Complete at least one run of the data analytics simulation for Kelsey-White (KW) in your Harvard Course Pack.

Part 1:

1. How did you do on your best run as determined by total cumulative profit? What strategies did you use? How do you think you can improve?
2. What filters did you use? Did they cause you to change your approach?
3. How did you determine demand? Was a range difficult to deal with? How would a specific number help or hurt your analysis?
4. How did social sentiment influence your decision making? How do you think real consumer products companies (e.g., Proc and Gamble) should use social data?

Part 2:

1. What specific data did you rely on in making your decisions?
2. If a competitor wanted to purchase the Blue brand, how much would the data about Blue be worth? How did you determine that value?
3. Were the analytics used in the simulation descriptive, predictive, and/or prescriptive? Provide specific examples.
4. Which, if any, machine learning approaches do you think would have provided the most benefit in making your decisions? Why?