AD0-E207 Adobe Analytics Architect Master Question and Answers

ï‚· Business Requirement: Report on Facebook and Twitter activity separately in Marketing Channel reports.

ï‚· 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.

ï‚· 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).

ï‚· 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).

ï‚· Business Goal: Increase website account registrations by tracking relevant metrics.

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

ï‚· 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.

ï‚· 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.

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

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.

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.

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.

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.

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 correctly capture the specified data in Adobe Analytics, thes.productssyntax needs to be properly formatted to include the product SKU, quantity, price, and custom variables and events. The correct format is:

SKU:atp29

Quantity:1

Price:700.00

Event1:70.00(discount)

eVar1:SUMMER10(coupon code)

eVar2:Amaze Touch Pro(product name)

The correct syntax is:

arduino

Copy code

s.products =";atp29;1 ;700.00;eventl =70.00;eVar1 =SUMMER10|eVar2=Amaze Touch Pro";

This format ensures that all the specified information is correctly captured and recorded in Adobe Analytics.

ï‚· Business Requirement: Enable a two-way integration between Adobe Audience Manager (AAM) and Adobe Analytics.

ï‚· Configuration Needs:

List Variable: Used to bring in multiple AAM segments into Adobe Analytics.

Server-Side Forwarding: Ensures that data flows between Adobe Analytics and AAM seamlessly.

ï‚· Explanation:

List Variable: Suitable for handling multiple segments and their associations with other metrics within Adobe Analytics.

Server-Side Forwarding: This method ensures real-time data exchange between the platforms, enabling both to use each other's data for enhanced segmentation and reporting.

ï‚· Verification: According to Adobe's documentation on integrating Audience Manager and Analytics, using list variables with server-side forwarding is the recommended approach for robust two-way integration (Adobe Audience Manager and Analytics Integration Guide).

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: 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).

====

ï‚· Business Requirement: Distinguish between SMS and email campaigns using the "cid" query string parameter.

ï‚· Configuration Steps:

Identify SMS Links: Using the query string parameter "cid" ending with "-txt".

Processing Order: Ensuring the SMS channel is processed before the email channel.

ï‚· Explanation:

Query String Parameter "cid" Ends with "-txt": This setting ensures that any link containing "cid" ending with "-txt" is identified as an SMS link.

Processing Order: Placing the SMS channel rule above the email channel ensures that SMS links are correctly categorized before the system checks for email links.

ï‚· Verification: According to Adobe's Marketing Channel Processing Rules documentation, properly configuring query string parameters and processing order is crucial for accurate channel attribution (Adobe Analytics Marketing Channel Processing Rules Guide).