assume the role of ACITO. You are an assistant chief information technologist for Amazon and are responsible for developing processes to increase sales for Whole Foods which is the grocery store chain owned by Amazon. Amazon currently uses data mining software to increase sales by "up selling" to customers on Amazon.com through recommending products based on products the customer has either viewed or previously purchased. You want to provide the same service for customers who purchase products for home delivery from Whole Foods. The current process is not particularly "smart" as it usually suggests a similar product of the same type rather than a complimentary product or something another customer has purchased. For example, if you go to the Whole Food website and search for tuna salad, usually the recommended product is another tuna salad product. From what I have been told, Whole Foods does not do a good job of up-selling through its online platform.

You want to provide an argument to convince the rest of IT leadership team to allow you to pursue a better modeling technique using data mining. Your argument can be a video, a PowerPoint presentation, an infographic or any other tool that you choose and must have the following components: explain

1. the problem which should include a discussion about the difference between brick and mortar customer behavior and e-customer behavior
2. data mining and why it is needed to address this problem
3. how data mining can help address the problem including specific examples of data mining techniques (e.g., classification, clustering, estimation, etc) and how they can be applied to the recommendation problem
4. how you will know if your solution is successful. You must provide at least two measurable outcomes that will inform the team of the success of your implementation HINT: Think in business terms-higher profits, more products sold, more clicks on recommended products, etc.