A firm that sells software services has been piloting a new product and has records of 500 customers who have either bought the services or decided not to. The target value is the estimated revenue from each sale. The global mean is $2128. However, the cost of the sales effort is not cheap the company figures it comes to $2500 for each of the 500 customers (whether they buy or not). The firm developed a predictive model in hopes of being able to identify the top spenders in the future. The lift and decile charts are shown in the following figures.

Lift chart (validation dataset) 500,000 400,000 300,000 Cummulative Cumulative profit when sorted using predicted values 200,000 100,000 Cumulative profit using average 0 0 100 200 300 # Cases Decile-wise lift chart (validation dataset) 3 2.5 2 Decile mean / Global meam 1.5 1 11 0.5 o 1 2 3 4 5 6 7 8 9 10 Deciles a. If the company begins working with a new set of 1000 leads to sell the same services, similar to the 500 in the pilot study, without any use of predictive modeling to target sales efforts, what is the estimated profit? b. If the firm wants the average revenue on each sale to at least double the sales effort cost, and applies an appropriate cutoff with this predictive model to a new set of 1000 leads, how far down the new list of 1000 should it proceed (how many deciles)? C. Still considering the new list of 1000 leads, if the company applies this predictive model with a lower cutoff of $2500, how far should it proceed down the ranked leads, in terms of deciles