AD0-E207 Adobe Analytics Architect Master Questions and Answers

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.

 Business Requirement: Enable server-side forwarding to integrate Adobe Audience Manager (AAM) with Adobe Analytics.

 Configuration Location:

Adobe Analytics Report Suite settings: This is where server-side forwarding needs to be enabled to allow data to be sent from Adobe Analytics to AAM.

 Explanation:

Adobe Analytics Report Suite settings: This setting ensures that data collected in Adobe Analytics is forwarded to Adobe Audience Manager.

 Verification: According to Adobe's integration documentation, server-side forwarding is configured within the Adobe Analytics Report Suite settings (Adobe Analytics and Audience Manager Integration Guide).

To deploy Adobe Analytics with Launch asynchronously, the necessary JavaScript library must be referenced in the header code of the HTML page. This ensures that the Launch library is loaded early in the page load process, allowing it to manage and fire tags efficiently.

When different parts of a website use different methods to implement Adobe Analytics (hard-coded vs. tag management system), it can lead to inconsistencies in data reporting. This is because the two methods might not be perfectly synchronized in terms of how they handle data collection, processing rules, or variables. Despite using the same AppMeasurement version and operating on the same domain, differences in the deployment method can cause issues such as discrepancies in variable persistence, tracking cookies, or firing sequence of the analytics calls. These inconsistencies can make it difficult to maintain and accurately report on the collected data.

Virtual report suites in Adobe Analytics have the following attributes:

Some settings are inherited from the parent report suite: Virtual report suites inherit certain configurations from the parent report suite, such as variable definitions and processing rules.

They can be added individually to permission groups: Virtual report suites can be assigned to different user groups, allowing for controlled access based on permissions.

Current and real-time data is supported: Virtual report suites support current and real-time data, enabling up-to-date reporting and analysis.

These attributes make virtual report suites a flexible and powerful tool for segmenting and managing data within Adobe Analytics.

 Business Requirement: The company needs to report on internal search keywords and their contribution to revenue by creating thedigitalData.search.keyworddata object in the data layer.

 Recommended Syntax: The syntax must be correctly structured to allow Adobe Analytics to map the data object to eVar1 efficiently.

 Explanation:

 Business Requirement: The company wants to ensure that the original search term ("Mobile") receives credit for the purchase, despite subsequent searches.

 Understanding Merchandising eVars: Merchandising eVars are used to attribute success events (like purchases) to specific values captured earlier (like search terms).

 Allocation and Expiration Settings:

Original Value (First) Allocation: This setting ensures that the first value captured (in this case, "Mobile") remains attributed to the visitor, regardless of subsequent values.

Expiration Setting: Setting the expiration to the purchase event ensures that the value ("Mobile") remains active until the visitor makes a purchase.

 Explanation:

Configure an eVar as Merchandising Variable: This allows tracking specific values like search terms in relation to product views and purchases.

Original Value (First) Allocation: Ensures that the initial search term ("Mobile") gets credit.

Expiration to Purchase Event: Keeps the eVar value until the purchase is made, ensuring accurate attribution.

 Verification: According to Adobe Analytics documentation on Merchandising eVars, using Original Value allocation with appropriate expiration settings ensures correct attribution of original search terms to final purchases (Adobe Analytics Implementation Guide).

 Business Requirement: The company wants to track shares of blog posts to social networks and report on the total number of shares and the specific networks used.

 Variables and Metrics Needed:

eVar for "Blog Post Title": Captures the title of the blog post being shared.

eVar for "Blog Share Social Network": Captures the social network to which the post is shared.

Event for "Blog Shares": Captures the number of times a post is shared.

 Explanation:

eVar for "Blog Post Title": This variable allows reporting on the specific blog posts being shared.

eVar for "Blog Share Social Network": This variable tracks which social networks the posts are shared to, enabling detailed reporting.

Event for "Blog Shares": This metric captures the total number of shares, providing a quantifiable measure of sharing activity.

 Verification: According to Adobe Analytics best practices for tracking social sharing, using specific eVars for post titles and social networks along with an event for total shares ensures comprehensive reporting (Adobe Analytics Implementation Guide).

Business Requirement: Determine the appropriate report suite IDs for different websites using one Adobe Launch property.

Method:

Data Element: Utilizes a data element to dynamically determine and populate the report suite ID based on the domain or other contextual information.

Explanation:

Data Element: Provides flexibility to dynamically assign the correct report suite ID for each website based on defined conditions or context.

Verification: According to Adobe Launch best practices, using data elements to populate report suite IDs ensures accurate and context-specific tracking across multiple domains (Adobe Launch Documentation).

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To make Adobe Analytics data GDPR-compliant, specific privacy settings need to be applied to the variables that collect personal data. The following privacy settings are relevant:

12: This identifier is for data elements that are directly related to individuals.

DEL-PERSON: This setting indicates that the data should be deleted if requested by the user under GDPR.

ACC-PERSON: This setting allows access to the data by the individual upon request.

By applying these settings to the variables collecting gender and age data, the company ensures compliance with GDPR regulations, allowing for the necessary control and access to personal data.

 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).