Copyright © 2009 James Taylor. Visit the original article at Personalize customer relationships by personalizing decisions.
Syndicated from BeyeNetwork
David Vergara wrote a nice piece over on Target Marketing recently – Use effective segmentation with predictive analytics to personalize customer relationships. David does a nice job of outlining the steps involved in a segmentation modeling, a key area for data mining and predictive analytics.
To adopt analytics to personalize customer relationships, however, I think you need to go further. I think you need to understand the decisions you make that contribute to the relationship so you can personalize those decisions and, thus, the overall relationship. With an understanding of the decisions involved it will be clear how and where to apply the segmentation and analytic models you have developed – they will help you make better decisions.
To take personalized actions for a customer, you must make personalized decisions about those customers. You must decide if a particular customer will respond positively to this offer. You must decide how hard you want to try to retain a customer, or how flexible you should be in collections. You must decide if a cross-sell is appropriate given a customer’s current state and concerns, and what offer you should use. You must decide that the tradeoff is worthwhile before you offer a new product to replace an existing one. You must identify the decisions that affect your customers and manage them with effective decision services.
Decision services contain rules that are defined by regulation, by policy, by expertise and by the customer’s preferences. They must also contain segmentation models so that different kinds of customers can be treated differently and predictive analytic models that turn uncertainty about a customer’s future behavior into usable probability. And they can use optimization technology to manage tradeoffs and ensure the best use of resources.
Using decision services to automate decisions in this way allows you to put predictive analytics and segmentation models to work. This is the topic of a white paper I wrote (available here) and an upcoming presentation and tutorial at Predictive Analytics World.
