Case study 4
Data mining refers to the nontrivial process of identifying novel, valid, usefully, and ultimately understandable patterns in data stored in the structured database. The data mining method that targets in the development of their targeted advertising is predictive modeling. When using this method, Target can identify the customer segments and the differentially market to the segments. With the use of this method, it focuses heavily on the ability to determine the customer purchasing patterns through their prior purchase behavior and also other demographic data. In this case, using data mining, the company was able to predict whether a woman was pregnant through observing her purchasing patterns and also her demographic profile.
Data mining works to enhance the experience of the customer. Uber is one company that is largely data driven and score for optimal experience and repeat purchase. Uber has a large amount of data, and it tends to use this information for its customer to learn about the customer and also deliver the services that they need. Using the data that the company collects from its clients, it can be able to advertise new services that may be coming through checking the preferences of the client. Therefore, with data mining, Uber has managed to advertise most of its services to its clients. I do not think that it is an invasion of privacy, but just a company doing its business. Companies normally use transactional data when they are learning about the behavior of the customers. It is not an invasion of privacy since it is lawful to store and also analyze the transaction and customer data.
Macys.com is improving its services through analyzing the consumer data so as to gain insight to its loyal shopper base. From the data that they collect, Macys.com tends to use it in creating a personalized customer experience that includes customized incentives at the checkouts. They are also capable of sending a hyper-targeted direct mailing to their clients. A new analytical tool that Macys deploy is predictive analytics. It provides the forecasts what the customers want with more targeted emails and advertisements. Macys tend to use visualization for customer and business insights and also to set the stage for predictive analytics modeling. While using visualization, it is possible to view the trends in the customer traffic from the website such as the way product families are performing.
Macys.com tend to be using analytical software from SAS so as to understand better and also enhance its customer’s online shopping experience, while it increases the retailer overall profitability. With the use of data, Macys can improve customer experience. The company uses data in building powerful tool so as to improve the experience of customers. It also strives to innovate on how to use the data science in these areas. With the implementation of the new tools, Macys observed cost savings in different areas. The new tool did replace the classic model creation process that is manual repetitive and also prone to human error. Therefore, as a result, the company managed to save costs in different areas and also increased its sales.