A new Adobe Analytics implementation recently went live on an ecommerce site.
An Analyst notices some problems during the analysis of the product details pages for Electronics products:
* The expected "PDP" value does not appear in the Site Section dimension.
* No product views are associated with these pages.
* The expected product category of "Electronics" is not populating eVarlO.
Which parameters should the Architect see in browser network requests when the solution operates correctly?
Business Requirement: Ensure correct tracking of product detail pages for Electronics products.
Expected Parameters:
events=prodView: Tracks the product view event.
ch=PDP: Sets the site section to 'PDP' (Product Detail Page).
eVar10=Electronics: Captures the product category.
events=prodView: Ensures product views are recorded.
ch=PDP: Ensures the site section is correctly identified as 'PDP'.
eVar10=Electronics: Ensures the product category is captured correctly.
Verification: According to Adobe Analytics documentation on event tracking and eVars, using these parameters ensures accurate and detailed tracking of product detail pages (Adobe Analytics Implementation Guide).
A company has a Tableau Dashboard that includes data from various sources including Adobe Analytics. The dashboard is
updated weekly.
Which method should an Architect use to extract the data to be used with the dashboard?
Business Requirement: Extract data for weekly updates to a Tableau Dashboard from Adobe Analytics.
Recommended Method:
Deliver data via FTP through Data Warehouse: Provides a robust and automated method for exporting large datasets on a scheduled basis.
Data Warehouse: Allows for the extraction of large and complex datasets suitable for integration with external BI tools like Tableau.
FTP Delivery: Automates the data export process, ensuring timely updates to the Tableau Dashboard.
Verification: According to Adobe Analytics Data Warehouse documentation, using FTP delivery through Data Warehouse is the preferred method for exporting large datasets for external use (Adobe Analytics Data Warehouse Guide).
A company wants to report on the monetary value of a visitor's cart when they reach the checkout page.
The company offers only 5 products online. They want to report on product names but do not want to upload files into Adobe Analytics to classify the product IDs.
A visitor reaches the checkout page with the following items in their cart:
* A single $8 Novelty Mug", product ID=123
* 2 bags of "Coffee Beans'' with a total price of $10, product ID=234
Which variable values must be set to meet these requirements?
Business Requirement: Report on the monetary value of a visitor's cart at the checkout page without using product IDs.
Variable Configuration:
s.events: Captures the checkout event and the monetary value.
s.products: Lists the product names and their corresponding values.
Explanation:
s.events = 'scCheckout,event1': This sets the event to capture the checkout action and records the event value.
s.products = ';Novelty Mug;;;event1=8.00,;Coffee Beans;;;event1=10.00': This format lists the products by name and assigns their respective monetary values.
Verification: According to Adobe Analytics product string documentation, the format used correctly attributes product names and values to the checkout event (Adobe Analytics Implementation Guide).
A media company has a business requirement to capture a value of the news sections (politics, sports, food) that an art belongs to that visitors engage with. The company wants to understand and analyze the contribution the news sections give to any type of conversion.
The company also wants to assign attribution to all of the news sections engaged with when a conversion takes place during the active session to analyze what news sections play a role in the conversion activity.
Which solution should the architect use?
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.
During a website audit, an Architect finds that the checkout pages on the site have been redesigned to include a tag management system that deploys Adobe Analytics.
The rest of the site has Adobe Analytics hard-coded onto the site. Both implementations use the same AppMeasurement version and are on the same domain.
How will this approach affect the reporting?
When different parts of a website use different methods to implement Adobe Analytics (hard-coded vs. tag management system), it can lead to inconsistencies in data reporting. This is because the two methods might not be perfectly synchronized in terms of how they handle data collection, processing rules, or variables. Despite using the same AppMeasurement version and operating on the same domain, differences in the deployment method can cause issues such as discrepancies in variable persistence, tracking cookies, or firing sequence of the analytics calls. These inconsistencies can make it difficult to maintain and accurately report on the collected data.
