AD0-E207 Adobe Analytics Architect Master Questions and Answers

Processing Rules in Adobe Analytics are versatile and can be used for various purposes:

Clean up misspelled site sections: Corrects misspelled values in data collection to ensure accurate reporting.

Populate campaign with a query string parameter: Extracts query string parameters and uses them to populate campaign variables.

Copy an eVar into a prop to see pathing: Allows copying values from an eVar to a prop to enable pathing analysis on that variable.

These rules help maintain data quality and flexibility in reporting.

When uploading data source files to Adobe Analytics, it is crucial that each record has the same number of columns as the header record. If one of the records does not match the number of columns, the entire file will not be processed due to the column mismatch. This ensures data integrity and consistency in the uploaded data.

 Business Requirement: Ensure data captured by eVar1 is correctly reported.

 Potential Issues:

Tracking server is incorrect: Data might not be sent to the correct server for processing.

eVar1 is NOT enabled in admin settings: The eVar must be enabled in the admin settings to be recorded and reported.

Report Suite ID is incorrect: Data might be sent to the wrong report suite, causing discrepancies in reporting.

 Explanation:

Tracking server is incorrect: Ensures data reaches the correct Adobe Analytics server for processing.

eVar1 is NOT enabled in admin settings: Critical to have eVar1 enabled for it to collect and report data.

Report Suite ID is incorrect: Ensures data is reported in the correct report suite.

 Verification: According to Adobe Analytics troubleshooting documentation, ensuring the correct tracking server, enabled eVars, and correct Report Suite ID are fundamental steps in diagnosing reporting issues (Adobe Analytics Troubleshooting Guide).

To benchmark the effectiveness of the current navigation system, the Architect should look at the navigation usage rate per visit. This metric, calculated by multiplying the number of navigation clicks by the number of visits, provides insight into how often visitors are engaging with the navigation system on a per-visit basis. It helps to understand the relative frequency of navigation usage, which is crucial for optimizing the system and ensuring that it effectively helps users to explore the site and find products.

Segment IQ in Adobe Analytics is used to compare different segments of traffic to determine the statistical significance of differences between metrics. A high differential score of 0.9 or greater indicates a high statistical significance difference between the metrics of the two segments. This means that the differences observed in metrics like Page Views/Visitors, Searches/Visitors, Carts/Visitors, Cart Additions/Visitors, and Revenue/Visitors are not due to random chance but are significant and meaningful.

Custom success events in Adobe Analytics are specific to the business goals and can vary widely depending on the site’s purpose. Examples of such events typically include actions that are significant indicators of user engagement or progress through a conversion funnel:

Cart Adds: Tracking how often users add items to their cart.

Form Completions: Monitoring the number of users who complete and submit forms on the site.

These are distinct from more generic metrics like purchases or checkouts which are often predefined standard events in many analytics implementations.

 Business Requirement: The company wants to track successful and unsuccessful form submissions and identify the types of forms being submitted.

 Variables and Metrics Needed:

Event for "Forms Submitted with Errors": Captures instances where forms are submitted but contain errors.

eVar for "Form Type": Identifies the type of form being submitted, which is crucial for analyzing different form performance.

Event for "Forms Submitted Successfully": Captures instances where forms are successfully submitted.

 Explanation:

Event for "Forms Submitted with Errors": Essential for understanding and improving form completion processes by identifying where users encounter issues.

eVar for "Form Type": Provides detailed breakdowns of form performance by type, aiding in targeted improvements.

Event for "Forms Submitted Successfully": Measures the completion rate of forms, which is critical for business metrics.

 Verification: According to Adobe Analytics best practices, using specific events for tracking successful and error submissions alongside eVars for categorization provides comprehensive insights (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).

To capture and analyze the contribution of news sections to conversions, the following steps should be taken:

Assign a custom eVar to capture the news section value: This allows for tracking which news sections users engage with.

Enable linear attribution to the eVar: Linear attribution ensures that all news sections engaged with during a session are credited proportionally for any conversions, providing a more balanced view of their contribution.

Expire the eVar after the visit: This ensures that the attribution is relevant to the current session and does not carry over to future sessions, maintaining accuracy in conversion analysis.

This approach provides a clear and comprehensive understanding of how different news sections contribute to conversions.

To track website usage without visitors seeing which data points are being collected, the recommended approach is to send tracking calls server-side via the Data Insertion API. This method allows for the collection of page names, form names, a counter event for each page of the checkout flow, and thes.productsvariable while keeping the tracking logic and data points hidden from the client side.

 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).

 Business Goal: Increase website account registrations by tracking relevant metrics.

 Key Dimensions and Metrics: Visitor Login Status, Form Name, Form Starts, Forms Submitted With Errors, Forms Submitted Successfully.

 Calculated Metrics:

Registration Form Completion Rate: Measures the percentage of forms started that are successfully completed, providing insights into form usability and effectiveness.

Return Visitation Rate: Tracks how often visitors return but is not directly related to registration form completion.

Registered Visitor Transaction Rate: Useful for post-registration analysis but not directly for increasing registrations.

Registered Visitor Form Start Rate: Redundant as registered visitors are less relevant for new registrations.

Unregistered Visitor Registration Form Start Rate: Tracks the engagement of unregistered visitors with the registration form, crucial for understanding initial interest.

 Explanation:

Registration Form Completion Rate: Essential for evaluating the effectiveness of the registration form.

Unregistered Visitor Registration Form Start Rate: Provides insights into how many new visitors are interested in registering, a direct indicator of potential registration increase.

 Verification: According to Adobe's Measurement Planning documentation, these calculated metrics are vital for tracking and improving form conversion rates (Adobe Measurement Planning Guide).