Leveraging AI for Strategic Retail Space Maximization
One of the largest food & beverage companies needed to optimize in-store promotions for salty snacks by identifying “hot zones” in retail stores where promotional materials would have the most impact. The goal was to strategically place displays in areas with high shopper traffic and engagement to maximize visibility and sales.
The company tapped into the robust capabilities of the Mediar Shopper Behavior Lab, utilizing its advanced computer vision and predictive analytics tools. High-resolution cameras monitored detailed shopper movements, capturing data on foot traffic, dwell times, and interactions with different store areas. The Lab processed this data into dynamic heatmaps that identified “hot zones” within each store—critical areas with the highest shopper engagement. The company used these insights to strategically place secondary promotional displays, such as endcap and in-aisle displays, in these high-visibility zones. Furthermore, predictive models developed by the Lab enabled them to anticipate peak shopping periods, such as weekends and seasonal shopping spikes, allowing them to adjust promotional placements and product visibility accordingly. This data-driven approach ensured that promotional efforts were always aligned with shopper behavior, maximizing their effectiveness.
The implementation of this targeted strategy led to a substantial 15% increase in sales during peak shopping periods. By focusing promotional efforts on identified hot zones, the company achieved higher shopper engagement with their displays, leading to enhanced product visibility and an overall improvement in the return on investment for their in-store promotions. The ability to continuously monitor and adjust promotional strategies based on real-time data also provided the company with a significant competitive edge, ensuring that their marketing efforts were consistently aligned with shopper trends and behaviors.
