Category-Manager Exam Dumps : Certified Professional Category Manager (CPCM)

The correct answer is B .

In fact-based category storytelling, the “What” section establishes the business situation, opportunity, issue, or insight supported by relevant data. It is not the place to dump every chart or every possible observation. CMKG explains that fact-based presentations should focus on growth opportunities for the retailer and translate those opportunities into strategies tied to action. It also states that fact-based presentations should use relevant facts that support the presentation purpose, and irrelevant facts or insights should not be included.

Option A is wrong because detailed appendices may support the story, but they are not the primary focus of the “What” section. Option C is wrong because exploratory analysis happens before the story is built; the story presents the selected insight, not every possible analysis path. Option D is exactly the bad practice CMKG warns against: data that distracts from key ideas and opportunities weakens the presentation.

The correct answer is A .

Predictive analytics is the analytics phase that uses historical data and models to estimate future outcomes. The CPCM course explicitly includes predictive analytics as part of advanced category analytics, including regression models, clustering algorithms, collaborative filtering, and time-to-event models. IBM defines predictive analytics as a branch of advanced analytics that makes predictions about future outcomes using historical data, statistical modeling, data mining, and machine learning.

Option C, descriptive analytics, explains what happened in the past. Option D, prescriptive analytics, recommends what action should be taken. Option B, generative, refers to creating new content or outputs and is not the correct analytics phase here. The phrase “what’s likely to happen next” is the giveaway: that is predictive analytics.

The correct answer is B .

Regression analysis is used to understand how a dependent variable changes in relation to one or more independent variables. In pricing analytics, that usually means analyzing how sales, units, profit, or demand respond to price or other business drivers. The CPCM pricing material identifies correlation and price regression analysis as methods used to evaluate historical pricing and project future sales and profit at specific price points. CMKG also lists advanced pricing analytics as including breakeven point, correlation, price regression, ABC, and slope.

Option A is wrong because calculating an average is descriptive statistics, not regression. Option C is too strong because regression can show relationships or associations, but it does not automatically prove causation. NIST’s regression explanation specifically warns that cause-and-effect cannot necessarily be inferred from regression alone. Option D is wrong because classification belongs to classification models or supervised learning classification tasks, not standard regression analysis.