boot, it can keep that style from appearing as a recommendation.
Tarica says the recommendation tool will provide Frye with customer behavior data, help improve customers’ on-site shopping experience and ultimately increase sales. “We hope to gain a better understanding of how customers interact with our site, and the data supplied adds another level of analytics to our overall web strategy,” he says. “Secondly, we hope the recommendations help our customers find the product that is most suitable and relevant to their tastes.”