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| Section | Objectives |
|---|---|
| Assortment and Space Management | - Retail Optimization
|
| Retail Economics and Supply Chain | - Business Operations
|
| Pricing and Promotion Analytics | - Commercial Strategy
|
| Category Health and Assessment | - Category Performance Evaluation
|
| Shopper and POS Data Analytics | - Building Data Competency
|
| Fact-Based Selling and Storytelling | - Communication and Insights
|
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NEW QUESTION # 59
What is the primary purpose of sub-segment fair share analysis?
Answer: A
Explanation:
The correct answer is B .
Fair share analysis is a relative-performance analysis. CMKG explains that indices compare a result against another relevant reference point or benchmark, and specifically describes Fair Share Index as a way to compare a tactic such as share of shelf, items, promotions, or displays against category share. In category management, the same logic applies to sub-segments: the analyst compares a sub-segment's share against a relevant benchmark to decide whether it is overdeveloped, underdeveloped, or performing at a reasonable level.
Option A is wrong because profitability analysis focuses on margin, profit dollars, or financial return, not fair- share comparison. Option C is wrong because category management does not automatically allocate resources equally; resources should follow shopper demand, strategy, opportunity, and performance. Option D is wrong because identifying the best-selling product is a ranking or sales-volume analysis, not a fair-share analysis.
NEW QUESTION # 60
Which of the following purchase behaviors best explains the category performance?
Dollars: +5%
Number of Households: +2%
Trips per Household: -2%
Units per Trip: +3%
Dollars per Unit: +2%
Answer: A
Explanation:
The correct answer is C .
The category dollars increased by +5% . To identify what best explains that performance, compare the listed purchase-behavior drivers. The strongest positive driver shown is Units per Trip at +3% . Number of Households is also positive at +2%, and Dollars per Unit is positive at +2%, but neither is as strong as Units per Trip. Trips per Household is negative at -2% , so it cannot be the best explanation for growth.
CMKG's shopper analytics explanation supports this type of driver analysis. It explains that sales are driven by household purchasing behavior and spending, and gives the formula: Total Number of Buying Households × Spend per Buying Household = Dollar Sales . CMKG further breaks spending into purchase occasions and spend per trip, which is exactly the kind of logic tested in this question.
Option A is wrong because total baskets are not clearly increasing; the household gain is offset by the decline in trips per household. Option B is partially correct but not the strongest driver. Option D is also positive, but
+2% is lower than the +3% gain in units per trip.
NEW QUESTION # 61
Which of the following methods is used to collect Shopper Data at the point of sale?
Answer: D
Explanation:
The correct answer is C because point-of-sale shopper data is generated through checkout scanning activity.
CPCM/CMKG describes POS data as "retail POS data, including retailer and third-party scanned sales data," and explains that the course covers how POS data is derived, key measures, sales, profitability, distribution, and shopper insights.
The phrase "scanning items at checkout" is the key. POS data is created when products are scanned during a retail transaction. When that transaction is tied to a loyalty card, the retailer can connect the basket to a household or shopper profile, which makes it much more useful for shopper analytics.
Option A is wrong because shipping products from manufacturers is supply-chain movement, not shopper data collection. Option B is wrong because online search queries are digital behavior data, not point-of-sale data. Option D is wrong because mobile tracking may show location behavior, but it is not the standard POS collection method tested here.
NEW QUESTION # 62
What does ROI analysis measure?
Answer: D
Explanation:
The correct answer is D .
The CPCM course identifies Promotion Analysis Techniques as a formal CPCM curriculum area and states that promotional assessment includes "incrementality of the promotion," promotional price, ad space and positioning, display support, seasonality, and competition. It also states that promotion calculations include
"return on investment" and that learners must "assess promotional effectiveness using a return on investment approach." ROI analysis is therefore not just a sales-volume check. It measures whether the promotion produced enough incremental financial return to justify the money, margin, discount, display, ad space, or funding invested in it. A promotion can generate high sales but still be a weak ROI event if the lift is heavily subsidized, margin is sacrificed, or sales are mostly cannibalized from normal purchases.
Option A is wrong because cost savings alone are not ROI. Option B is wrong because customer satisfaction is not the financial ROI measure. Option C is incomplete because total sales volume ignores cost, margin, incremental sales, and investment.
NEW QUESTION # 63
What is the Dollar Sales per $MMACV for the Product Group in Store 478?
Answer: B
Explanation:
The correct answer is D .
Dollar Sales per $MMACV measures sales productivity normalized by store or market selling power. CPG Data Insights defines Sales per $MM ACV as a velocity measure calculated by dividing sales by the market's All Commodity Volume expressed in millions, and explains that it helps compare productivity across markets, retailers, or products with different distribution levels.
For Store 478 :
Product Group Actual Dollar Sales = $10,000
Store 478 ACV $ Sales = $2,000,000
ACV expressed in millions = $2,000,000 ÷ $1,000,000 = 2
Calculation:
$10,000 ÷ 2 = $5,000
So the Dollar Sales per $MMACV for the Product Group in Store 478 is $5,000 .
Option C, $4,000, is the total-store benchmark calculation: $400,000 ÷ 100 = $4,000. The question asks specifically for Store 478 , not the total store benchmark.
NEW QUESTION # 64
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