Adobe AD0-E207 Exam Dumps

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.

B . s.eVar1 = s.prop1:

Directly setting the eVar value to the prop value in the code is straightforward but does not minimize the server call size as both values are separately included in the request.

C . s.eVar1 = 'D=c1':

This method uses dynamic variable substitution, which reduces the server call size by referencing the prop value (c1) directly in the eVar without duplicating the data in the request.

Verification: Check the Adobe Analytics server call in the Network tab to confirm the reduced size.

D . A processing rule to copy the prop value to the eVar:

Processing rules can be used to copy values server-side, similar to VISTA rules but without the additional cost. However, this approach does not minimize the server call size.

Detailed Steps:

Dynamic Variable Substitution:

Set the eVar value to reference the prop value using the syntax s.eVar1 = 'D=c1'.

This tells Adobe Analytics to dynamically substitute the value of c1 (prop1) into eVar1 without sending redundant data.

Example:

s.prop1 = 'exampleValue';

s.eVar1 = 'D=c1';

Benefits:

Reduced Server Call Size: By using dynamic variable substitution, the server call payload is smaller, optimizing data transmission.

Efficient Data Handling: The value is captured once in the prop and referenced in the eVar, maintaining efficiency and persistence.

References:

Adobe Analytics Implementation Documentation: Dynamic Variable Substitution

Adobe Analytics Network Call Analysis Guide: Understanding Server Calls

By using s.eVar1 = 'D=c1', the Architect achieves the goal of collecting the value in both a prop and an eVar efficiently while minimizing the server call size.

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.

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).

When merchandising is enabled in Adobe Analytics, revenue attribution can vary based on the allocation method:

Linear Allocation: Distributes revenue equally across all instances of the product view and add-to-cart events. Thus, $100 would be attributed to both merch_category1 and merch_category2.

Most Recent Allocation: Attributes the revenue to the most recent instance of the variable. Thus, $100 would be attributed to merch_category2.

This approach ensures that revenue attribution accurately reflects user interactions with products.

To correctly capture the specified data in Adobe Analytics, the s.products syntax 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:

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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.