AD0-E207 Exam Dumps - Adobe Analytics Questions and Answers

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.

 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).

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.

The issue arises because the calculated metric "Orders / Visits" is not aggregating correctly at the product level in the Products report. To resolve this, the Architect should create a calculated metric that uses the Total versions of the Orders and Visits metrics. This ensures that the calculation is performed on the overall totals rather than individual line items, providing an accurate percentage of visits that resulted in purchases.

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.

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.

To restrict data access to different business groups based on their department, the following methods can be used:

Create a global report suite with an eVar set to the department then create virtual suites based on that eVar: This method allows for a single comprehensive dataset that can be segmented into virtual report suites for each department, making data management and reporting easier.

Create individual report suites for each department and assign each analyst the access rights: This approach provides complete data isolation for each department, ensuring that analysts only have access to their respective department's data.

Both methods ensure that data access is properly restricted and managed according to departmental boundaries.

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.

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.

Introduction: The requirement is to use a value in both a prop (for pathing reports) and an eVar (for persistence) while minimizing the size of the server call.

Explanation of Methods:

A. A VISTA rule to copy the prop value to the eVar:

VISTA (Visitor Identification, Segmentation & Transformation Architecture) rules are server-side rules that can copy values between variables. However, they are complex, incur additional costs, and do not reduce server call size.