An $800+ million dollar innovative leader in the retail and foodservice industries, combining wholesaling, branded products, custom foodservice cutting, cold storage, and transportation of meat, poultry, seafood, and deli food products.
The business challenge
The company traditionally segmented its customers following a basic channel approach. However, as they continued to grow and develop, customer needs and wants were blurring across channels. They needed a way to segment their 3,000+ customers to ensure exceptional products and services were delivered to customers with the highest value. They also needed to restructure their sales organization to better align with the new segmentation approach.
The Baker Tilly approach
Baker Tilly Consulting developed a new segmentation approach using the following methods:
- Data discovery: Identified and analyzed transactional sales data to determine customer segmentation clusters.
- Segmentation modeling: Defined four key customer segments and trends to better align resources based on specific segment needs.
- Organization and alignment: Worked with key stakeholders to anticipate changes to sales department roles, responsibilities, compensation and business processes.
- Offers, incentives and experiences: Guided the company in determining new products and developing specific offers, incentives and experiences for each segment.
- Deployment and implementation road mapping: Developed a roadmap to implement the new sales organization structure, customer offers and experiences, and other key initiatives.
- Cognitive computing: Accelerated the project using our internal turnkey computing analytics platform which allows for direct deployment of analytics in a hosted environment.
The business impact
The company has realized an optimal level of customer focus and sales effectiveness as a result of the segmentation project. Additional impact on the business includes:
- Resource utilization: With new customer segments defined according to revenue potential, the company can better align resources, time and money with their most valued customers.
- Predictive analytics: Using unsupervised machine learning algorithms to analyze product mix, customer buying behavior, and price sensitivity, the company can identify high growth potential customers, improve business forecasting effectiveness, and increase forecasting accuracy of customer buying behavior.
- Customer-centric focus: By defining four key customer segments, the company is able to ensure the delivery of optimal offers, incentives, and experiences for their highest value customers.
- Enhanced customer experiences: An automated process that continually measures and monitors customer behaviors and treatment strategies allows the company to modify customer experiences as needed to drive greater loyalty and satisfaction amongst their most valuable customer segments.
- Increased financial performance: The new customer segments and treatment strategies enabled the company to confidently forecast a 3 percent increase of sales from their highest valued customers which amounted to an additional $8.5 million in revenue.