You have just begun working for a baby products company called Baby&Me. The company has a database of 1,000,000 existing customers that are registered with an account on their website.

Just prior to your arrival, the company sent an advertisement via email to a random sample of its existing customers for a premium bottle warmer. Now, the company wants to send out another advertisement to a sample of the other 90% of existing customers for the same product but wants to target the customers most likely to respond based on the results of the first round of advertisements.

Target variable:

• purchased: whether the customer used the discount offer

Attributes:

• repeat_customer: whether the customer has previously purchased a product from Baby&Me
• total_spent: the total amount of money the customer has spent on Baby&Me products
• children: how many children the customer has
• adults: how many adults live in the customer's household

You also have the following information about the product and advertisement:

• Bottle warmer price: $40
• Bottle warmer cost: $10
• Advertisement cost: $0.50

A) Create a cost/benefit matrix table for this situation using the information above.

B) Suppose that you are given a fixed budget of $50,000 to email targeted ads for the bottle warmer and that you decide to set your models to a modestly conservative 60% probability threshold. What is the expected profit for each targeted advertisement sent when using a decision tree and when using a logistic regression subject to the budget constraint?

C) Based on your calculations, which model yields a greater expected profit, and would you recommend Baby&Me send targeted ads?