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 profit 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 Figure 5.17. (The lifts in the lift chart to be read as 2.40 (for decile 1), 1.90 (for decile 2), 1.70 (for decile 3), 1.50 (for decile 4), and 1.10 (for decile 5)). Questions 12-15 are based on this description.

12. 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 for all 1000 leads combined? Show both the work and answer below.

$2128*1000

13. If the firm wants the average profit on each sale to be 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)? Your answer must include the number of decile(s) and the reasoning below.

14. 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? Your answer must include the number of decile(s) and the reasoning below.

15. Why use this two-stage process for predicting sales (i.e., set a threshold for profit and look for appropriate deciles) – why not simply develop a model for predicting profit for the whole of 1000 new leads?

This is all provided by my professor.

Cumulative Decile mean / Global mean Lift chart (validation dataset) 500000 400000 300000 200000 100000 3 2.5 O 2 1.5 1 5 0 0 0 100 200 300 # cases -Cumulative sales when sorted using predicted values -Cumulative sales using average Decile-wise lift chart (validation dataset) 1 2 3 4 5 6 7 8 9 Deciles 10