By Mary Cicalese
Founder, GROW
Companies today experience an unprecedented ability to collect and store information from customers and prospective customers. Such activities as credit card transactions and point-of-sale purchases, as well as information gleaned from customer loyalty cards, generate enormous amounts of raw data that can be translated into useful information that tracks purchasing behavior and patterns. With effective data mining techniques, this knowledge becomes useful in developing strategies about management, marketing, and investments.
Data mining reveals factors such as market segmentation, which identifies common characteristics of people who buy the same products or services from an organization. In addition, data mining permits organizations to pinpoint which prospective customers they should include on mailing lists for ideal direct marketing efforts and, for interactive marketing, which websites are more likely to be interesting to target customers. Companies often use data mining to recognize customer churn, the movement of customers from one product or brand to another, and market basket analysis, which ascertains which products are often bought together, such as soft drinks and diapers. Moreover, data mining helps companies determine what type of transactions carry a high risk of being fraudulent.
The explosion of available data storage as well as its relatively low cost enables companies to maintain vast stores of data from customers. Whether companies keep collected data on physical servers or in cloud-based storage, new security methods as well as an ever-increasing storage capacity offer even the largest organizations the opportunity to amass huge amounts of data. Moreover, new technologies that enable businesses to retrieve, sort, and interpret data promote the use of data mining by making it a faster and more focused process.
Prior to the advent of such technologies, most businesses lacked the ability to create meaningful reports of data collected from customers. Even after many organizations adopted the use of comprehensive computer systems, weeding through the data proved to be cumbersome. Even today, data mining requires highly specialized skills and knowledge. An investment in data mining, however, allows for the development of cohesive, consequential programs that target products and markets most likely to provide growth opportunities for an organization.
Because campaigns created with the results of data mining are based on actual customer purchase patterns and product performance, they generally produce more favorable results than blind campaigns and those based on feelings about what might attract sales and attention.
