Data Mining Cookbook by Rud O.P.

By Rud O.P.

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Topics
Computational Intelligence
Data Mining and information Discovery
Control
Artificial Intelligence (incl. Robotics)

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Sample text

I would check the status from home to make sure there weren't any problems. I didn't want any unpleasant surprises on Monday morning. In this chapter, I begin with an overview of the model-building process. This overview details the steps for a successful targeting model project, from conception to implementation. I begin with the most important step in developing a targeting model: establishing the goal or objective. Several sample applications of descriptive and predictive targeting models help to define the business objective of the project and its alignment with the overall goals of the company.

Lifetime Value A lifetime value model attempts to predict the overall profitability of a customer (person or business) for a predetermined length of time. Similar to the net present value, it is calculated over a certain number of years and discounted Page 12 to today's dollars. The methods for calculating lifetime also vary across products and industries. As markets shrink and competition increases, companies are looking for opportunities to profit from their existing customer base. As a result, many companies are expanding their product and/or service offerings in an effort to crosssell or up -sell their existing customers.

A unique numeric or alphanumeric code that relates to a particular product or service. Sales activity. The amount of the transaction. Date of activity. Date the transaction occurred. A credit card transaction database will typically contain dates, charge amounts, returns, payments, and fee activity including late fees, overlimit fees, and/or annual fees. A useful summarization for modeling is monthly totals for each field. A catalog company's transaction database will typically contain dates, source codes that identify the specific catalog, sales, and returns.

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