AI Case Study

Adidas improves online outfit recommendations with the use of machine learning

Through a partnership, Adidas has leveraged Findmine's technology for its online customer experience. The retailer has implemented a machine learning system that pairs items to create outfits, a previously manual task that would take a merchant 20 minutes to complete. Now, Adidas has been able to increase the number of items featured by 960%, while merchants spend 95% less time on the task.

Industry

Consumer Goods And Services

Retail General

Project Overview

"Adidas is partnering with artificial intelligence (AI) platform provider Findmine to offer complete product recommendations on the retailer’s site.

The German sportswear company can automatically generate complete recommended outfits as a customer browses the website looking for individual products.

Enter Findmine, with an AI solution that was initially tested out during a six-week period that showed half the traffic to the Adidas site manually-programmed outfits, while the remaining half were offered outfits generated by Findmine. The pilot proved that both merchants and customers were unable to distinguish the difference between the AI-based outfits and the manually-created ensembles.

“Findmine has helped us reduce the amount of manual work and has helped us ensure that our newest products have cross-selling from day 1, improving conversion, average order value, and customer satisfaction better than any other solution we’ve tried,” said Bryan Klavitter, senior director, Adidas consumer experience."

Reported Results

"Since the tech was officially rolled out, Adidas has seen a 95 percent decrease in the time merchandisers spend on Complete the Look, while the number of items featured in the outfits has increased by 960 percent."

Technology

"At my company Findmine, based at NYU Tandon’s Data Future Labs, we teach our system how to learn why an outfit or combination of furniture works, so it can make its own decisions. It allows us to take our customers’ entire product catalogue and build outfits on the fly or keep up with changing inventory — even changing seasons and trends! — because it’s figured out what works and what doesn’t, constantly readjusting to information." (venturebeat)

Function

Marketing

Digital Marketing

Background

"Before the solution, Adidas merchants would have to manually put together outfits for its online “Complete the Look” feature — a process that took 27 steps and 20 minutes to finish, and resulted in fewer than 10 percent of products appearing in the feature. And since the customer average order value (AOV) significantly increased when they were shown a recommended outfit, Adidas wanted to find a way to make the process easier."

Benefits

Data

Outfit pairings