Data Mining Techniques: For Marketing, Sales, and Customer by Gordon S. Linoff, Michael J. A. Berry

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By Gordon S. Linoff, Michael J. A. Berry

Very good insurance of assorted elements of knowledge mining. well known as a textbook (reason for purchase). lots of snap shots and illustrations; written in transparent and simply understood English.

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Sample text

Phone companies have used call detail records to discover residential phone numbers whose calling patterns resemble those of a business in order to market special services to people operating businesses from their homes. Catalog companies have used order histories to decide which customers should be included in which future mailings—and, in the case of Victoria’s secret, which models produce the most sales. Federal Express used the change in its customers’ shipping patterns during a strike at UPS in order to calculate their share of their customers’ package delivery business.

Data mining is presented as an ongoing activity within the business with the results of one data mining project becoming inputs to the next. Each project goes through four major stages, which together form one trip around the virtuous cycle. Once these stages have been introduced, they are illustrated with additional case studies. TE 22 A Case Study in Business Data Mining Once upon a time, there was a bank that had a business problem. One particu­ lar line of business, home equity lines of credit, was failing to attract good cus­ tomers.

Customers may rate or rerate their past purchases at any time, providing still more feed­ back to the recommendation system. With these recommendations, the web Why and What Is Data Mining? site can offer customers new wines that they should like, emulating the way that the stores like the Wine Cask have built loyal customer relationships. Cross-Selling USAA is an insurance company that markets to active duty and retired mili­ tary personnel and their families. The company attributes information-based marketing, including data mining, with a doubling of the number of products held by the average customer.

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