Improving the Customer Journey with Advanced Data Analytics
Advanced data analytics are now enabling a more intimate and articulated view of key customers for any consumer products business. Knowing a customer base and knowing their buying behaviors paves the way for a more fluid, productive, and mutually beneficial relationship between manufacturer and customer. When you truly know who your customer is and how they make buying decisions, new possibilities for brand loyalty and overall profit emerge.
A large manufacturing company engaged Clarkston’s experienced consultants to understand the composition of their customer base. Clarkston used the client’s existing data to find actionable insights and provide the foundation for the client’s data strategy as part of a customer segment transformation initiative. The company wanted to explore the capabilities with their current transactional data and how that would support this strategic transformation. There was an organizational shift from a defensive data strategy to an offensive data strategy designed to improve the customer journey.
The use of transactional data, instead of demographic or master data, allowed the client to find insights that enabled increased engagement with target customer segments. Clarkston’s Data + Analytics team utilized advanced data analytics and clustering machine learning techniques to create a roadmap of the customer journey based on buying frequency and market basket composition. The result? A more data-driven organization equipped with analytical support of the manufacturer’s overall strategy.
Across the consumer products industry, businesses are collecting, tracking, and housing data at increasing rates. With the right capabilities and tools, this data has the potential to create demonstrative improvements to strategic initiatives, customer relationships, operational models, and more. As the industry continues to evolve, remaining competitive in your market will be directly correlated to your business’ ability to manage, interpret, and act on data with advanced data analytics.
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Co-authors and contributions by Elise Watson, Jenny McLean, Maggie Seeds, Sebastian Valencia.