Marketing-Cloud-Email-Specialist Practice Test Questions

Explanation:

Datorama dashboards can be organized into multiple pages—presented as tabs within the Intelligence Reports interface—so users can switch between high-level and detailed views (for example, Email Overview, Deliveries, Engagement, and Performance) without leaving the same dashboard canvas. Using tabs groups related metrics logically and reduces clutter, improving navigation and usability. While “Campaigns” and “Sender Profile” are valuable filter dimensions for slicing data, they don’t change the dashboard layout. Only the tabs feature lets you structure your visualizations into separate, easily accessible pages, making it faster for stakeholders to find the insights they need.

Explanation:

The correct answer is B because bounced contacts from previous sends are excluded from future sends by default, unless they are reactivated. DoNotTrack preferences only affect tracking data, not sending. Suppressed contacts from contact deletion are not relevant because the data extension contains the audience for the send.

Explanation:

File transfer is the activity that is missing from the automation. File transfer is used to move files from one location to another, such as from Marketing Cloud to an SFTP server. Without this activity, the data extract will create a .csv file in Marketing Cloud, but it will not send it to the SFTP server. Fire event is used to trigger a journey or an automation from another automation. Import file is used to import data from a file into a data extension.

Explanation:

Automation Studio and Journey Builder can be used to accommodate this request. Automation Studio can be used to create an automation that runs daily and injects new records from the data extension into a journey. Journey Builder can be used to create a journey that sends a customized ‘congratulations’ email immediately after entry, and then waits for 14 days before sending a review request email. Journey Builder and Behavioral Triggers would not work because behavioral triggers are based on web or mobile app activity, not purchase data. Automation Studio and Path Optimizer would not work because path optimizer is used to test different paths within a journey, not different product recommendations.

Explanation:

Adding each send email activity to different steps in an automation ensures that each email is fully sent before the next email begins sending. The automation will wait for the completion of each step before moving on to the next one. Including a verification activity between each step is unnecessary and may cause errors. Adding each send email activity to a single step in an automation will send all emails at the same time.

Explanation:

If you want to ensure the exclusion is updated before the audience query runs, you should place the audience SQL Query Activity in a step after the exclusion SQL Query Activity. This way, the exclusion query will run first and update the data extension with the subscribers who should be excluded from the send. Then, the audience query will run and pull the subscribers who meet the criteria for the send, excluding those who were filtered out by the previous query. Placing a wait step between them or placing them in the same step will not guarantee that they will run in the correct order. You can learn more about this in the [Automation Studio Basics] module on Trailhead.

Explanation:

Configuring the Journey Entry Event to ‘allow no re-entry’ will ensure that subscribers who have made recent purchases will only receive a thank you email the first time they show up in the file drop. This will prevent them from receiving duplicate emails if they make multiple purchases.

Explanation:

Data Views in Marketing Cloud store historical engagement data (opens, clicks, bounces, etc.) for up to 6 months (or longer if archived). By writing an SQL Query against these Data Views (e.g., _Open, _Click), NTO can compare year-over-year engagement metrics.

Why Not the Others?

B. Audit Trail Extract: Tracks user/admin actions (e.g., logins, edits) but not subscriber engagement.

C. Tracking Data Extract: Provides raw data exports but requires manual setup and lacks the flexibility of SQL for analysis.

Explanation:

Based on Subscriber Preview List or Data Extension is a Preview & Test Content Personalization option that allows marketers to preview how an email will look for different subscribers based on their personalization attributes and dynamic content rules. Marketers can select a list or data extension that contains the subscribers they want to preview, and then use the arrows or search function to navigate through the different previews.

Explanation:

Multi-Step journeys in Journey Builder let you design complex flows—including randomized splits or Path Optimizer A/B tests—to compare two recommendation strategies. You can inject Einstein Recommendations in one branch and static content in another, then automatically measure conversion metrics side-by-side. Once a winner emerges, you simply remove the losing path and continue using the more effective branch for all future return-confirmation sends. Single Send and Transactional Send journeys don’t support built-in A/B or multivariate testing within the canvas, so they can’t automate evaluating and choosing a winning option.

Reference:

Experiment with Your Customer Journeys (Path Optimizer)