Direct Marketing Magazine shared some ideas about predictive analytics.
Personalize Customer Relationships
Segmentation is a way of grouping people or organizations with similar demographic profiles, attitudes, purchasing patterns, buying behaviors or other attributes. This helps to understand customers more thoroughly and thus market to them more effectively.
Many businesses use segmentation to recognize that customers have some unique characteristics. But they stop when going further may be possible, for this reason, segmentation can be a “blunt instrument,” leading to “one-to-some” marketing. It can perpetuate “accepted wisdom” about customers and the market that are not necessarily accurate.
Marketers can add predictive analytics to the segmentation process to generate insight needed to more effectively and efficiently acquire, grow and retain the right customers. The result could be a better understanding of what products and services customers are likely to want next. Predictive analytics can be thought of as auto-segmentation. This technology can discover groupings in customer data and find relevant patterns that are likely to be more subtle, extracting greater predictive insight than traditional segmentation. This would ensure that insight obtained into what customers want and how they behave, and marketing decisions made would be evidence-based and result in more profitable outcomes from one-to-one customer interactions.
Predictive analytics incorporates data collection, statistics, modeling and deployment capabilities. This 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.
In the next post we will look at a predictive analytics “road map”.
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