- Published: September 25, 2022
- Updated: September 25, 2022
- University / College: University of South Australia
- Language: English
- Downloads: 6
Data mining proves to be a very flexible tool that is used across a wide range of businesses. From huge multi-billion dollar credit card companies focusing on a global customer base to small individual firms with a desire to better respond to their customer’s needs and wants. Data mining is the obtaining of massive quantities of data about consumers, analysing it, and then tailoring marketing aims around the data to specifically meet customer needs.
Though this may seem like a logical process for correctly identifying customer wants, the role of data mining enters businesses of today into a completely new concept of marketing as we know it. Before data mining firms would mass market consumers with little or no regard for each individual’s preferences. They are now able to cater their marketing aims directly to each of their individual customers needs, it is with this in mind that each company strives to compete against their rivals and gain large shares of their market place.
Take for example large magazine company Reader’s Digest. With a data base that has existed for 40 years and now holds the information of over 100 million families world-wide it can pick out specific details of its clients that it wishes to focus upon and can market to a customer group as little as 20. The company may research its databases to see who has bought a certain line of books for example and then use those customers to focus on the sales of other books by the same author, or maybe a story tape. This makes the customer feel that their needs are being personally catered for.
Using data mining in this manner enables Readers Digest to select a potential customer base from a very wide range of people. This process can be a huge advantage against high street firms that do not have the access to such information. Catering specifically to the customer’s needs and even personalising products helps to build customer loyalty. Data mining also prevents companies from any unnecessary expenditure and therefore helps to increase profits. Through data mining companies can correctly target their customers and prevent any losses through incorrect targeting of uninterested customers.
Based on previous data patterns a company will be able to forecast for future trends and possible areas of un-profitability, this is known as demand forecasting. Data mining has proven to be very useful for many companies in the prevention of unnecessary marketing. It can save a company a lot of time and effort that could be better focused elsewhere. In this sense it is an example of strategic use of information technologies as the companies will look at the information obtained and revise their marketing objectives around that to more specifically meet customer requirements.