|University||National University of Singapore (NUS)|
|Subject||Data Science and Machine Learning|
(a) Comparing Amazon Go to traditional brick-and-mortar supermarket shopping, what are some data that can be collected about the customers that cannot be done before?
(b) Based on the data that can be collected (such as those you have mentioned in (a)), what are some metrics Amazon Go can collect to understand shoppers’ shopping behavior? Provide 5 metrics in the table below. For each metric, describe the data that needs to be collected to compute the metric. An example is given in the table.
(c) Through the data that Amazon Go collects about its shoppers, briefly explain what are the different analytics (descriptive, predictive, and prescriptive) that could be performed with such data. For each type of analytics, what are the decisions (s) that can be made to improve customers’ shopping experience?
(d) What are some challenges that Amazon Go might face in conducting these analytics?
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