In this episode, we uncover the importance of optimizing demand transfer at the store level. Traditional approaches relying on national demand transfer curves often overlook the unique dynamics of individual stores.

By leveraging AI and store-level data, retailers can accurately predict demand transfer patterns, minimize cannibalization, and maximize incrementality.

We'll dive into the significance of tailoring assortment strategies to specific stores, using the example of Walmart stores in Miami to illustrate the transformative impact of optimizing demand transfer.

Tune in to uncover why optimizing demand transfer at the store level matters for retail success.

Related content you might be interested in:

• Uncovering Latent Shoppers - Bridging the Gap Between Stated Preferences and Actual Shopper Behavior
• The Future of Category Management: Harnessing the Power of Generative AI & Natural Language Models (NLM)
• Deconstructing the Out-of-Stock Problem With AI
• HIVERY's AI uncovers latent shopper insights & gains industry recognition