Omni-Channel Merchandising Study: Merchandise Technology

JustEnough recently sponsored research by EKN into the current and future state of merchandise planning and uncovered many windows of opportunity for retailers. Over this and the next several posts, I’ll be sharing short, medium and long term recommendations from the study related to merchandising processes and technology that can help retailers execute on a customer-centric merchandising strategy. I hope you enjoy this series of articles.

Here is the fifth and final part:


  Short Term (0 - 6 months)        Medium Term (6 - 12 months)        Long Term (1 - 2 years)

Merchandise Technology

Provide re-forecast and what-if scenario tools to merchandising teams to simulate different seasonal and non-seasonal merchandising campaigns, special promotions, planograms and other execution requirements related to pricing, promotions and micro space management.

Formalize a customer insights knowledge repository for enterprise-wide access that includes a 3-5-year historical internal (retail transaction) and external (competitive) consumer buying trends and data.

Integrate real-time sales data and customer insights into the planning, assortment, allocation, pricing, promotions and replenishment process. Encourage stores and other sales channels to provide direct input for better merchandising planning specific inventory needs and improved sales projections during key selling seasons such as holiday, back-to-school and sales events

Implement a merchandising Big Data strategy by using advanced relational data from transaction, loyalty/rewards, Wi-Fi and mobile data. This will help introduce predictive customer buying insights for internal teams as well as external vendors and brands.

Adopt predictive analytics into the merchandising, assortment planning and rapid replenishment process for top selling seasonal stock keeping units (SKUs). Include causal and cross-category purchase behavior, weather, locational promotions, attachment selling, rapid replenishment and customer loyalty as the first few use cases for creating predictive merchandising insights.

Incorporate a mid to long-term plan for implementing an Internet of Things (IoT) platform strategy that helps utilize store and DC/warehouse sensory device data for improving in-store and DC-based merchandising, picking and replenishment, targeted product information and location-based promotions messaging accuracy.