DATA MINING

Knowledge Discovery in Databases (KDD)

From Wikipedia, the free encyclopedia: "Data mining, also known as knowledge-discovery in databases (KDD), is the practice of automatically searching large stores of data for patterns. To do this, data mining uses computational techniques from statistics, machine learning and pattern recognition."

Wikipedia continues: "A simple example of data mining is its use in a retail sales department. If a store tracks the purchases of a customer and notices that a customer buys a lot of silk shirts, the data mining system will make a correlation between that customer and silk shirts. The sales department will look at that information and may begin direct mail marketing of silk shirts to that customer, or it may alternatively attempt to get the customer to buy a wider range of products. In this case, the data mining system used by the retail store discovered new information about the customer that was previously unknown to the company."

Behavioral Database Analysis

Enertex Marketing clients are not selling silk shirts, rather, they are predominately selling the arts and culture. As with the silk shirt example, Enertex searches clients' databases for buying patterns, to identify the best prospects for the use of either the Marketing Department or Development Department, and can further identify poorer prospects less suitable for upgrade or retention.

The representative data mining products from Enertex include the Targeted Response Improvement Method (TRIM) system and the Patron Tenure Analysis and Migration Analyses discussed in greater detail within this site.

For further information about the data mining capabilities of Enertex please call 212-532-3115, or e-mail info@enertexmarketing.com.

We look forward to hearing from you.

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