Data mining Using Machine Learning Techniques

Data mining is the act of acquiring and analyzing data in order to condense it into better information that businesses can use to determine the best ways to minimize costs and maximize revenues. Because the process is computer-generated, businesses must recruit qualified computer professionals (Banerjee, 2017). Data mining is valuable to companies in a number of ways.

One example is how data mining may assist businesses with sales forecasting. According to Banerjee (2017), the data reveals the number of clients shopping in the company in order to estimate their purchasing behaviors. Second, data mining aids database marketing by taking into account customer trends and so generating items that are appealing to customers. This starts with data collection as the marketer looks for opportunities, for instance, best time for discount promotion so as to win more customers. Third, data collected assists in stock planning because it shows what sells most. From Banerjee (2017)'s perspective, stock planning directs company owners on what to buy, the quantity, balancing the inventory and defining the best price tags for products. Fourth, data mining helps companies retain customers. This is achieved by use of employees' social media, for example, to engage customer segment in Facebook to create ideas for customers' satisfaction, increasing loyalty and improving brand. Using faceoff, companies can get ideas from customers, post them on faceoff and be voted for by people interested in the final idea (Banerjee, 2017). Finally, data mining helps in breaking down market into significant segments like gender, occupation, age and income hence promoting marketing campaigns leading to more business.

In summary data mining creates awareness to companies of their consumers' needs and tastes. From the above discussed ways, data mining is mandatory in generating more business as cited by Banerjee (2017).

Reference

Banerjee, S. (2017). A Survey of Prospects and Problems in Hindustani Classical Raga

Identification Using Machine Learning Techniques. In Proceedings of the First

International Conference on Intelligent Computing and Communication, 458, pp. 467-

475). Singapore: Springer.

https://sci-hub.io/https://doi.org/10.1007/978-981-10-2035-3_48