Marketing-Cloud-Account-Engagement-Consultant Practice Test Questions

Explanation:

In the Advanced section of the “Look and Feel” step when configuring a form in Marketing Cloud Account Engagement (MCAE), you can enable Kiosk/Data Entry Mode, which ensures that the browser is not cookied as the submitted prospect. This is particularly useful in scenarios like trade shows, events, or shared devices where multiple people may fill out the form from the same browser. By enabling this mode, MCAE prevents overwriting or merging prospect records due to cookie tracking, ensuring that each submission is treated as a distinct prospect.
Example:
LenoxSoft is collecting lead data at a conference using a tablet. If Kiosk Mode is not enabled, the first prospect who fills out the form will be cookied, and subsequent submissions may overwrite or associate with that original prospect. Enabling Kiosk Mode ensures each submission is clean and separate.

❌ Why the Other Options Are Incorrect:

B. PI Enable explicit bot protecting using reCAPTCHA
This feature is configured in the form settings, not specifically in the “Look and Feel” > Advanced section. MCAE uses Honeypot bot protection by default, and reCAPTCHA is an optional enhancement configured elsewhere.
C. Include "Not you?" link to allow visitors to reset the form
This option is available in the form behavior settings, not in the Advanced section of Look and Feel. It’s used to allow users to reset prefilled form data if they’re not the identified prospect.
D. Disable autoresponder emails on this form
Autoresponder emails are managed in the Completion Actions step of the form setup, not in the Look and Feel section. You can choose whether or not to send autoresponders based on form submissions there.

References:
Marketing Cloud Account Engagement Forms Overview
Kiosk Mode in MCAE Forms
Form Completion Actions

Explanation:

When you open the Pipeline Dashboard in B2B Marketing Analytics, it has built-in filters (for example Year, Quarter, Opportunity Stage, etc.) that let you slice the data shown in the dashboard by time periods, including fiscal years.
Because those filters are already part of the dashboard, you can simply select the relevant fiscal year to show only opportunities whose close dates fall within that fiscal year. This method doesn’t require rebuilding datasets or creating custom lenses—it leverages existing dashboard functionality.
For example:
Suppose LenoxSoft’s fiscal year runs from October to September. The CMO or analyst opens the Pipeline Dashboard, selects the fiscal year “FY 2025” in the Year filter. All widgets (pipeline value, open opportunities, won opportunities, funnel stages) now reflect only opportunities whose close date lies between October 2024 and September 2025.
This approach is efficient, dynamic, and preserves all the dashboard behavior (drilling, comparing periods, etc.) without extra manual work.
⚠️ Other Options (and why they’re less optimal or incorrect)
Let me go through the alternatives and compare them with the correct approach:

A. Develop a new lens that includes only data from the fiscal year
You could build a custom lens that filters the underlying opportunity dataset to only that fiscal year’s data. Then you could use that lens on a dashboard or embed it in a custom dashboard. However:
You’d have to maintain it manually each year (create a new lens or update filters).
You lose the benefit of using the standard out-of-the-box dashboard with all its widgets and built-in logic.
It’s more labor-intensive and yes, more prone to divergence from the standard datasets and calculations.
In many cases, it’s a valid fallback if your fiscal year is nonstandard and the standard dashboard filters don’t support exactly what you need—but it’s not the recommended first approach when the dashboard already supports year/quarter filters.

C. Create a custom dataset using only data from the fiscal year
Building a dataset that only includes opportunities from a given fiscal year means:
You’d need to configure dataflows or recipes to filter at ingestion (or create a derived dataset).
Each year you’d need to build or update a new dataset (unless you build logic into the dataflow to dynamically filter by the current fiscal year).
You lose the continuity of the standard dataset (you might miss other opportunities or historical comparison data).
This is a heavy technical lift for what is a simpler use case. Only do this if your reporting needs are so bespoke that default filters won’t suffice.

D. Apply the “tag” filter on the Pipeline Dashboard using the fiscal year
Tags in B2BMA or Pardot are generally user-generated labels applied to assets or prospects (e.g. “Q4ProductLaunch2025”). They’re not typically used to label opportunities by fiscal year. There’s no automatic or system behavior that tags opportunities by fiscal year out of the box, so this option is unrealistic for LenoxSoft’s use case. Also, the Pipeline Dashboard doesn’t inherently include a tag dimension for opportunities as a built-in, reliable filter the way date and year filters are provided.
You would have to manually tag every opportunity by fiscal year and maintain those tags, which is error prone and doesn’t scale.

📝 Summary & Recommendation
The fiscal year filter on the Pipeline Dashboard is your simplest, most maintainable, and intended method to view only the opportunities for that fiscal year.
Use lenses or custom datasets only when your needs exceed what built-in filters support (for example, nonstandard or shifting fiscal periods or special projections).
Tagging is not a practical or scalable solution for period-based filtering.

📚 References
Trailhead: Standard Dashboards in B2B Marketing Analytics — mentions that dashboards come with Year and Quarter filters.
Salesforce Help: B2B Marketing Analytics Dashboards — describes the Pipeline dashboard and its filtering features.
Salesforce B2B Marketing Analytics Implementation Guide — best practices for filtering dashboards by date (recommend using “relative date mode”).
Dashboard Filter Examples (Analytics) — general concept of using dashboard filters to change perspective.

Explanation:

Concept Identification: This question tests your knowledge of the Prospect Resubscribe feature, which is the compliant and standard method for handling potential accidental unsubscribes.

Why This Answer is Correct:
The prospect resubscribe feature is designed for exactly this scenario. When enabled, it adds a one-click resubscribe link to the footer of automated and one-to-one emails (like form confirmation emails) that the prospect will still receive even after unsubscribing.
If a prospect unsubscribed by mistake, they will still receive these transactional-type emails. When they see the resubscribe link, they can easily click it to opt back into marketing communications. This puts the power and intent confirmation directly in the hands of the prospect, which is a best practice.
"Setting up a template" refers to configuring the wording of this resubscribe link and message in the Admin > Prospect Settings area.

Why the Other Answers are Incorrect:
A. Opting out a prospect is irreversible... This is factually incorrect. While you should never manually opt a prospect back in, the platform provides a built-in, compliant mechanism (the resubscribe feature) to allow prospects to reverse their own decision.
B. Opt prospects back in only if they have interacted with other marketing content... This would be a violation of compliance laws (like CAN-SPAM and GDPR). Automatically opting someone back in based on a score or activity without their explicit consent is considered spamming. The prospect must take a positive action to resubscribe.
C. Create a completion action to assign a task to the Assigned User to make a phone call... While this might seem proactive, it is not scalable and is an intrusive use of sales resources. It also does not address the core issue through a standardized, automated marketing process. A phone call from sales after an unsubscribe could be perceived as harassment.

Key Takeaway:
The Prospect Resubscribe feature is the cornerstone of compliant list hygiene management. It respects the prospect's original unsubscribe decision while providing a clear, low-friction path for them to correct a mistake. This is enabled in Account Engagement > Admin > Prospect Settings.

Explanation:

✅ A. You can define a page to be a priority page to highlight the activity to Sales reps and other users.
This is true. In Marketing Cloud Account Engagement (MCAE), Page Actions allow you to mark specific pages as priority pages. When a prospect visits a priority page, their activity is highlighted in their record and can trigger alerts or notifications to assigned users. This helps sales reps identify high-intent behavior, such as visiting pricing or demo request pages.
Example:
LenoxSoft marks their “Pricing” and “Contact Sales” pages as priority. When a prospect visits these pages, the assigned sales rep receives an alert, enabling timely follow-up.

✅ B. It is possible to use URL wildcard by adding * to the end of the URL.
This is true. MCAE supports wildcard matching in Page Actions using an asterisk * at the end of a URL. This allows you to apply the same Page Action to multiple pages with similar URLs.
Example:
LenoxSoft wants to track visits to any blog post. They set a Page Action for www.lenoxsoft.com/blog/*, which matches all URLs under the blog directory, such as www.lenoxsoft.com/blog/post1 or www.lenoxsoft.com/blog/2025-trends.

❌ C. You cannot use auto responder emails with page actions.
This is false. While Page Actions themselves do not directly trigger autoresponder emails (which are typically tied to forms), you can use Completion Actions or Automation Rules triggered by Page Actions to send emails. So while not native to Page Actions, autoresponders can be indirectly triggered.

✅ D. You cannot set the prospect's source campaign with page actions.
This is true. Page Actions cannot assign or change the source campaign of a prospect. The source campaign is typically set via form submissions, imports, or API integrations. Page Actions are used for tracking and triggering actions based on page visits, not for campaign attribution.

References:
Salesforce Help: Page Actions Overview
Salesforce Trailhead: Automate with Page Actions

Explanation:

When you place Engagement History metric fields (e.g., Email Clicks, Form Submissions, File Downloads) on the Salesforce Campaign layout, those numbers populate only for Connected Campaigns—that is, campaigns that are linked to Account Engagement (Pardot) via Connected Campaigns with Engagement History enabled. If the campaign isn’t connected, Salesforce has no relationship to the underlying Account Engagement assets and activity, so the roll-up fields have nothing to aggregate and will show 0 across the board.
For example, if “LenoxSoft – Spring Launch” is a standard Salesforce Campaign that was never connected to its corresponding Account Engagement campaign, even if prospects clicked emails and submitted forms tied to that AE campaign, the Salesforce Campaign’s Engagement History metric fields will remain 0. As soon as you use (or migrate to) Connected Campaigns and the AE assets are associated properly, the Engagement History metrics begin to reflect real activity.

Why the others are not correct (with examples):

B. Missing AE permission set — Permission sets affect who can view Engagement History components and related records, not whether the metrics exist. If users lacked the right permission set, they might not see the Engagement History component or related list entries, but fields wouldn’t be forced to show “0”; they’d still be populated on the record for users with access.

C. Engagement happened before the fields were added — Engagement History metrics are calculated from stored activity data and populate retroactively once the fields are on the layout (provided the campaign is connected). Adding the fields later doesn’t erase historical engagement.

D. Not refreshed in 24 hours — Engagement History and Connected Campaigns updates are near real time (subject to standard sync cycles), and there is no fixed “24-hour refresh” gate that would cause every metric to display “0.” A blanket 0 across all metrics is almost always a sign the campaign isn’t connected (or assets aren’t associated), not a temporary refresh delay.

References:
Salesforce Help: Connected Campaigns overview and requirements (and how activity rolls up to Campaigns)
Salesforce Help: Engagement History on Salesforce Campaigns (metrics, components, and visibility)
Salesforce Help: Add Engagement History Metrics to Page Layouts

Explanation:

When implementing Marketing Cloud Account Engagement (Pardot) for the first time, the essential setup steps focus on establishing the connection between your website, email sending infrastructure, and the Account Engagement platform.

The three essential setup components are:

A. Create and add a tracking code to the website
This is necessary for tracking visitor and prospect activities (page views) on your website, which is fundamental to how Account Engagement works.

B. Setup DNS for each used domain and validate the connection
This refers to setting up the necessary DNS entries (like SPF and DKIM) for your email sending domain. This is crucial for email deliverability and ensures your emails pass authentication checks, preventing them from being marked as spam.

C. Setup tracker subdomain and validate it
This is required to brand and host your Account Engagement marketing assets (like landing pages, forms, and files) and to rewrite trackable links in your emails. Setting up a tracker subdomain (e.g., go.lenoxsoft.com) and validating it with a CNAME record in your DNS is a foundational step for tracking and for displaying branded URLs.

Why Option D is Not Essential

D. Choose which sender IP to use
This is typically handled by Salesforce/Marketing Cloud Account Engagement. You will generally use a shared or dedicated IP address provided by them. While IP warming and management are important for deliverability, the choice of which shared/dedicated IP to use is often not a required step during the initial, foundational setup process for a new implementation, unlike the immediate requirement to establish domain-level DNS authentication (B) and tracking (A and C).

Explanation:

This is the correct and only viable solution that meets all the stated requirements within the platform's constraints. Let's break down why it works perfectly:

Handles the Form Restriction:
The scenario states that prospects are created via the Salesforce connector, not a Pardot form handler. This means when a Lead/Contact is created in Salesforce (from their existing form), it syncs over to Account Engagement. The Campaign field for these prospects will be set to "Salesforce Connector" because that was the mechanism of their creation. This Dynamic List correctly uses this field as the first criteria.
Manages Engagement Program Membership Dynamically:
The core requirement is to add prospects to an Engagement Studio program and remove them automatically when their score reaches 100. Engagement Studio programs can use Dynamic Lists as their entry audience. A Dynamic List is a "living" audience; it constantly re-evaluates its members. A prospect who matches the criteria (Campaign = Salesforce Connector AND Score < 100) is in the list (and thus, in the program). The moment their score hits 100, they instantly and automatically fail the criteria and are removed from the list, which also removes them from the Engagement Studio program, stopping all future emails. This satisfies the "remain until they reach a score of 100" requirement perfectly.
Correct Logic:
The criteria Prospect Score is less than 100 is the exact logic needed to keep prospects in the nurturing program until they become sales-ready (score >= 100).
Example:
A lead named "Jane Doe" submits Lenoxsoft's existing web form. A Lead is created in Salesforce.
The Salesforce connector syncs this Lead to Account Engagement, creating a prospect with Campaign = Salesforce Connector and Score = 0.
Jane automatically enters the "New Lead" Engagement Studio program because she matches the Dynamic List criteria.
She receives the first email, clicks it (earning 10 points), and downloads a whitepaper (earning 25 points). Her score is now 35. She remains in the program.
Later, she views the pricing page (a priority page, earning 50 points), bringing her score to 85. She still remains.
Finally, she requests a demo (earning 20 points), pushing her score to 105.
The moment her score updates to 105, she instantly and automatically fails the Dynamic List criteria (Score < 100) and is removed from the list. The Engagement Studio program stops sending her emails, as intended.
Reference:
This is a standard automation pattern in Account Engagement: Using a Dynamic List as a "gatekeeper" for an Engagement Studio program. Salesforce Trailhead and implementation guides recommend this method for creating dynamic, behavior-based nurturing streams.

Incorrect Answers and Detailed Explanations

B. Build a Segmentation rule :: Prospect Campaign is :: Salesforce Connector and Prospect Score :: is more than :: 100, Action :: add to list
This logic is completely backwards. It would build a list of prospects who are already highly qualified (score > 100). The goal is to nurture prospects until they reach that point. Adding them to a list after they are qualified makes no sense for the "New Lead" nurturing program. Furthermore, "Segmentation Rule" is a term for building Dynamic Lists, but the flawed criteria render this option useless for the stated goal.

C. Build an Automation rule :: Prospect Created Date ago is :: 100 :: and prospect score:: is less than :: 10, Action :: add to list
This is incorrect for several reasons. First, the criteria are nonsensical and do not align with the requirements (Created Date ago is 100 is unclear and score less than 10 is too low). More importantly, Automation Rules are the wrong tool for managing Engagement Studio membership. An Automation Rule with an "add to list" action is a one-time, bulk operation. It would add prospects who match the criteria at the moment the rule runs, but it would not remove them when their score changes. They would be stuck in the list and the program forever, violating the key requirement to stop emails at a score of 100.

D. Build an Automation rule :: Prospect Campaign is :: Salesforce is:: Salesforce Connector and prospect score :: is less than :: 100, Action :: add to list
While the criteria in this option are correct, the tool is wrong, just as in option C. Using an Automation Rule to add prospects to a static list for an Engagement Program creates a "set-it-and-forget-it" audience. Anyone added would remain in the program indefinitely, regardless of whether their score later exceeded 100. This would result in over-emailing and a poor prospect experience, directly violating the requirement to remove them upon reaching a score of 100. The dynamic addition and removal is only possible with a Dynamic List.

Summary and Key Takeaway
The critical distinction tested here is between static automation (Automation Rules that perform one-time actions on a set of records) and dynamic automation (Dynamic Lists that constantly update their membership based on changing field values).
For any Engagement Studio program where membership should be contingent on a prospect's changing data (like a score, grade, or custom field), the only correct approach is to use a Dynamic List as the program's entry audience. This ensures the system automatically manages who is actively being nurtured in real-time, providing a responsive and intelligent marketing automation flow.

Explanation:

LenoxSoft’s Marketing Cloud Account Engagement (Pardot) administrator has created scoring categories to track prospect engagement separately for each product line (e.g., Scoring Category A for Folder A assets, Scoring Category B for Folder B assets). The goal is to ensure the sales team can view these category-specific scores for each lead or contact in Salesforce. Scoring categories are custom fields in Account Engagement that sync to Salesforce as read-only fields on Lead and Contact records, but they require specific setup to be visible. Let’s evaluate the options:

A. Replace the Score field with Category Score fields on lead and contact page layouts in Salesforce: Incorrect.
The standard Score field (total prospect score across all categories) is a core metric synced from Account Engagement to Salesforce (pi__score__c). Replacing it with category score fields (e.g., pi__category_A_score__c) would remove visibility into the overall score, which is typically valuable for sales. Instead, category scores should be added alongside the standard score to provide both total and product-specific insights.

B. Share both Folder A and Folder B with the sales users' records in Marketing Cloud Account Engagement: Incorrect.
Folders in Account Engagement organize assets (e.g., emails, forms) and can be shared with users to control access within Pardot. However, folder sharing doesn’t affect Salesforce visibility or sync category scores to Lead/Contact records. Sales users primarily work in Salesforce, not Pardot, and need scores on page layouts, not folder access.

C. Add the Marketing Cloud Account Engagement Category Score related list to the lead and contact page layouts in Salesforce: Correct.
When scoring categories are created in Account Engagement (Admin > Scoring Categories), they generate corresponding fields in Salesforce (e.g., pi__category_A_score__c, pi__category_B_score__c) for each Lead and Contact. These fields are grouped in a Category Scores related list in Salesforce, which displays all category-specific scores for a record. To make these visible:
Go to Setup > Object Manager > Lead/Contact > Page Layouts.
Edit the page layout and add the Category Scores related list (automatically created by the Account Engagement AppExchange package).
Save and assign the layout to sales user profiles.
This ensures sales can see category scores (e.g., Product A score, Product B score) alongside other engagement data without modifying the standard Score field.

D. Assign the Marketing Cloud Account Engagement Category Scoring permission set to the sales user's profile in Salesforce: Incorrect.
There is no specific “Category Scoring permission set” in Account Engagement or Salesforce. The standard Account Engagement User or Marketing User permission sets grant access to Pardot features or Marketing App setup, but category scores are synced as standard Salesforce fields (pi__*) visible to any user with access to the Lead/Contact object and page layout. No additional permission set is needed for visibility.

Why C?
The Category Scores related list is the native Salesforce mechanism to display scoring category data synced from Account Engagement. It:
Shows all category scores (e.g., Category A, Category B) for each Lead/Contact.
Is read-only, ensuring sales can view but not edit scores.
Integrates seamlessly with the Account Engagement AppExchange package, which must already be installed for scoring categories to sync.
Requires minimal setup (just adding the related list), making it efficient for LenoxSoft.

Implementation Steps:

Verify Scoring Categories:
In Account Engagement: Admin > Scoring Categories > Confirm Category A and Category B are set up and tied to Folder A and Folder B assets.
Ensure the Salesforce Connector is active (Admin > Connectors > Salesforce) to sync category scores.

Add Related List:
In Salesforce: Setup > Object Manager > Lead > Page Layouts > Edit the sales team’s layout.
Add the Category Scores related list (under Related Lists section).
Repeat for Contact object.

Test Visibility:
Engage a test prospect with Folder A and B assets (e.g., open an email, visit a landing page).
Check the Lead/Contact record in Salesforce to confirm Category A and B scores appear in the related list.

Train Sales:
Show sales how to interpret category scores (e.g., Category A score = 50 means engagement with Product A assets) alongside total score.

Additional Notes:
Folder Setup: Ensure assets in Folder A and B are correctly tagged with their respective scoring categories in Account Engagement (e.g., email settings > Scoring Category).
Sync Timing: Scores sync in near real-time but may take a few minutes. If scores remain “0,” verify asset-to-category mapping and connector sync.
Alternative: If sales prefers inline fields over a related list, add individual category score fields (pi__category_A_score__c) to the page layout, but the related list is more compact for multiple categories.

References:
Salesforce Help: “Scoring Categories in Account Engagement” (Winter ’26) – Details how category scores sync to Salesforce and appear in the Category Scores related list on Lead/Contact layouts.
Salesforce Trailhead: “Account Engagement and Salesforce Integration” – Explains syncing custom metrics like category scores and adding them to page layouts for sales visibility.

Explanation:

When you import prospects into Marketing Cloud Account Engagement (MCAE) and need each new prospect to attach to a specific Salesforce Lead or Contact—especially when your Salesforce org has duplicates with the same email and your MCAE account allows multiple prospects per email—the only reliable disambiguator is the Salesforce CRM ID of the exact Lead or Contact you want. During import, choosing Match records by CRM ID lets MCAE create (or update) the prospect and explicitly link it to that Lead/Contact record, avoiding the ambiguity that comes with email-based matching in duplicate scenarios.
Example: Suppose you have two Salesforce Leads with the same email alex@acme.com:
Lead A (CRM ID: 00Qxx0000001AAA) – belongs to the US sales team
Lead B (CRM ID: 00Qxx0000001BBB) – belongs to the EMEA sales team
Your CSV includes two rows for alex@acme.com—one meant for the US team and one for EMEA. By populating a column with the correct CRM ID for each row and choosing Match by CRM ID, MCAE will create two separate prospects (since your account allows multiple prospects per email) and link each to the intended Salesforce Lead (A or B). This preserves ownership, campaigns, and sync behavior exactly as desired.

Why the other options fall short

B. Match records by Account ID
Account IDs refer to Account records, not Leads/Contacts. Matching on Account won’t attach the prospect to a specific Lead/Contact, which is what you need here.

C. Match records by fuzzy match rules
MCAE imports don’t use “fuzzy” matching for prospect-to-Lead/Contact linking. That’s not a supported import match method and wouldn’t solve the duplicate-email disambiguation problem.

D. Match records by email address
With duplicate Leads/Contacts sharing the same email—and with MCAE allowing multiple prospects per email—email matching is ambiguous. MCAE can’t know which Lead/Contact to link to; you risk incorrect associations or missed links.

References (Salesforce)
Import Prospects – supported match methods and how to use CRM ID during import
Allow Multiple Prospects with the Same Email Address – behavior and implications for matching

Explanation:

This is the correct and most robust solution. The requirement has two distinct criteria that must be true simultaneously: 1) Form Submission, and 2) Specific State value. A Completion Action on a form (Option A) can only check for the form submission; it cannot also evaluate the value of a field submitted in that form. An Automation Rule, however, is perfectly designed for this multi-criteria logic.

Automation Rule Criteria:
You would create an Automation Rule with a rule group where the prospect must match ALL of the following:

Form Submission is "Request a Demo"
State is one of Georgia, Florida

Automation Rule Action:
The action would be Assign prospect to user (or Assign prospect to user in group for round-robin assignment).
This rule will trigger and perform the assignment the moment a prospect submits the form and the submitted "State" field contains "Georgia" or "Florida." It is a fully automated, precise, and reliable solution.
Example:
A prospect located in Texas submits the "Request a Demo" form. The Automation Rule evaluates the criteria: Form is submitted? Yes. State is GA or FL? No. The rule does not trigger, and the prospect is not assigned. Another prospect in Florida submits the form. The rule evaluates: Form submitted? Yes. State is GA or FL? Yes. The rule triggers immediately and assigns the prospect to the designated sales rep.
Reference:
Salesforce Help documentation on Automation Rules highlights their use for complex logic based on prospect field values and activities. They are the recommended tool when an action depends on more than just a single activity trigger.

Incorrect Answers and Detailed Explanations

A. Create a completion action on the "Request a Demo" form with the action to assign to user.
This is incorrect because it is incomplete. A Completion Action on a form is a "dumb" trigger—it fires for every single submission of that form, regardless of what data is entered. If you set a Completion Action to "Assign to User," it would assign every prospect who submits the form, including those from Texas, California, etc. This violates the specific requirement to only assign prospects from Georgia or Florida. Completion Actions lack the ability to evaluate field values submitted with the form.

B. Add a completion action on the form to notify Admin, who manually assigns the prospect.
This is inefficient and does not fulfill the requirement for automation. While it technically "solves" the problem of identifying the right prospects, it introduces a manual, slow, and error-prone step. The business requirement is to "automatically assign," which implies a system-triggered action without human intervention. Relying on an admin to manually assign leads is not scalable and defeats the purpose of marketing automation.

C. Export the form submission report and import, assigning to the correct user upon import.
This is archaic, inefficient, and not a real-time automation. This is a completely manual process that involves exporting data, manipulating it (likely in Excel), and then re-importing it to perform the assignment. This process would have significant latency (prospects wouldn't be assigned for hours or days), is prone to human error, and is entirely unnecessary given that native, real-time automation tools (like Automation Rules) exist within the platform to handle this exact use case.

Summary and Key Takeaway
The key distinction tested here is between a simple activity-based trigger (a Completion Action) and a conditional logic-based trigger (an Automation Rule).
Use a Completion Action when you want something to happen whenever a specific activity occurs, with no additional conditions (e.g., "Always send a thank-you email after this form is submitted").
Use an Automation Rule when the action must only occur if the activity happens AND certain data conditions are met (e.g., "Assign a prospect only if they submit the demo form AND are in a specific territory").
For any complex qualification logic that involves evaluating prospect field values in conjunction with an activity, an Automation Rule is the definitive and correct tool.