Practice Free AD0-E207 Adobe Analytics Architect Master Exam Questions Answers With Explanation

Business Requirement: Ensure correct tracking of product detail pages for Electronics products.

Expected Parameters:

events=prodView: Tracks the product view event.

ch=PDP: Sets the site section to "PDP" (Product Detail Page).

eVar10=Electronics: Captures the product category.

Explanation:

events=prodView: Ensures product views are recorded.

ch=PDP: Ensures the site section is correctly identified as "PDP".

eVar10=Electronics: Ensures the product category is captured correctly.

Verification: According to Adobe Analytics documentation on event tracking and eVars, using these parameters ensures accurate and detailed tracking of product detail pages (Adobe Analytics Implementation Guide).

? Business Requirement: Report on Facebook and Twitter activity separately in Marketing Channel reports.

? Configuration Steps:

Identify Social Media Traffic: Create a rule to identify all social media traffic.

Split Facebook and Twitter Traffic: Create rules to distinguish traffic from Facebook and Twitter based on tracking codes.

? Explanation:

First Rule for Social Media Traffic: This rule captures all social media traffic under a single category.

Second Rule to Split Traffic: Additional rules to distinguish between Facebook and Twitter based on specific tracking codes ("socialjb" for Facebook and "sociaLtw" for Twitter).

? Verification: According to Adobe's documentation on Marketing Channel Processing, using multiple rules to identify and then split traffic ensures detailed and accurate reporting (Adobe Analytics Marketing Channel Processing Rules Guide).

Overview of the Issue: The hourly unique visitor report being 3 hours behind indicates a delay in data processing within Adobe Analytics.

Potential Causes: The delay could be due to several factors such as increased data volume, server performance issues, or unexpected traffic spikes.

Explanation:

Increased unique variable values: This could slow down processing, but it typically affects data collection rather than causing such a significant delay.

Increased number of users running reports: This might slow down the user interface and report generation, but not data processing itself.

New variables enabled for report suite: This usually affects the data collection stage and can cause delays but would not typically result in a consistent 3-hour lag.

An unexpected traffic spike: A sudden increase in traffic can overload data processing servers, causing delays in reporting as the system tries to catch up with the increased data volume.

Verification: According to Adobe's documentation, data processing delays are often caused by unexpected traffic spikes that increase the volume of data beyond typical processing capacity (Adobe Analytics Documentation).

? Business Requirement: Ensure compliance with GDPR and CCPA by updating mobile data collection practices.

? Tracking Methods:

getGeoCoordinates: Retrieves geographical coordinates but is typically not the method used for tracking purposes.

trackState: Tracks the state of the application and user interaction.

trackAction: Tracks specific user actions within the application.

trackLocation: Explicitly tracks geographic location data, including latitude, longitude, and iBeacon data.

? Explanation:

trackLocation: Must be removed to comply with regulations as it directly tracks and transmits geographic location data.

? Verification: According to Adobe Mobile Services documentation, removing the trackLocation call ensures compliance with data protection regulations by eliminating the collection of sensitive geographic data (Adobe Mobile SDK Guide).

In Adobe Analytics, non-sequential segments allow for the inclusion of conditions that do not necessarily occur in a specific order. Since the specific product demo page and coupon page can be viewed in any order between the landing page and the order confirmation page, non-sequential containers are the appropriate choice. They allow for the creation of a segment whereusers must have started their visit from a campaign and completed an order, without enforcing a strict sequence for intermediate steps.

The issue in the original code lies in the incorrect placement of the event syntax. In Adobe Analytics, when defining events in the product string, the correct format must be followed to ensure the event is captured properly. Specifically, there needs to be a double semicolon (;;) before the event definition.

The corrected codes.products = ";car stereo;1 ;820;;event100=23"ensures that the event is recognized correctly by Adobe Analytics.

To ensure that Adobe Launch and its variables are correctly defined and available when the page view call is fired, the data layer should be placed before the Adobe Launch script in thesection of the webpage. This ensures that all data layer variables are available to the Launch script during its execution.

For Single Page Applications (SPAs), it is important to capture the URL changes correctly. Thes.pageURLvariable should be mapped todataLayer.urlto ensure that Adobe Analytics captures the correct URL each time the state changes in the SPA. This allows accurate tracking of user navigation within the SPA framework.

? Business Requirement: Track each step of the checkout process as separate page views in a Single Page Application (SPA).

? Configuration:

Direct Call Event: Triggered explicitly by the application code when a user moves to the next step.

s.t() beacon: Sends a page view beacon, suitable for capturing page views in SPAs.

? Explanation:

Direct Call Event: Allows developers to indicate specific points in the SPA where analytics tracking should occur.

s.t() beacon: Suitable for recording page views, capturing each step in the checkout flow as a separate page view.

? Verification: According to Adobe Launch documentation, using Direct Call Events with s.t() beacons is the recommended approach for tracking page views in SPAs (Adobe Launch Implementation Guide).

Standard metrics in Adobe Analytics are those that come pre-configured within the platform and are commonly used across various types of implementations. These include:

Purchase: Tracks the completion of a purchase transaction.

Orders: Records the number of orders placed.

These metrics are essential for eCommerce tracking and are part of the standard set of metrics available in Adobe Analytics.