Watch How a Global Grocer Cut Errors and Increased Speed to Shelf with GenAI
Video Summary
In this case study, Lori Schafer explains how a leading international grocer used Generative AI to dramatically improve product attribution. By automating attribute creation, the grocer reduced errors by 70%, cut manual work time by up to 60%, and accelerated speed to shelf by as much as 40%.
Key Takeaways
Product attribution was slowing down operations and limiting search accuracy
Generative AI automated attribute creation, reducing manual workload
The grocer achieved 40–60% time savings in managing product attributes
Products reached shelves 30–40% faster, delivering measurable speed-to-market gains
Error rates dropped by 70%, improving data accuracy and product searchability
Video Transcript
I’ll share an example from a very large international grocer we’re working with. They started by saying, “We need to improve product attribution so customers can search on the right attributes, and we need to do this much faster.”
By applying Generative AI, we’ve reduced the time they spend on creating product attributes by 40–60%. Accuracy has improved as well, with 70% fewer errors. And overall, products are reaching shelves 30–40% faster.