Case Study : Transforming B2B Distribution Sales using Predictive Analytics and Data Science

Client Profile

A B2B distribution business that is a market leader in its space with an e-Commerce platform for website sales and also relies on an inside sales force of approximately 30 sales reps. The client distributes thousands of products to thousands of customers throughout the US and some parts of Canada. The distribution centers are located in various parts of the U.S.


The client had a vast amount of fragmented historical and current data regarding customers, products, sales orders etc in ERP/CRM system. The sheer amount of data and reporting made it difficult for the sales reps to get strategic actionable insights to focus on segmented customer groups in depth, such as new customers, existing customers, and lapsed customers. The client needed to focus on high-margin products, retaining current customers and bringing back lapsed customers thus helping their sales reps become strategic in their customer interaction and decision making to achieve higher revenue goals.


By using three years historical sales order data and powerful predictive algorithms, eMoksha enabled a new sales strategy based on customer value scoring. By using this customer value based model, sales reps could see the most valued customers, how much they were buying, how frequently and recently they were buying. The scoring enabled them to go after customers in a strategic way. A predictive model was built to predict which customers they might lose in the future so they prevent customer churn. eMoksha also helped identify which products to promote and bundle for upselling and cross-selling.

Outcomes Achieved

  • Sales quality improvement by engaging with high scoring customers
  • Better quality customer win-backs, more revenue
  • Reduced customer attrition and higher customer retention
  • Overall sales team effectiveness
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