Commercial Data Mining by David Nettleton

By David Nettleton

No matter if you're fresh to information mining or engaged on your 10th predictive analytics undertaking, advertisement information Mining should be there for you as an obtainable reference outlining the complete technique and similar issues. during this booklet, you'll study that your company doesn't want a large quantity of knowledge or a Fortune 500 finances to generate enterprise utilizing current info resources. professional writer David Nettleton publications you thru the method from starting to finish and covers every thing from company goals to information assets, and choice to research and predictive modeling.
Commercial information Mining comprises case reviews and functional examples from Nettleton's greater than two decades of business event. Real-world situations protecting purchaser loyalty, cross-selling, and viewers prediction in industries together with assurance, banking, and media illustrate the options and methods defined during the booklet.

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Sample text

Commodities include raw materials and agricultural products and can be monitored, bought, and sold online. Commodities data includes the current (spot) or future prices of specific commodities such as gold, silver, oil, coffee, wheat, platinum, copper, and so on. Commodity prices are particularly relevant to businesses dependent on specific raw materials or primary goods, and historical and future commodity values could, for example, serve as input to a “what if” data model. There are conglomerate indexes for key commodity categories such as fuel, food, and metals.

Fortunately, the consumer is protected by current laws of data protection and privacy. These laws restrict the dissemina tion of data to third parties without the explicit consent of the person involved. The laws also define the type and extent of customer data that can be maintained, restrictions about the usage of the data, and a customer’s explicit acceptance if a company wishes to send publicity about new promotions, and so on. However, in reality, there are cases of bad practices, such as when a customer is obliged to return a postpaid reply to reject an offer.

Demographic data about specific customers can be elicited from them by using the surveys, questionnaires and loyalty registration forms discussed in this chapter. With reference to demographic data, we distinguish between the general anonymous type (such as that of the census) and specific data about identifiable customers (such as age, gender, marital status, and so on). DATA ABOUT A BUSINESS’S PRODUCTS AND SERVICES The data available about a business’s products and services depends on the type of business activity and sector the business is in.

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