Sales Data Analytics

Background:

A retail analytics initiative was undertaken to assess shop performance across West Bengal (WB) and its districts over a rolling 12-month period. The goal was to analyze sales trends, identify high-performing and underperforming shops, and optimize executive performance through data-driven insights.

Solution:

Azure’s analytics-driven approach segmented shops into top and bottom quartiles and provided district-wise insights. Advanced tracking mechanisms analyzed trends over 3-month, 6-month, and 12-month moving averages (MMA), helping in strategic decision-making.

Key features of the solution included:

• Real-time Shop Segmentation: Identified top-performing and struggling shops.
• Sales Performance Benchmarking: Compared shops against 12-month rolling averages by 10%, 20%, and 30% thresholds.
• New Shop Monitoring: Tracked newly added shops and their sustainability over six months.
• Executive & PJP Performance: Evaluated adherence to planned journey plans and impact on sales.

Results & Impact:

• 20% improvement in overall sales due to targeted interventions. Optimized field execution, boosting executive efficiency.
• Enhanced decision-making, leading to better market penetration and profitability.

Conclusion:

Through data-driven performance tracking, the initiative successfully enhanced sales growth, shop retention, and strategic planning, creating a scalable and sustainable retail model.

Clients: FMCG Company, India

Technology Used