Data Mining - Tools and Benefits of Data Mining

Data Mining

Jenna Walker

Dr. Emmanuel Nyeanchi

Information Systems Decision Making

May 30, 2012

Abstract

Businesses are utilizing techniques such as data mining to create a competitive advantage customer loyalty. Data mining allows business to analyze customer information, such as demographics and purchase history for a better understanding of what the customers need and what they will respond to. Data mining currently takes place in several industries, and will only become even more widespread as the benefits are endless. The purpose of this paper is to gain research and examine data mining, its benefits to businesses, and issues or concerns it will need to overcome. Real world case studies of how data mining is used will also be presented for a deeper understanding. This study will show that despite its disadvantages, data mining is an important step for a business to better understand its customers, and is the future of business marking and operational planning.

Tools and Benefits of data mining

Before examining the benefits of data mining, it is important to understand what data mining is exactly. Data mining is defined as “a process that uses statistical, mathematical, artificial intelligence, and machine-learning techniques to extract and identify useful information and subsequent knowledge from large databases, including data warehouses” (Turban & Volonino, 2011). The information identified using data mining includes patterns indicating trends, correlations, rules, similarities, and used as predictive analytics.

By employing predictive analytics, companies are actually able to understand the behavior of customers. Predictive analytics examines and sorts data to find patterns that highlight customer behavior. The important behavioral patterns are those that indicate what customers have responded to and will respond to in the future. Also, patterns can indicate a customer base that is in jeopardy with the company, customers that are not company-loyal and are easily lost. Predictive analytics of customer behavior can be of great benefit to the business (Turban & Volonino, 2011). Companies are able to build specific marking campaigns and models such as direct mail, online marking, or media marking based on customer preference and are better able to sell their products to a more targeted customer base. Knowing what the customer wants, what they will respond to, and which customer base to focus on takes the guesswork out of marking and product development. Taking the information retrieved and using it correctly will only increase profits (Advantages, 2012).

Association