Remove Customer Experience Remove Loss Prevention Remove Markdowns
article thumbnail

Navigating AI Adoption: Why the Co-Pilot Approach is the Most Successful  

Retail TouchPoints

Early use cases for AI in retail include inventory management, dynamic pricing, customer service chatbots, loss prevention and personalized marketing. Examples can include customer service escalations, product recommendations for high-involvement purchases, new product introductions and other more complicated tasks.

Markdowns 264
article thumbnail

Sick of hearing about AI? The key is understanding how to make it work for you

Inside Retail

This enables retailers to make data-driven decisions, improve forecasting accuracy, and enhance customer experiences, while also reducing costs and boosting profits. Loss prevention: Employs advanced surveillance techniques to detect and prevent shoplifting. Here are the key areas to apply AI in retail.

article thumbnail

5 Major Retail Digital Transformations to Watch For in 2021

Retalon

In effect, this means a reduction of total inventories, maximized sales, and reduced markdowns. This frees physical stores to serve as showrooms for the broader assortment, or better yet, provide customer experiences and events. Retail AI can apply this process when customers return their purchases.