RETAIL PROMOTION PLANNING ANALYTICS

Creating a segmented promotion strategy for profitable recruitment of new customers during end of season sales for a leading footwear company

1. Context

Due to increasing rentals and grim economic scenario, retail sector in India is facing significant challenges. Companies have to compete heavily to convert consumers with innovative strategies to survive and succeed. Price promotion strategies have become very important for brands to drive footfalls. Our client, a leading high end footwear retailer, wanted to understand the impact of historical price promotions to drive incremental sales and thereby design a promotion strategy for profitable recruitment of new consumers during the upcoming End of Season Sales.

2. Solution

Decision Point followed a 3 pronged approach to the Business Problem –

1. EOSS Situation Analysis
Based on historical participation in promotion Decision Point worked out the System impact in terms of Customers, Profitability, and Inventory

2. Defining EOSS Strategic Priorities
Post understanding of historical performance and combining with current business objective, Decision Point laid out the system priorities for participation in this EOSS

3. Promotion Planning
Decision Point adopted a 3 stepped analytical approach to develop a granular store level plan –

  • Article and Inventory Selection – CART Segmentation to select SKU’s to create maximum system impact in terms of profitability and customer acquisition
  • Promotion Configuration – Spend Sensitivity analysis to divide selected SKU’s across outlets, assign discounting levels  and assign phasing’s across the weeks of EOSS period
  • Impact Assessment – Simulations to generate the estimated impact on the system in terms of various parameters – Gross Profit%, Inventory Cost reduction etc

3. Impact

Based on our recommendation, client redefined the promotion time periods and prioritized the SKU’s and Outlets with a segmented approach generating higher lift in off takes vs. spends and acquiring higher number of new customers.