Data Mining Techniques For Marketing, Sales, and Customer by Gordon S. Linoff, Michael J. A. Berry
By Gordon S. Linoff, Michael J. A. Berry
* jam-packed with greater than 40 percentage new and up to date fabric, this version indicates enterprise managers, advertising analysts, and information mining experts easy methods to harness primary info mining tools and strategies to resolve universal kinds of company difficulties* every one bankruptcy covers a brand new information mining strategy, after which exhibits readers how one can follow the approach for more advantageous advertising, revenues, and customer service* The authors construct on their attractiveness for concise, transparent, and useful motives of complicated recommendations, making this ebook the appropriate advent to information mining* extra complicated chapters hide such themes as how you can organize info for research and the way to create the required infrastructure for information mining* Covers middle facts mining recommendations, together with determination bushes, neural networks, collaborative filtering, organization principles, hyperlink research, clustering, and survival research
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Additional resources for Data Mining Techniques For Marketing, Sales, and Customer Relationship Management
Success in using data will transform an organization from reactive to proactive. This is the virtuous cycle of data mining, used by the authors for extracting maximum benefit from the techniques described later in the book. This chapter opens with a brief case history describing an actual example of the application of data mining techniques to a real business problem. The case study is used to introduce the virtuous cycle of data mining. Data mining is presented as an ongoing activity within the business with the results of one data mining project becoming inputs to the next.
Mining data to transform the data into actionable information. 3. Acting on the information. 4. Measuring the results. Transform data into actionable information using data mining techniques. Identify business opportunities where analyzing data can provide value. Act on the information. 1 2 3 4 5 6 7 8 9 10 Measure the results of the efforts to complete the learning cycle. 1 The virtuous cycle of data mining focuses on business results, rather than just exploiting advanced techniques. The Virtuous Cycle of Data Mining As these steps suggest, the key to success is incorporating data mining into business processes and being able to foster lines of communication between the technical data miners and the business users of the results.
However, the incentive offered to retain a cus tomer is often quite expensive. Data mining is the key to figuring out which 17 18 Chapter 1 customers should get the incentive, which customers will stay without the incentive, and which customers should be allowed to walk. Weeding out Bad Customers In many industries, some customers cost more than they are worth. These might be people who consume a lot of customer support resources without buying much. Or, they might be those annoying folks who carry a credit card they rarely use, are sure to pay off the full balance when they do, but must still be mailed a statement every month.