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Salesforce Marketing-Cloud-Advanced-Cross-Channel Exam Questions
Salesforce Marketing Cloud Advanced Cross Channel (Page 3 )

Updated On: 15-Feb-2026
Page 3 of 22
PDF with 101 Questions

How often is the model refreshed for Einstein engagement frequency(uses 2Sday& data)-weekly

  1. hourly
  2. daily
  3. monthly
  4. Biweekly

Answer(s): B

Explanation:

Model Refresh Frequency:
Einstein Engagement Frequency's predictive model needs to be updated regularly to reflect the most recent engagement patterns.
Daily Refresh:
The EEF model is refreshed daily. This ensures that the send frequency recommendations are based on relatively up-to-date data.
Why Not Other Options:
A . Hourly: Hourly refresh would be computationally intensive and unnecessary, as engagement patterns don't change that rapidly.
C . Monthly: Monthly refresh would be too infrequent, as the model's accuracy would degrade significantly over a month.
D . Biweekly: Biweekly is also too infrequent to keep the model aligned with recent engagement trends.
In Summary:
The Einstein Engagement Frequency model is refreshed B. Daily to maintain accuracy.



What does Einstein copy Insight take into account, Select 3(arul's answer a, b, c)

  1. Frequently used phrases in subject line
  2. spelling and punctuation errors
  3. emotional tone of subject line
  4. engagement data

Answer(s): A,C,D

Explanation:

Understanding Einstein Copy Insights:
Purpose: Einstein Copy Insights, a feature in Marketing Cloud, analyzes your subject lines to predict their performance and provide recommendations for improvement.
Correct Statements:
A . Frequently used phrases in subject line: Einstein Copy Insights identifies phrases that are commonly used in your subject lines and analyzes their historical performance. This helps you understand which phrases are effective and which might be overused. C . Emotional tone of subject line: The model assesses the emotional tone of your subject lines (e.g.,

positive, negative, neutral) and correlates it with engagement rates. This helps you craft subject lines that resonate with your audience.
D . Engagement data: This is fundamental to Einstein Copy Insights. The model analyzes historical engagement data (open rates, click-through rates) for your subject lines to identify patterns and make predictions.
Incorrect Statement:
B . Spelling and punctuation errors: While good spelling and punctuation are important for email deliverability and professionalism, Einstein Copy Insights doesn't specifically analyze or flag these errors. It focuses on the content and its impact on engagement.
In Summary:
Einstein Copy Insights analyzes frequently used phrases, the emotional tone of subject lines, and historical engagement data to predict subject line performance. A, C, and D are correct.



In which section can you define fatigue rules to restrict a user from being recommended same content multiple times

  1. Einstein content selection
  2. Einstein copy insights
  3. Einstein engagement scoring

Answer(s): A

Explanation:

Understanding Content Fatigue:
Content fatigue occurs when subscribers receive the same or very similar content repeatedly, leading to decreased engagement or even unsubscribes.
Einstein Content Selection and Fatigue Rules:
Einstein Content Selection is a feature that uses AI to personalize content for each subscriber at the time of send. It takes into account subscriber preferences, past behavior, and available content assets.
Fatigue Rules: Within Einstein Content Selection, you can define "fatigue rules" (also sometimes referred to as "exclusion rules"). These rules prevent the system from recommending the same content to a subscriber too frequently within a defined timeframe.
Why Other Options Are Incorrect:
B . Einstein Copy Insights: Focuses on analyzing subject line performance and providing recommendations, not on managing content fatigue.
C . Einstein Engagement Scoring: Predicts the likelihood of a subscriber engaging with emails (opening, clicking, unsubscribing). It doesn't directly control content selection or fatigue rules.



Select features Einstein content selection, Select 2

  1. Uses open time email content
  2. Content selection based on business rules

Answer(s): A,B

Explanation:

Einstein Content Selection Key Features:
A . Uses open time email content: This is a core aspect of Einstein Content Selection. It selects and inserts content into emails at the time the subscriber opens the email, rather than at the time of send. This allows for highly personalized and up-to-date content.

B . Content selection based on business rules: You can define business rules within Einstein Content Selection to control how content is selected. This includes things like:
Fallback Rules: Specifying default content to use if no personalized content is available. Exclusion/Fatigue Rules: Preventing certain content from being shown too frequently or to specific segments.
Attribute Matching Rules: Matching content assets to subscriber profiles based on attributes (e.g., showing women's clothing to subscribers identified as female).
Why A and B Are Correct:
Open-Time Personalization: Einstein Content Selection is designed for dynamic, open-time content personalization.
Business Rules Control: Business rules are essential for ensuring that Einstein Content Selection aligns with your marketing strategy and goals.



When are customers eligible to be send a message in STO(when customer will engage then its sent)

  1. immediately when the STO activity arrives
  2. Within the first minute of next hour.
  3. with the next hour
  4. At the hour user engages Within the next 24hours

Answer(s): D

Explanation:

Understanding Send Time Optimization (STO):
Purpose: STO is a Marketing Cloud feature that uses AI to determine the optimal time to send an email to each individual subscriber, maximizing the likelihood of engagement. How it Works: STO analyzes a subscriber's historical engagement data (when they typically open and click emails) to predict the best send time within a 24-hour window.
STO Send Time Logic:
Prediction Window: STO predicts the hour within the next 24 hours when a subscriber is most likely to engage.
Send at Predicted Hour: The email is sent during that predicted hour.

It's not immediate: STO doesn't send emails immediately upon entering the activity. It waits for the predicted optimal hour.
It's not within the first minute of the next hour: STO determines a specific hour, not just the start of the next hour.
It's not necessarily within the next hour: The predicted hour could be several hours away, depending on the subscriber's engagement history.






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