Data Mining is the process used to extract usable data from a larger set of any raw data. The process analyzes data patterns in larges batches using at least one software. It can be applied by businesses to learn more about their customers and develop more effective strategies. Below are some examples of its application.

Data Mining for Retail

Data mining enables a retail business to know their client’s choices and preferences even better than they do. If you think that sounds crazy, Target Corporation recently broke through another level of customer tracking with the use of it. Target developed a list of 25 products that when purchased together indicate a woman is likely pregnant.

Data Mining in Banking

Banks use data mining to better understand market risks. It is most often used in banking to determine the likelihood of a loan being repaid by the borrower. It is also used commonly to detect financial fraud. An example used is fraud detection is when some unusually high transactions occur, and the bank’s fraud prevention system is set up to put the account on hold until the account holder confirms that this was a legitimate purchase.

Data Mining in Marketing

Data mining is used to explore large datasets to improve companies market segmentation. By analyzing the relationships between variables such as customer age, gender,etc.. it is possible to create a personalized loyalty campaign just for that customer segment. It can also be used to predict which users are likely to subscribe from a service, what interests them based on their searches, or what mailing list should include to achieve a higher response rate.

Conclusion

Many successful companies use data mining to gain a competitive advantage by integrating data insights into their decision-making process. Also to develop strategies based on these insights from their client’s data. These use cases are rapidly expanding every day thanks to the constant development of the data mining field, which continues to provide more and more accurate results.


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Kiel Briggs

Kiel has 10+ years of experience delivering reporting and analytics solutions across many industries. He is a member of the eCapital Analytics Team where he specializes in data visualization, machine learning and system architecture.

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