In reviewing data from a Data Feeds request, an Architect sees that on the same hit, eVar1 has no value but post_eVarl has the value: PDP:summer:sunglasses
Why are these values different?
The difference between eVar1 and post_eVar1 values indicates that processing rules or Vista Rules are being applied. Processing rules or Vista Rules can modify the values of variables after the initial data collection. In this case, eVar1 initially has no value, but post_eVar1 shows the modified value 'PDP:summer
' after the application of these rules.
A company is using Segment IQ to compare mobile and desktop traffic.
The metrics of interest to them are as follows:
* Page Views/Visitors
* Searches/Visitors
* Carts/Visitors
* Cart Additions/Visitors
* Revenue/Visitors
The differential score when comparing each metric with each segment is high at 0.9 or greater. What does this differential score indicate?
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.
A Solution Design Reference (SDR) is built for architectsite.com. The site has the following business requirements:
* Report on newsletter sign-up attempts (event1) by URL
* View the user journey through the site by page name
* Track which site section successful newsletter sign-ups (event2) occur
Which query string parameters must be seen in the network request to meet the requirements?
To meet the specified business requirements, the query string parameters in the network request must include:
events=event1,event2: This captures both newsletter sign-up attempts (event1) and successful sign-ups (event2).
vl=architectsite.com: This identifies the URL.
pageName=homepage: This tracks the user journey through the site by page name.
ch=home: This captures the site section where the successful newsletter sign-ups occur.
The combination of these parameters ensures that all the required data points are collected and reported accurately.
A company has an email marketing tool that is used for both SMS and email.
The tool generates the following campaign URLs:
SMS link: www.website.com?cid=em:campaign_name-txt Email link: www.website.com?cid=em:campaign_name
How should the Architect configure Marketing Channel Processing Rules to identify the SMS channel?
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).
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).
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