A sports betting company is testing the effectiveness of its online ads and has developed a classification model predicts whether a potential customer will respond to its offer using information in the potential customer’s browser history

(cookies, etc.). For the top 10% of customers most likely to respond to online ads in a test dataset, an analyst determines that the lift of the classification model is 5.75. What is a correct interpretation of lift for this subset of customers?

a. The classification model identified 5.75 times more customers that responded to online ads than if a random 10% of customers was selected.

b. The classification model identified 575% more customers that responded to online ads than if a random 10% of customers was selected.

c. The classification model identified 5.75% more customers that responded to online ads than if a random 10% of customers was selected.

d. Over the entire range of threshold values, the classification model is 5.75 more likely to identify a responding customer than a non-responding customer.