Adobe AD0-E207 Practice Test - Questions Answers, Page 2

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 code s.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.

Standard metrics in Adobe Analytics are those that come pre-configured within the platform and are commonly used across various types of implementations. These include:

Purchase: Tracks the completion of a purchase transaction.

Orders: Records the number of orders placed.

These metrics are essential for eCommerce tracking and are part of the standard set of metrics available in Adobe Analytics.

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.

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: Enable a two-way integration between Adobe Audience Manager (AAM) and Adobe Analytics.

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.

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.

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).

Business Requirement: Distinguish between SMS and email campaigns using the 'cid' query string parameter.

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.

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.

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).

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).