The Retail Analytics Council (RAC) is the leading organization focused on the study of consumer shopping behavior across retail platforms and the impact of technology. Established in August 2014, RAC is an initiative between the Medill School of Journalism, Media, Integrated Marketing Communications and the McCormick School of Engineering, Computer Science Department.

 

2021 Q3 Retail Tech Bulletin

 

AI Applications in Bank Marketing Roundtable

 

Meet our newly-added Retail Advisory Board Members

 

Assessing the Impact of Supply Chain Shock

 

Roundtable

AI Issues and Advances in the Restaurant & QSR Industry

 

Retail Robot Roundtable

Robot Adoption Trends in a New Retail World

At the beginning of the project, the team discovered two opportunities for search improvement on the website. One was that some search terms returned no search results. For example, if the search term entered was “Christmas gift for girlfriend” on the website, no product would be returned. However, this is a search term that a customer would very possibly use. The second issue discovered was that some customers perceive a product in a way that is different from how the website management team does. For example, in customer reviews, an item labeled by the retailer as a “casual dress” was described by a customer as a “fancy dress.” This gap creates a potential challenge for generating matching search results and sales.

At the beginning of the project, the team discovered two opportunities for search improvement on the website. One was that some search terms returned no search results. For example, if the search term entered was “Christmas gift for girlfriend” on the website, no product would be returned. However, this is a search term that a customer would very possibly use. The second issue discovered was that some customers perceive a product in a way that is different from how the website management team does. For example, in customer reviews, an item labeled by the retailer as a “casual dress” was described by a customer as a “fancy dress.” This gap creates a potential challenge for generating matching search results and sales.

At the beginning of the project, the team discovered two opportunities for search improvement on the website. One was that some search terms returned no search results. For example, if the search term entered was “Christmas gift for girlfriend” on the website, no product would be returned. However, this is a search term that a customer would very possibly use. The second issue discovered was that some customers perceive a product in a way that is different from how the website management team does. For example, in customer reviews, an item labeled by the retailer as a “casual dress” was described by a customer as a “fancy dress.” This gap creates a potential challenge for generating matching search results and sales.