Case $1$: Improving Customer Engagement at VMWare through Analytics

$1.$ How does B$2$B personalized marketing differ from B$2$C marketing?

$2.$ How is the propensity to respond model different from the traditional propensity to buy model?

$3.$ VMW has identified more than $600$ predictor variables. The data is also highly imbalanced; do you think that techniques such as logistic regression can be applied when the number of variables is large? What variable reduction techniques can be used to make the model more efficient?

$4.$ Discuss the business implications of the models to be developed here. What will be the value additional to the marketing department and the sales department of VMW because of this exercise?