THE GOAL OF CONTACTING EXISTING CUSTOMERS

 

 

 

 

 

 

 

 

 

 

 

 

 

Each of these goals has implications for the data mining process. Contacting existing customers through an outbound telemarketing or direct mail cam­ paign implies that in addition to identifying customers at risk, there is an understanding of why they are at risk so an attractive offer can be constructed, and when they are at risk so the call is not made too early or too late. Forecast­ ing implies that in addition to identifying which current customers are likely to leave, it is possible to determine how many new customers will be added and how long they are likely to stay. This latter problem of forecasting new customer starts is typically embedded in business goals and budgets, and is not usually a predictive modeling problem.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

How Will the Results Be Delivered? A data mining project may result in several very different types of deliver­ ables. When the primary goal of the project is to gain insight, the deliverable is often a report or presentation filled with charts and graphs. When the project is a one-time proof-of-concept or pilot project, the deliverable may consist of lists of customers who will receive different treatments in a marketing experiment. When the data mining project is part of an ongoing analytic customer relationship management effort, the deliverable is likely to be a computer pro­ gram or set of programs that can be run on a regular basis to score a defined subset of the customer population along with additional software to manage models and scores over time. The form of the deliverable can affect the data mining results. Producing a list of customers for a marketing test is not suffi­ cient if the goal is to dazzle marketing managers.