Pricing Analytics: Finding the Optimal Price-Points for a Consumer Goods Company

The Client

A global food manufacturer with a vast direct network along with a distributor network that reaches major retailers across the US.

The Challenge

5000+ SKUs were being sold through major retailers. The client was using trade deals with their retail partners to increase market penetration and sales. The client had evaluated several optimization solutions but had found them unsuitable. They had very little insight into the effectiveness of pricing tactics while creating new deals.

The Solution

Core Compete developed a complete framework for trade deals to evaluate tradeoffs and simulate the impact of pricing actions on sales and margins. The ‘end-to-end’ workflow for data acquisition to pricing insight generation was automated, freeing time and effort for critical stakeholders for more value-added tasks.

Highlights

  • Automated analysis of weekly retail Point of Sale (POS) data to derive meaningful relationships between pricing actions and sales volumes

  • Pricing insights aid business stakeholders in negotiating better trade deals with retail partners

  • Multiple business stakeholders use insights being automatically generated by the solution

Core Compete in Action

The solution analyzes weekly sales to generate price point curves and tease out meaningful relationships between pricing and volumes, highlighting recommended price-points and bands.

The entire insight generation process is automated to free up time from stakeholders for more value-added analysis.

The Result

The system generates price point curves from weekly sales to identify meaningful relationships between pricing and volume and recommends key price points. The account teams, sales and brand management are utilizing this to make pricing, trade deal creation, and competitive price gap analysis decisions.

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