Database : Get a Little Closer

Use effective segmentation with predictive analytics to personalize customer relationships

Segmentation is a way of grouping people or organizations with similar demographic profiles, attitudes, purchasing patterns, buying behaviors or other attributes to help understand customers more thoroughly and thus market to them more effectively.

The problem is many businesses use segmentation to only recognize that every customer has some unique characteristics, providing a somewhat superficial view for each.

For this reason, traditional segmentation often can be a “blunt instrument,” leading to one-to-some marketing. It’s too simplistic and lumps together customer groups that have distinct preferences and behaviors—and it can perpetuate “accepted wisdom” about customers and the market that isn’t necessarily accurate.

However, marketers that add predictive analytics to the segmentation process can generate the insight needed to more effectively and efficiently acquire, grow and retain the right customers. The result is a better understanding of what products and services customers are likely to want next.

Predictive Analytics’ Role
The approach taken by many marketers using predictive analytics can be thought of as auto-segmentation. Predictive analytics technology can discover automatically which groupings exist in customer data and find relevant patterns that are likely to be much more subtle, extracting much greater predictive insight than traditional segmentation.

This ensures segmentation is objective, insight is obtained into what customers want and how they behave, and marketing decisions made are evidence-based and result in more profitable outcomes from one-to-one customer interactions.

Predictive analytics technology incorporates data collection, statistics, modeling and deployment capabilities, and drives the entire segmentation process, from gathering customer information at every interaction to analyzing the data and providing specific, real-time recommendations on the best action to take at a particular time, with a particular customer. The result is more effective customer relationship management strategies, including advertising and marketing campaigns; upsell and cross-sell initiatives; and long-term customer loyalty, retention and rewards programs.

Navy Federal Credit Union, one of the world’s largest credit unions and one of the 50 largest financial institutions in the United States, uses predictive analytics to study its 3.2 million members’ buying habits. The credit union created more sophisticated segmentation functionality, allowing it to determine which members best matched specific product and service offerings, thus eliminating the guesswork many direct mail solutions impose.

While it was important to know what products and services members were interested in, as well as how they used them, predictive analytics allowed Navy Federal to dig deeper into its segments to better understand members’ responses and predict how they might respond in the future.

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