In which of these situations would it be more appropriate to use a probability model rather than a regression/data-mining approach? a. Predicting when the customer will make her next purchase.
b. Predicting which customer is most likely to churn in the next year.
c. Predicting the brand that the customer will buy during her next category purchase.
d. Predicting whether the customer will buy the brand at least once in the next year.
e. Predicting whether the customer will churn in the next year

The correct options are b, c and d.

Step-by-step explanation:

The regression or data mining approach is used to predict the future value of the variable under study.

Whereas the probability model is used to predict the chances or likelihood of an event taking place.

To predict which customer is most likely to churn in the next year, we need to compute the probability for customers who are likely to churn in the next year.

Thus, a probability model would be used.

Each brand has a specific probability of being purchased by a customer.

Thus, a probability model would be used.

In this case also we need to compute the probability of a customer buying the brand at least once in the next year.

The correct options are b, c and d.

i think the answer would be c