MAC Predictive Modeling 5

Question 1

What does a lift curve measure in the context of a marketing predictive model?

Accepted Answer

How much better the model performs compared to random targeting when ranking prospects

Answer

A lift curve shows how much more likely model-selected prospects are to respond compared to a random selection, helping prioritize outreach.

Question 2

In attribution modeling, the 'time decay' model assigns credit by:

Accepted Answer

Giving more credit to touchpoints closer in time to the conversion

Answer

The time decay attribution model gives more credit to touchpoints that occurred closer to the conversion event, reflecting their greater influence.

Question 3

Which evaluation metric is most informative when the cost of false positives and false negatives are very different?

Accepted Answer

F1 Score

Answer

F1 Score balances precision and recall, making it more informative than accuracy when misclassification costs are asymmetric.

Question 4

A company segments customers using K-Means clustering before building a predictive model. What is the primary benefit of this approach?

Accepted Answer

It allows the team to build separate, more tailored models for each customer segment

Answer

Segmenting customers before modeling allows separate, specialized models per cluster, capturing segment-specific behavior better than a single global model.

Question 5

What is 'data leakage' in predictive modeling?

Accepted Answer

Including information in the model that would not be available at prediction time

Answer

Data leakage occurs when future or target-derived information is included in model training, causing artificially inflated performance that won't hold in production.

(MAC) Marketing Analytics Certification Practice Test

(MAC) Marketing Analytics Certification Practice Test

MAC Predictive Modeling 5