By Michael J. A. Berry
* choked with greater than 40 percentage new and up-to-date fabric, this version exhibits company managers, advertising analysts, and information mining experts find out how to harness primary facts mining tools and strategies to unravel universal forms of enterprise difficulties * each one bankruptcy covers a brand new information mining strategy, after which exhibits readers find out how to observe the process for more suitable advertising, revenues, and customer service * The authors construct on their popularity for concise, transparent, and sensible reasons of complicated ideas, making this e-book the precise advent to information mining * extra complicated chapters disguise such themes as how you can arrange facts for research and the way to create the mandatory infrastructure for info mining * Covers middle information mining strategies, together with determination timber, neural networks, collaborative filtering, organization ideas, hyperlink research, clustering, and survival research
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Extra resources for Data Mining Techniques: For Marketing, Sales, and Customer Support
But one thing has not changed. The author is still a loyal customer of the Wine Cask, where some of the same people who first introduced him to cheap Algerian reds in 1978 and later to the wine-growing regions of France are now helping him to explore Italy and Germany. After a quarter of a century, they still have a loyal customer. That loyalty is no accident. Dan and Steve at the Wine Cask learn the tastes of their customers and their price ranges. When asked for advice, their response will be based on their accumulated knowledge of that customer’s tastes and budgets as well as on their knowledge of their stock.
Scores can be used to sort a list of customers from most to least loyal or most to least likely to respond or most to least likely to default on a loan. The data mining process is sometimes referred to as knowledge discovery or KDD (knowledge discovery in databases). We prefer to think of it as knowledge creation. What Tasks Can Be Performed with Data Mining? Many problems of intellectual, economic, and business interest can be phrased in terms of the following six tasks: ■■ Classification ■■ Estimation ■■ Prediction ■■ Affinity grouping ■■ Clustering ■■ Description and profiling The first three are all examples of directed data mining, where the goal is to find the value of a particular target variable.
As such, they are the eyes and ears (and perhaps the nose, tongue, and fingers) of the enterprise. The Role of Data Warehousing The customer-focused enterprise regards every record of an interaction with a client or prospect—each call to customer support, each point-of-sale transac tion, each catalog order, each visit to a company Web site—as a learning opportunity. But learning requires more than simply gathering data. In fact, Why and What Is Data Mining? many companies gather hundreds of gigabytes or terabytes of data from and about their customers without learning anything!
Data Mining Techniques: For Marketing, Sales, and Customer Support by Michael J. A. Berry
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