JPTestKingがもっと早くSalesforceのMC-Con-201認証試験に合格させるサイトで、SalesforceのMC-Con-201「Salesforce Certified Marketing Cloud Next Consultant」認証試験についての問題集が市場にどんどん湧いてきます。JPTestKingを選択したら、成功をとりましょう。
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Analytics & Performance Insights | 8% | - Marketing data and insights
|
| Topic 2: Agentforce & AI Innovation | 11% | - Conversational messaging
|
| Topic 3: Data Modeling, Identity Resolution & Segmentation | 25% | - CRM data ingestion and activation
|
| Topic 4: Consent | 13% | - Consent management concepts
|
| Topic 5: Campaign Design, Flow Orchestration & Content | 30% | - Personalization
|
| Topic 6: Platform Setup & Governance | 13% | - Business Units and governance
|
煩わしいSalesforceのMC-Con-201試験問題で、悩んでいますか？悩むことはありません。JPTestKingが提供した問題と解答はIT領域のエリートたちが研究して、実践して開発されたものです。それは十年過ぎのIT認証経験を持っています。JPTestKingのSalesforceのMC-Con-201の試験問題と解答は当面の市場で最も徹底的な正確的な最新的な模擬テストです。
質問 # 94
Northern Trail Outfitters (NTO) is investigating reports that promotional emails are being delivered to individuals who have previously opted out earlier the same day. NTO discovers that customer consent preferences are updated daily using a batch data transform that writes directly to the Communication Subscription Consent data model object (DMO), causing customer complaints.
Which action should the Marketing Cloud Next Consultant take to resolve it?
正解：A
解説：
The problem isn't merely the batch schedule; the implementation is using an unsupported consent-write path
. Salesforce's August 2026 Marketing Cloud Next guidance explicitly warns against using Data 360 batch transforms, streaming transformations, direct data-stream mappings, or bulk APIs to write directly into the Communication Subscription Consent DMO. Those methods can produce consent values that appear stored but aren't consistently honored by the messaging consent layer at send time.
The supported solution is to route the change through Create Consent/Consent Request . A Data 360- triggered flow can listen for the relevant change and invoke Create Consent, which updates the contact point's consent for the required channel and communication subscription through the supported consent service.
Therefore, changing a daily batch to hourly doesn't fix the architectural defect. Switching from batch to streaming transformation also doesn't make a direct DMO write supported.
The master bank correctly identifies B. Salesforce explicitly recommends reissuing incorrectly written consent through a Data 360-triggered flow calling Create Consent.
Study Guide Reference: Consent # Supported Consent Write Methods # Create Consent Action and Data
360-Triggered Flows.
質問 # 95
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?
正解：B
解説：
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.
質問 # 96
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?
正解：B
解説：
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.
質問 # 97
Northern Trail Outfitters wants to enrich its customer profiles by combining CRM Contact data with anonymous web browsing activity captured via the web tracking embed code. A Marketing Cloud Next Consultant has already set up the Contact data stream mapped to the Individual data model object (DMO) and confirmed that web tracking events are flowing into the Website Engagement DMO.
What must the consultant configure in Identity Resolution to link anonymous visitor data to known Contact profiles?
正解：A
解説：
Salesforce provides the Device to Known Identity Resolution rule specifically to associate anonymous tracked visitors with known Unified Individual profiles.
Current Marketing Cloud Next setup documentation states that an Individual Identity Resolution ruleset should include an Identity Match DMO match criterion where Identity Match Type is matched exactly to device-to-known. Salesforce explains that this recommended rule attributes web-tracking activity to the correct Unified Individual.
This architecture exists because anonymous website engagement initially contains a device or visitor identity rather than ordinary CRM identity attributes. Once the visitor becomes identifiable-for example, through a recognized interaction-the Identity Match relationship enables Data 360 to stitch that visitor identity to the known Individual.
Option A incorrectly proposes manually altering identity relationships with Flow. Option B assumes Website Engagement should be directly matched to Individual using email, which bypasses the specialized identity- stitching mechanism Salesforce provides.
The uploaded master bank identifies C.
Study Guide Reference: Data Modeling, Identity Resolution and Segmentation # Identity Resolution # Identity Match DMO and Device-to-Known Matching.
質問 # 98
Northern Trail Outfitters (NTO) runs a weekly promotional newsletter. NTO's Marketing Cloud Next Consultant has configured a record-triggered flow on the Lead object in Salesforce that fires when a lead clicks a specific product link in an email. The flow is meant to automatically opt the lead in to a product subscription using the Create Consent action, but the consent record consistently fails to create.
What should the consultant configure instead?
正解：B
解説：
The uploaded bank keys C , which places the automation at the layer where the actual email-click engagement exists: Data 360 engagement data.
Current Salesforce documentation supports the core architecture. Create Consent is supported in Data Cloud
/Data 360-triggered flows and can be used to automate consent updates based on behavioral data such as a link click . Salesforce explicitly describes link clicks and form submissions as valid sources for automated Create Consent processing.
The original CRM Lead record doesn't itself become updated merely because an email engagement event occurred, so a conventional Lead record-triggered flow is an unreliable trigger for this behavior. A Data 360- triggered flow can instead react to the appropriate engagement DMO event and pass the relevant sending contact point into Create Consent.
The source specifically identifies the Email Engagement DMO, click criteria, link URL, and Send time Email Address fields. Those exact field-level details are source-derived; current public Salesforce documentation independently confirms the broader Data 360-triggered + Create Consent pattern.
Study Guide Reference: Consent # Behavioral Consent Automation # Data 360-Triggered Flow and Create Consent.
質問 # 99
......
多くの受験者にとって、MC-Con-201試験資格証明書を取得することは簡単ではないです。MC-Con-201試験に合格するには、たくさん時間と精力が必要です。しかし、Salesforce MC-Con-201試験参考書を選ばれば、試験に合格するだけでなく、時間を節約できます。だから、Salesforce MC-Con-201試験参考書を早く購入しましょう！
MC-Con-201受験準備: https://www.jptestking.com/MC-Con-201-exam.html