AD0-E207 Adobe Analytics Architect Master Questions and Answers

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.

 Business Requirement: Use dynamic variables to collect the current page URL in eVar32.

 Method:

Dynamic Variable Syntax:D=cpreferences the current page URL.

 Explanation:

s.eVar32="D=cp": This syntax tells Adobe Analytics to dynamically populate eVar32 with the current page URL.

 Verification: According to Adobe Analytics dynamic variables documentation, usingD=cpcorrectly references and captures the current page URL in eVars (Adobe Analytics Dynamic Variables Guide).

Business Requirement: Analyze all internal search terms, including those falling into the "(low traffic)" category.

Extraction Methods:

Data Warehouse: Provides comprehensive data extraction capabilities, allowing for the retrieval of detailed and granular data that might not be fully visible in standard reports.

Data Feeds: Offers raw data extraction capabilities, enabling the capture of all search terms without the aggregation and sampling that can occur in standard reports.

Explanation:

Data Warehouse: Can export detailed data, bypassing the "(low traffic)" limitation by accessing the raw, unsampled data.

Data Feeds: Provides a way to extract raw data directly from Adobe Analytics, ensuring that all search terms, including those with low traffic, are included.

Verification: According to Adobe Analytics documentation, using Data Warehouse and Data Feeds are recommended methods for extracting comprehensive datasets, including detailed search terms (Adobe Analytics Data Warehouse Guide, Data Feeds Documentation).

To meet the specified business requirements, the query string parameters in the network request must include:

events=event1,event2: This captures both newsletter sign-up attempts (event1) and successful sign-ups (event2).

vl=architectsite.com: This identifies the URL.

pageName=homepage: This tracks the user journey through the site by page name.

ch=home: This captures the site section where the successful newsletter sign-ups occur.

The combination of these parameters ensures that all the required data points are collected and reported accurately.

Business Requirement: Extract data for weekly updates to a Tableau Dashboard from Adobe Analytics.

Recommended Method:

Deliver data via FTP through Data Warehouse: Provides a robust and automated method for exporting large datasets on a scheduled basis.

Explanation:

Data Warehouse: Allows for the extraction of large and complex datasets suitable for integration with external BI tools like Tableau.

FTP Delivery: Automates the data export process, ensuring timely updates to the Tableau Dashboard.

Verification: According to Adobe Analytics Data Warehouse documentation, using FTP delivery through Data Warehouse is the preferred method for exporting large datasets for external use (Adobe Analytics Data Warehouse Guide).

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: Ensure userID is set in the data layer and mapped to eVar5, and used for visitor identification.

 Issue Identification:

The userID data object must be available in the data layer before the Adobe Launch rule executes.

 Explanation:

visitorID is not available in the data layer when the Adobe Launch rule runs: If the visitorID is not present in the data layer at the time the rule executes, the mapping to eVar5 will not occur, resulting in an empty eVar5 report.

 Verification: According to Adobe Launch documentation, the timing of data layer availability is crucial for rule execution. Ensuring data is present before rules execute is necessary for accurate data capture (Adobe Launch Implementation 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.

 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).

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).

 Overview of the Issue: The "None" value in Marketing Channel reports indicates visits that are not attributed to any of the defined marketing channels.

 Potential Diagnostic Steps:

Break down "None" Marketing Channel by Tracking Code: This can provide insights but does not directly address the underlying configuration issues.

Review Marketing Channel Processing Rules: Ensures that the rules are correctly defined and applied. Incorrect or missing rules can result in visits being categorized as "None".

Review Marketing Channel Data Feeds: Useful for data validation but not for configuration troubleshooting.

Check that Internal URL Filters are configured correctly: Ensures that internal traffic is filtered out and does not interfere with marketing channel attribution.

Review Marketing Channel Data Connector settings: Relevant for integrations but not for basic processing rule configurations.

 Explanation:

Review Marketing Channel Processing Rules: Essential to verify that all necessary rules are correctly set up to attribute visits to the correct channels.

Check that Internal URL Filters are configured correctly: Ensures that visits from internal sources do not affect marketing channel data, preventing incorrect attribution to "None".

 Verification: According to Adobe Analytics Implementation documentation, reviewing processing rules and internal URL filters is crucial for accurate channel attribution (Adobe Analytics Implementation Guide).