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M8.2 Discussion

M8.2 Discussion

Q In 2012, a major PR fiasco rocked the retail community having to do with data mining and privacy. A Target statistician found a way to analyze historical purchasing data and correlate that data with possible pregnancies. This led the company marketing department to send pregnancy advertisements and coupons to expecting mothers. Then, one day, an angry father arrived at Target demanding to know why Target was sending his high school daughter such advertisements. Later, the father issued an apology. His daughter was due in later that year (Hill, 2012). This story raised both applause and triggered repulsion from the public. It is both amazing that data can make such predictions and provide usable suggestions. It’s also scary that companies have the power to expose our secrets. Initial Post? Your initial post should be at least 400 words, utilize scholarly references and APA, and be posted by Thursday.?In your initial post, answer the following questions:? 1. Is Target’s data mining and predictive analytics a success, a failure, or both? Explain your answer. 2. How does Target create profiles of customers? 3. Is Target’s “pregnancy predictor” a long-term competitive advantage? Explain. 4. How does Target make such accurate predictions? 5. What are the ethical considerations of the use of this data? In your response, complete the following: Response Post? By Sunday,?respond to at least two of your peers in at least 100 words.?Utilize scholarly references and APA. Ask questions to move the conversation forward.?? In your response, discuss the following with your classmates:?? 1. Identify additional identity reasons why Target might invest in predictive analytics. Evaluation This discussion will be graded using the discussion board rubric. Please review this rubric prior to beginning your work to ensure your participation meets the criteria in place for this discussion. All discussions combined are worth 30% of your final course grade.

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Hello everyone. Hope you all are fine. 1. Is Target’s data mining and predictive analytics a success, a failure, or both? Explain your answer. Target’s Data mining and predictive analytics are both the success and the failure. It allows companies to analyze large amounts of customer data to identify patterns and make more informed business decisions. By analyzing customer purchase histories, Target might be able to find out which products are likely to be purchased together, and use this information to optimize product placement in stores or create targeted marketing campaigns (Kim & Kim, 2021).