if you build it, they may come — keeping your AI on business

MC Escher

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Hand with Reflecting Sphere, MC Escher

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Using Predictive Modeling to Optimize Customer Relationships

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by: Frank Capek Customer Innovations – Driving Profitable Growth

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Predictive modeling uses a variety of analytical techniques to make predictions about the future based on current and historical data. These predictions are expressed as numbers that correspond to the likelihood a particular event, opportunity, or behavior will take place in the future. Predictive modeling can be used in making increasingly effective and individualized decisions about the treatment of customers. These models analyze the customers’ past performance in order to assess how likely a customer is to exhibit a specific behavior or respond to a specific offer.

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“While most of these mature approaches have been run off line, leading organizations are beginning to embed predictive models in customer-facing processes in ways that generate revenue opportunities and control risks in real time during live transactions and interactions with customers. Competitive pressures are driving companies to personalize the way they manage customer relationships. This is increasingly possible as:/Companies have invested heavily in the integration and quality of their customer data.

“More powerful predictive modeling tools are available including advanced statistical regression and time series approaches, as well as, emerging machine learning [also see, see] techniques such as neural networks, radial basis functions [see], and support vector machines. These machine learning techniques provide powerful tools for automated pattern recognition and prediction.

“We see five major application categories of predictive modeling for optimizing customer relationships:” … (full article)

Image Credit: M.C. Escher

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Newcomb’s commentary: “The best vision is insight.” Malcolm Forbes

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