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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Tactical Planning & Execution | 25% | - Efficient Assortment Development - Space Management & Store Clustering - Pricing Strategy & Analysis - Promotional Strategy & Evaluation |
| Topic 2: Data Competency & Analysis | 25% | - POS Data Analytics - Panel Data & Advanced Analytics - Shopper Data & Geo-demographic Analysis |
| Topic 3: Professional Standards & Communication | 10% | - Fact-Based Storytelling & Presentation - Ethics & Legal Implications |
| Topic 4: Category Assessment & Strategy | 25% | - Root Cause Analysis & Insight Generation - Category Health Measurement - Category Definition, Segmentation & Role |
| Topic 5: Business & Supply Chain Knowledge | 15% | - Supply Chain Principles - Retailer Economics & Profitability |
>> New CMA Category-Manager Test Objectives <<
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NEW QUESTION # 64
What is the primary purpose of a promotional strategy?
Answer: B
Explanation:
The correct answer is D .
The CPCM course describes promotion as a key driver of incremental sales and a retailer differentiation tool.
It further explains that the promotion course covers promotion from both a marketing perspective and a promotion/flyer program perspective, including planning, execution, assessment, and the factors that affect promotion outcomes.
That directly supports option D. Promotional strategy is used to influence shopper behavior, create awareness, generate incremental demand, support category objectives, and improve sales performance through targeted promotional activity. The promotion must be assessed through lift, incremental sales, subsidy, ROI, breakeven, cannibalization, and other measures because the objective is not merely to run activity; it is to produce measurable business impact.
Option A is wrong because supply chain and inventory are operational support areas, not the primary purpose of promotional strategy. Option B is wrong because pricing strategy is related but separate. Option C is too broad; promotional strategy supports business growth, but it is not the overall corporate business plan.
NEW QUESTION # 65
Using the formula for ACV weighted distribution, calculate the ACV for a product available in stores with total sales of $2,000,000 and $3,000,000, in a market where the total sales of all stores are $10,000,000.
Answer: B
Explanation:
The correct answer is C .
The CPCM POS Data course covers scanned sales data and POS measures including distribution analysis. For the calculation itself, ACV Weighted Distribution uses the ACV of the stores carrying the product divided by the total market ACV. NielsenIQ explains the same structure: Total ACV for stores carrying the product ÷ Total ACV for all stores .
The product is available in stores with total sales of:
$2,000,000 + $3,000,000 = $5,000,000
Total market sales of all stores:
$10,000,000
Calculation:
$5,000,000 ÷ $10,000,000 = 0.50 = 50%
Option A is wrong because 30% would only use the $3,000,000 store and ignore the $2,000,000 store. Option B is wrong because the product is not available in all stores. Option D is wrong because 66% does not match the ACV-weighted calculation from the values given.
NEW QUESTION # 66
What is the primary purpose of Affinity Models in Category Management?
Answer: D
Explanation:
The correct answer is B .
The CPCM course places affinity-type work inside advanced predictive analytics. The official CPCM course material states that advanced category analytics includes "predictive analytics including collaborative filtering, clustering algorithms, regression models and time-to-event models." In category management, affinity modeling is used to identify relationships between items that are bought together. Oracle Retail describes market basket/affinity analysis as using data-mining techniques to search for sales patterns between products within transactions, such as rules connecting products purchased together.
Option B is therefore the best answer because chips and salsa is a classic co-purchase relationship. Option A describes clustering, not affinity modeling. Option C describes switching or substitution analysis. Option D describes sales forecasting, usually handled through regression, time-series, or other forecasting models.
NEW QUESTION # 67
Which of the following is the first step in the multivariate clustering process?
Answer: B
Explanation:
The correct answer is A .
The multivariate store clustering process starts by identifying the Product Demographic Affinity Profile , because the analyst first needs to understand which demographic groups have the strongest relationship or affinity with the product/category being studied. ARC's category-specific store clustering guidance identifies
"Identify the Product Demographic Affinity Profile (PDAP)" as a core step and then moves into calculating product demand potential.
This sequence matters. You cannot calculate demand potential correctly until you understand the demographic profile that is most relevant to the product or category. Once the product's demographic affinity is known, the analyst can compare that profile to store-level demographic profiles and then create meaningful clusters based on demand and opportunity.
Option B is later in the process because clusters are created after the relevant product and store-level measures are understood. Option C is important, but it follows the product affinity logic. Option D also comes after identifying the demographic affinity profile.
NEW QUESTION # 68
What does a high Sales per Point of Weighted Distribution (SPWD) indicate about a product's performance?
Answer: B
Explanation:
The correct answer is D .
SPWD is a velocity/productivity measure. A high SPWD means the product is generating strong sales for each point of weighted distribution it has. In other words, the product is performing well where it is available
, even if it does not yet have broad distribution.
NielsenIQ explains that sales per distribution point accounts for distribution and ranks products on sales productivity based on distribution levels. It also gives the key interpretation: a product with higher total sales is not necessarily more productive if it has much higher distribution. That is exactly why option D is correct.
Option A is the opposite of the correct interpretation. A high SPWD does not suggest underperformance; it suggests strong velocity. Option B is wrong because total revenue alone does not account for distribution.
Option C is wrong because broad availability is measured by distribution or ACV weighted distribution, not by SPWD. A product can have low distribution and still have high SPWD if it sells strongly in the outlets where it is carried.
NEW QUESTION # 69
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