CMC Marketing Analytics & Data-Driven Decision Making

Question 1

A marketing consultant wants to measure the incremental revenue generated for every dollar spent on a campaign. Which metric best captures this?

Accepted Answer

Return on Marketing Investment (ROMI)

Answer

Customer Lifetime Value (CLV)

Answer

Cost Per Acquisition (CPA)

Answer

Net Promoter Score (NPS)

Question 2

Which statistical technique is most appropriate for predicting a continuous outcome variable (e.g., monthly sales) from multiple independent variables?

Accepted Answer

Multiple linear regression

Answer

Chi-square test

Answer

Cluster analysis

Answer

Factor analysis

Question 3

A/B testing in digital marketing is best described as:

Accepted Answer

Simultaneously exposing two groups to different versions of a variable to identify which performs better

Answer

Comparing two different target audience segments over six months

Answer

Testing a product in two geographically distinct markets sequentially

Answer

Analyzing before-and-after data from a single campaign change

Question 4

In marketing analytics, what does 'attribution modeling' primarily help a consultant determine?

Accepted Answer

Which touchpoints in the customer journey receive credit for a conversion

Answer

The total cost of a marketing campaign

Answer

How to segment a customer database by demographics

Answer

The optimal frequency of ad impressions per user

Question 5

A data set contains customer purchase amounts that are highly right-skewed due to a few very large orders. Which measure of central tendency should a consultant use to best represent the typical customer purchase?

Accepted Answer

Median

Answer

Mean

Answer

Mode

Answer

Range

Question 6

Which type of data analytics focuses on understanding why something happened by examining patterns and relationships in historical data?

Accepted Answer

Diagnostic analytics

Answer

Descriptive analytics

Answer

Predictive analytics

Answer

Prescriptive analytics

Question 7

A marketing consultant segments customers into groups based on their purchase Recency, Frequency, and Monetary value. This framework is known as:

Accepted Answer

RFM analysis

Answer

SWOT analysis

Answer

STP framework

Answer

PESO model