Boosting Easter Chocolate Sales With Mediar's AI Insights

Mediar, leveraging its cutting-edge platform, embarked on a strategic partnership with one of the largest chocolate brands to revolutionize the sales strategy for Easter chocolate tablet sales. This collaboration enabled the utilization of Mediar's platform, which is adept at measuring the ROI of in-store promotions in real-time, thereby offering retailers and brands an unprecedented insight into shopper engagement through actionable data. This case study underscores the transformative impact of Mediar's technology-driven approach, leading to a marked enhancement in the sales of chocolate tablets during the critical Easter season. This initiative not only showcased the synergy between Mediar and a leading chocolate brand but also set a new benchmark in leveraging technology to understand and stimulate market demand.

Background and Challenge

In the competitive confectionery market, maximizing sales during key seasonal events like Easter is crucial. The objective was to identify innovative strategies to increase the sales of chocolate tablets during this period, focusing on shopper conversion rates and the optimization of product placement. A sophisticated, data-driven solution was necessary to effectively understand and influence shopper behavior, ensuring optimal product placement.

Objectives

• Boost sales of chocolate tablets during the Easter season.
• Improve shopper conversion rates through strategic product placement.
• Leverage advanced AI technologies, including computer vision, to analyze shopper behavior.

Methodology

Mediar's approach combined synthetic data generated by AI, machine learning analyses, and real-time shopper behavior monitoring through computer vision and CCTV. This comprehensive methodology included:

Enhancing the Learning Database with AI-Generated Synthetic Data

To deepen the understanding of shopper behavior, AI models were used to generate synthetic data, thereby enriching the learning database. This step was critical in creating a robust foundation for further analysis.

Machine Learning AI and Computer Vision for Comprehensive Data Analysis

The strategy encompassed not just traditional data analysis but also the integration of computer vision techniques to analyze CCTV footage from stores. This multi-faceted approach allowed for a more nuanced understanding of how shoppers interact with products and the store layout. Key methods included:

• Historical Conversion Funnel Analysis: Understanding past shopper behaviors to identify patterns and potential points of improvement.
• Lost Shopper Measurement: Identifying moments where potential sales did not materialize, aiming to understand why shoppers opted not to purchase.
• Behavior Correlation across Categories: Exploring how interactions with other categories could influence chocolate tablet sales.

Utilizing Computer Vision to Analyze Shopper Behavior

Computer vision algorithms were applied to CCTV footage to track shopper movements and interactions within the store, especially in relation to the chocolate tablet displays. This provided invaluable insights into:

• How shoppers navigated the store.
• Dwell times near product displays.
• The impact of store layout and display positioning on shopper engagement.

Solution Implementation

Informed by the insights gained from Mediar's analytics, a new end-of-aisle location near the Housewares was chosen for an additional display of chocolate tablets. This strategic placement was identified as a high conversion area based on Shopper Lab insights.

Results

The strategic display placement led to impressive results in test stores compared to control stores:

• A 63% increase in sales for promoted Stock Keeping Units (SKUs).
• A 53% increase in overall industry sales of chocolate tablets.
• A 44% increase in sales within the chocolate tablet category.

These outcomes highlighted the impact of leveraging real-time data and AI insights for strategic product placement and promotion decisions.

Conclusion

Mediar's use of AI-generated synthetic data, machine learning, and computer vision technologies has set a new standard for optimizing in-store promotions and product placements. The substantial sales uplift for chocolate tablets during Easter demonstrates the effectiveness of a technology-driven approach in the retail industry. This case serves as a model for employing advanced analytics to drive sales optimization initiatives across various retail sectors. Potential clients interested in transforming their sales strategy with Mediar's cutting-edge solutions are encouraged to contact Mediar for more information.