by Adam Pease
Levi’s, the historic American denim provider, has decided to overhaul its online shopping experience with computer vision. Levi’s move combines visual search with personalization powered by recognition to push forward the customer experience. This blog explores the way that computer vision is affecting the growth and development of eCommerce.
The Era of Video Search Is Here
Levi’s new announcement has two components, one of which goes live next November and one of which goes live next year. The first feature, visual search, has been a sought-after capability in eCommerce for some time. Shoppers are often held back by their own memory, or lack of knowledge surrounding products. They may want a particular product but have forgotten the name, or have trouble finding it in a sea of other similar products. This can discourage purchasing and represents a significant bottleneck to the growth of eCommerce.
Visual search enables users to search digital storefronts using images or the related visual features of images. In Levi’s case, the jeans retailer will be rolling out a feature next month that allows users to upload their own photographs that the store will then try and match with similar products. With a catalog that is massive and decade-spanning, it makes sense that Levi’s would implement a feature that would help its customers find their needle in the haystack more easily.
Optimizing Customer Preferences With Computer Vision
Computer vision systems establish a grammar for parsing images that enable another layer of intelligence into the way that business content is organized. Establishing this basic grammar of recognition can enable enterprises to build more elaborate and multi-layered solutions on top of it. This is exactly the strategy Levi’s is taking.
After releasing visual search, the retailer plans to implement a new top-level organizational system for its storefront that it is calling Grid. The Grid system leverages computer vision to build a more granular understanding of how visual relationships between products correspond to customer preferences.
It will help the provider target its shoppers with suggested products that match their same style preferences. By using the actual recognized appearance of the product, rather than just its metadata, Levi’s is using computer vision to reach a new degree of specificity with its customer personalization.
Bottom Line
Video search has been a long-awaited feature in Western retail markets, and Levi’s is demonstrating that large providers can benefit from investing in computer vision as a way to transform their eCommerce experience. This story demonstrates the way that computer vision can not only improve the customer experience but also transform the way businesses approach understanding their customer preferences.