成功した方法を見つけるだけで、失敗の言い訳をしないでください。CMAのCategory-Manager試験に受かるのは実際にそんなに難しいことではないです。大切なのはあなたがどんな方法を使うかということです。Fast2testのCMAのCategory-Manager試験トレーニング資料はよい選択で、あなたが首尾よく試験に合格することを助けられます。これも成功へのショートカットです。誰もが成功する可能性があって、大切なのは選択することです。
| Section | Objectives |
|---|---|
| Topic 1: Data and Analytics | - Retail and shopper data analysis
|
| Topic 2: Shopper and Retail Insights | - Behavioral and shopper analytics
|
| Topic 3: Execution and Business Planning | - Category execution and collaboration
|
| Topic 4: Category Management Foundations | - Category management principles and framework
|
| Topic 5: Category Strategy Development | - Strategic category planning
|
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質問 # 69
Which phase of analytics uses past data and models to estimate what's likely to happen next?
正解：C
解説：
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.
質問 # 70
What does ROI analysis measure?
正解：B
解説：
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.
質問 # 71
There are 4 chains in the Market, What is the ACV Weighted Distribution for Item A within that Market?
Chain A: Distribution of Item A = Yes, Total Store ACV = $1,000,000
Chain B: Distribution of Item A = No, Total Store ACV = $2,000,000
Chain C: Distribution of Item A = Yes, Total Store ACV = $2,000,000
Chain D: Distribution of Item A = Yes, Total Store ACV = $1,000,000
正解：D
解説：
The correct answer is A .
The CPCM POS Data course covers retail and third-party scanned sales data and introduces key POS measures and definitions, including distribution-related analysis. ACV Weighted Distribution is calculated by dividing the ACV of stores carrying the product by the total ACV of all stores in the market; Circana defines Percent ACV Distribution the same way, as weighted distribution based on the total sales volume of carrying stores compared with all possible stores.
For Item A, the chains carrying the item are:
Chain A = $1,000,000
Chain C = $2,000,000
Chain D = $1,000,000
Total ACV where Item A is distributed = $4,000,000
Total Market ACV = $1,000,000 + $2,000,000 + $2,000,000 + $1,000,000 = $6,000,000 Calculation:
$4,000,000 ÷ $6,000,000 = 66.7%, rounded to 67%
Option D, 75%, is the unweighted numeric distribution because Item A is in 3 of 4 chains. That ignores ACV size, so it is not ACV Weighted Distribution. Option B and C are dollar values, not percentages.
質問 # 72
Using the chart, what is the most complete insight for Mid-Mart regarding the Snack Category?
正解：D
解説：
The correct answer is A .
The CPCM course emphasizes turning data into insights and then into action. It states that category managers must draw insights from data, understand tactical analysis, and identify category opportunities that can be acted on through category tactics. This question is testing exactly that: not just calculating the gap, but identifying the gap, the source of the gap, and the dollar opportunity.
From the chart:
Mid-Mart ACV share = 25.0%
Mid-Mart Snack share = 20.0%
So Mid-Mart is:
25.0% - 20.0% = 5.0 points behind Total Store
The total Snack market is $200,000 . If Mid-Mart achieved its fair share of Snacks based on its 25% Total Store ACV share, expected Snack sales would be:
$200,000 × 25% = $50,000
Actual Mid-Mart Snack sales are:
$40,000
So the opportunity is:
$50,000 - $40,000 = $10,000
The driver is the Club Channel , because Club has 25% ACV share but 30% Snack share. Club is 5 points over fair share, while AO Grocery is exactly aligned at 50% ACV share and 50% Snack share. Therefore, the most complete insight is that Mid-Mart is 5.0 points behind Total Store, the gap is driven by the Club Channel, and the opportunity is $10,000.
質問 # 73
What is the best data source to understand how a Retailer is performing in a Category versus their competitors in the market?
正解：B
解説：
The correct answer is D .
The CPCM course identifies Building Data Competency: POS Data as part of the CPCM curriculum and explains that POS data includes retailer and third-party scanned sales data, with trends, sales, profitability, distribution, and shopper insights reviewed in the context of retail POS data.
The phrase "versus their competitors in the market" is the key. A retailer's own POS data shows that retailer's internal sales, but it does not show how competing retailers are performing. Syndicated POS Data aggregates scanned sales across the broader market, so it is the correct source for comparing retailer category performance against competitors.
Option A is wrong because Retailer POS Data is limited to one retailer's own sales. Option B is wrong because Retailer Loyalty Data explains known shopper behavior within that retailer, not market-level competitor performance. Option C is wrong because Syndicated Panel Data is stronger for household/shopper behavior, not scanned sales comparison across retailers.
質問 # 74
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