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Using Retail Analytics To Improve Pricing Decisions


Consumer products manufacturers are facing an increasingly difficult pricing landscape, partially due to a network consisting of tens of thousands of retailers with varying maturities of data collection and sharing methods. Compounding this, certain manufacturers leverage an Everyday Low Price (EDLP model), requiring that their product is the lowest priced in the store, making it difficult for others to compete on price and protect margins. Learn how this Clarkston Consulting client is using retail analytics to improve pricing decisions.

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A leading consumer products manufacturer with a large spread of products in convenience stores and retail locations engaged Clarkston to help maintain share and profitability in these stores, particularly in the face of a competitor’s EDLP model. Sales representatives serve as their primary channel for negotiating with retailers to discontinue the ELDP model so equipping the sales representatives with more effective tools is critical. With historical data and regional examples, the sales representatives can make a convincing case and show retailers the sales dollars and volumes similar retailers have experienced while not on the EDLP model program.

Clarkston helped enable the sales force by developing interactive and engaging dashboards that sales representatives could reference when meeting with retailers. Clarkston was able to integrate data from multiple sources into Azure Analysis Services, making this the first project the client promoted all the way from development to production in the platform. Clarkston’s work has helped them to convert at least one additional store every single day. This work served as a template and precedent for future work through formalized processes.

To continue reading the Using Retail Analytics To Improve Pricing Decisions Case Study, download below.

Download the Full Case Study Here

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Tags: Advanced Analytics, Analytics, Case Study, Pricing Strategy