만약 시험만 응시하고 싶으시다면 우리의 최신Salesforce MC-Con-201자료로 시험 패스하실 수 있습니다. Pass4Test 의 학습가이드에는Salesforce MC-Con-201인증시험의 예상문제, 시험문제와 답 임으로 100% 시험을 패스할 수 있습니다.우리의Salesforce MC-Con-201시험자료로 충분한 시험준비하시는것이 좋을것 같습니다. 그리고 우리는 일년무료 업데이트를 제공합니다.
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Analytics & Performance Insights | 8% | - Reporting and analytics
|
| Topic 2: Agentforce & AI Innovation | 11% | - Predictive AI
|
| Topic 3: Data Modeling, Identity Resolution & Segmentation | 25% | - CRM data ingestion and activation
|
| Topic 4: Platform Setup & Governance | 13% | - Business Units and governance
|
| Topic 5: Campaign Design, Flow Orchestration & Content | 30% | - Messaging data sources
|
| Topic 6: Consent | 13% | - Consent record management
|
Salesforce인증MC-Con-201시험을 패스하여 자격증을 취득한다면 여러분의 미래에 많은 도움이 될 것입니다.Salesforce인증MC-Con-201시험자격증은 it업계에서도 아주 인지도가 높고 또한 알아주는 시험이며 자격증 하나로도 취직은 문제없다고 볼만큼 가치가 있는 자격증이죠.Salesforce인증MC-Con-201시험은 여러분이 it지식테스트시험입니다.
질문 # 101
Northern Trail Outfitters (NTO) wants to include a Last_Purchased_Date field from a Data Graph in a new marketing email. The date/time value is displayed as 2027-03-15T08:30:45 when previewing the email. NTO wants it to display as:
Monday, March 15, 2027 8:30 AM
Which approach should NTO use?
정답：C
설명：
Marketing Cloud Next supports Handlebars helpers for advanced email personalization and formatting.
Salesforce's Handlebars format helper can format date values using standard or custom date/time patterns and culture settings. For example, date-format tokens support full weekday names, full month names, day and year values, 12-hour time, minutes, and AM/PM indicators. That directly supports transforming an ISO-style value such as 2027-03-15T08:30:45 into a human-readable presentation such as Monday, March 15, 2027 8:
30 AM.
This is a presentation-layer requirement, so the transformation belongs in the content's personalization logic.
There is no need to alter the underlying Data Graph value. SOQL is a Salesforce query language and isn't the appropriate mechanism for formatting a Data Graph personalization value inside an email. Likewise, a Salesforce formula operator isn't the standard content-rendering solution for this scenario.
Therefore, A is the correct architectural approach and matches the answer keyed in the uploaded bank.
Study Guide Reference: Campaign Design, Flow Orchestration and Content # Email Content and Personalization # Data Graph personalization and Handlebars.
질문 # 102
A retailer is planning their first "New Product Promotion" email campaign in Marketing Cloud Next. Their marketing manager wants to send to everyone in the CRM database who has not explicitly asked to be removed.
What will happen when they launch the campaign?
정답：B
설명：
Marketing Cloud Next uses an explicit opt-in consent model for promotional marketing. Absence of an opt- out doesn't mean that an individual is eligible to receive marketing messages. Salesforce explicitly states that a Prospect, Lead, or Contact without a consent value is considered opted out by default for marketing channels and communication subscriptions.
Therefore, recipients must have valid affirmative consent associated with the appropriate contact point, channel, and communication subscription. If the "New Product Promotion" campaign uses its own communication subscription, customers who lack the necessary OPT_IN state are suppressed rather than treated as implicitly eligible.
Option A incorrectly assumes an opt-out-only consent model. Option C makes the same incorrect inference:
the absence of an OPT_OUT record isn't equivalent to affirmative permission.
This distinction is critical during initial implementation because existing CRM records aren't automatically opted in. Salesforce recommends importing or otherwise establishing valid consent before promotional messaging begins.
The source bank correctly identifies B. Salesforce's July 2026 documentation explicitly states that consent isn't default opt-in and that promotional messages are rejected when the recipient lacks an affirmative opt-in.
Study Guide Reference: Consent # Consent Validation # Explicit Opt-In and Default Consent Status.
질문 # 103
Northern Trail Outfitters (NTO) wants to send a monthly update email that includes the total number of items each customer has purchased to date, as well as that customer's favorite category. NTO wants to include fields such as 'Total Items' and 'Category Name' in the email, but these fields do not exist within the raw ecommerce order data, which is currently ingested and mapped in Data 360.
How should NTO resolve this issue?
정답：C
설명：
A Calculated Insight is designed for aggregations across multiple Data 360 records. The requested values aren't simple attributes stored on one ecommerce order. "Total Items" requires aggregation across the customer's purchase history, while "Favorite Category" requires grouping purchase activity by category and identifying the dominant result.
Salesforce Calculated Insights support aggregate metrics such as sums and counts together with dimensions that enable more granular analysis. Salesforce also supports calculated insight metrics in activations and downstream personalization scenarios.
A streaming insight is unnecessary because the campaign runs monthly and doesn't require second-by-second recalculation. Using a standard formula field as proposed in C also doesn't solve multi-record ecommerce aggregation: formula expressions aren't a substitute for analytical rollups across transaction history.
The uploaded source keys B. One wording issue exists in option B: it says "aggregate the purchase volume for the account," while the scenario ultimately requires values associated with each Unified Individual. The underlying architectural principle remains correct-use a Calculated Insight grouped appropriately to the customer/profile dimension.
Study Guide Reference: Data Modeling, Identity Resolution and Segmentation # Calculated Insights # Metrics, Dimensions, and Aggregations.
질문 # 104
A Marketing Cloud Next Consultant needs to suppress subscribers from an upcoming audience flow who have a low probability of opening or clicking email content.
Which Einstein feature should the consultant use?
정답：A
설명：
Einstein Engagement Scoring is designed to predict the likelihood that an individual subscriber will engage with future email communications. Salesforce states that the model predicts email opens and clicks, subscriber retention, web conversion, and overall engagement for individual consumer contacts.
Those predicted likelihood values can be used to identify customers with low engagement propensity. A marketer can therefore segment, filter, suppress, or branch customers according to their predicted open or click probability before an audience flow sends a message.
Send Time Optimization solves a different problem. STO assumes that a recipient is going to receive the communication and predicts when that person is most likely to engage. It doesn't primarily determine whether a low-propensity customer should be excluded. Messaging Insights isn't the predictive subscriber-level engagement scoring capability described in this requirement.
Salesforce also stores the output in the Email Engagement Score DMO , which supports reporting and audience analysis based on open, click, and subscription likelihood.
The uploaded master bank correctly keys A. Salesforce's current Einstein Engagement Scoring model card confirms that it predicts opens, clicks, retention, and overall engagement.
Study Guide Reference: Agentforce and AI Innovation # Einstein Engagement Scoring # Predictive Audience Optimization.
질문 # 105
Northern Trail Outfitters ingests customer records from its commerce and loyalty systems into Data 360. The records represent the same customer but have different source identifiers.
How does Identity Resolution determine that these records belong to the same Unified Individual?
정답：A
설명：
Match rules determine whether separate source profiles represent the same real-world individual. Data 360 Identity Resolution evaluates configured attributes and matching methods-such as normalized email, normalized phone, name, party identifiers, or device identifiers-to decide which Individual records should belong to the same Unified Individual.
Salesforce provides default and custom match rules. For example, default configurations can compare fuzzy first name, exact last name, and normalized email or telephone values. Multiple rules can coexist within an Identity Resolution ruleset.
Reconciliation rules serve a later and fundamentally different purpose. After records have been matched, reconciliation determines which values become representative unified-profile attributes-for example, whether CRM or loyalty should supply the preferred First Name. Therefore B confuses matching with attribute-value selection.
Identity Resolution also doesn't destructively merge the source records into one Individual record. Source profiles remain available and are linked through the resulting unified profile.
The uploaded master bank correctly identifies C.
Study Guide Reference: Data Modeling, Identity Resolution and Segmentation # Identity Resolution # Match Rules versus Reconciliation Rules.
질문 # 106
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Pass4Test에는 IT인증시험의 최신Salesforce MC-Con-201학습가이드가 있습니다. Pass4Test 는 여러분들이Salesforce MC-Con-201시험에서 패스하도록 도와드립니다. Salesforce MC-Con-201시험준비시간이 충분하지 않은 분은 덤프로 철저한 시험대비해보세요. 문제도 많지 않고 깔끔하게 문제와 답만으로 되어있어 가장 빠른 시간내에Salesforce MC-Con-201시험합격할수 있습니다.
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