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A Simple Bayesian Approach in Mining the Touch Point Data

In any CRM cycle, we often adopt a "multiple touch point" strategy by using phone, mail, email or other communication channel. It is important to know how will a customer react to different touch points, or different combination of touch points. The analytical work could easily become unrealistic as the combinatorial computation could soon beyond reach. Just a 30 touch points system and consider only 5 stages of interaction; the total cases will be 30 to the power of 5 (24.3 million cases!). This is also a path dependent case, as the customer will behave differently if you email first and then call versus call first and then email. I am proposing a simple Bayesian approach to analyze the touch point data.