An Architect advises a site developer to embed the Adobe Launch script in the <head> and to place the data layer before the closing
tag of a web page.
During testing, an Adobe Analytics page view call fires successfully. Several Adobe variables are not defined in the call. The embedded Launch script and the data layer are implemented correctly per the Architect's specifications.
What should the Architect do to resolve the issue?
Move the data layer to before the Adobe Launch script in the <head>.
Move the data layer just before the tag.
Move the data layer to after the Adobe Launch script in the <head>.
Move the data layer just before the
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 the<head>section of the webpage. This ensures that all data layer variables are available to the Launch script during its execution.
An Architect is using dynamic variables in an Adobe Analytics implementation. eVar32 is used to collect the current page URL.
Which syntax should be used?
s.eVar32="D=g'
s.eVar32='D=cp"
s.eVar32=*D=host'
s eVar32="D=url"
Business Requirement: Use dynamic variables to collect the current page URL in eVar32.
Method:
Dynamic Variable Syntax:D=cpreferences the current page URL.
Explanation:
s.eVar32="D=cp": This syntax tells Adobe Analytics to dynamically populate eVar32 with the current page URL.
Verification: According to Adobe Analytics dynamic variables documentation, usingD=cpcorrectly references and captures the current page URL in eVars (Adobe Analytics Dynamic Variables Guide).
An Architect is unable to analyze all internal search terms for the previous month because 15% of the internal search terms fall into "(low traffic)".
Which two extraction methods will show all search terms? (Choose two.)
Data Extract
Report Builder
Data Warehouse
Data Feeds
Reporting API
Business Requirement: Analyze all internal search terms, including those falling into the "(low traffic)" category.
Extraction Methods:
Data Warehouse: Provides comprehensive data extraction capabilities, allowing for the retrieval of detailed and granular data that might not be fully visible in standard reports.
Data Feeds: Offers raw data extraction capabilities, enabling the capture of all search terms without the aggregation and sampling that can occur in standard reports.
Explanation:
Data Warehouse: Can export detailed data, bypassing the "(low traffic)" limitation by accessing the raw, unsampled data.
Data Feeds: Provides a way to extract raw data directly from Adobe Analytics, ensuring that all search terms, including those with low traffic, are included.
Verification: According to Adobe Analytics documentation, using Data Warehouse and Data Feeds are recommended methods for extracting comprehensive datasets, including detailed search terms (Adobe Analytics Data Warehouse Guide, Data Feeds Documentation).
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?
events=event1,event2 vl =architectsite.com pageName=homepage site=home
events=eventl ,event2 vl =architectsite.com pageName=homepage cc=home
events=event1 .event2 vl =architectsite.com pn=homepage ch=home
events-event! ,event2 vl =architectsite.com pageName=homepage ch=home
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 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?
Download Excel from Custom Report
Download CSV from Analysis Workspace Report
Deliver data via FTP through Data Warehouse
Deliver data via FTP through Data Feeds
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.
Explanation:
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 develops a new website using a Single Page Application framework. A data layer variable called dataLayer.url is updated with the correct URL when each state change happens.
Which variable should the Architect map to dataLayer.url?
s.pageURL
s.linklnternalFilters
s.url
s.spaURL
For Single Page Applications (SPAs), it is important to capture the URL changes correctly. Thes.pageURLvariable should be mapped todataLayer.urlto ensure that Adobe Analytics captures the correct URL each time the state changes in the SPA. This allows accurate tracking of user navigation within the SPA framework.
An Architect has defined the following tracking specifications:
• A userlD variable must be set in the data layer
• The userlD value must be mapped to eVar5
• The userlD value must be used as the Adobe visitor identification method.
The tagging engineer confirms that Adobe Launch is configured as requested.
An Analyst notices that the eVar5 report is not being populated.
The Architect can see that the userlD data object is populated in the data layer after the page loads.
What is causing this problem?
visitorlD is not available in the data layer when the Adobe Launch rule runs
userlD is not being populated using dynamic variables.
eVar5 is not being populated using dynamic variables.
userlD is not available in the data layer when the Adobe Launch rule runs.
Business Requirement: Ensure userID is set in the data layer and mapped to eVar5, and used for visitor identification.
Issue Identification:
The userID data object must be available in the data layer before the Adobe Launch rule executes.
Explanation:
visitorID is not available in the data layer when the Adobe Launch rule runs: If the visitorID is not present in the data layer at the time the rule executes, the mapping to eVar5 will not occur, resulting in an empty eVar5 report.
Verification: According to Adobe Launch documentation, the timing of data layer availability is crucial for rule execution. Ensuring data is present before rules execute is necessary for accurate data capture (Adobe Launch Implementation Guide).
An Architect needs to create a segment of users that started a visit from a campaign and completed an order.
A specific product demo page and coupon page can be viewed in any order between the landing page and the order confirmation page.
What should the Architect use to meet the requirements?
Non-sequential containers
Logical group containers
Only before sequence segments
Only after sequence segments
In Adobe Analytics, non-sequential segments allow for the inclusion of conditions that do not necessarily occur in a specific order. Since the specific product demo page and coupon page can be viewed in any order between the landing page and the order confirmation page, non-sequential containers are the appropriate choice. They allow for the creation of a segment whereusers must have started their visit from a campaign and completed an order, without enforcing a strict sequence for intermediate steps.
A customer launches a new checkout flow that includes all checkout steps in a Single Page Application.
The development team must be instructed on how to indicate when a user moves to the next step of the checkout flow so this information can be tracked in Adobe Analytics using Adobe Launch.
The customer wants to be able to report on each step of the checkout as different page views.
Which configuration of an Adobe Launch rule must the tagging engineer configure in Adobe Launch to meet these requirements?
Direct Call Event with an s.t() beacon
Click Event with an s.t()
Direct Call Event with an s.tl() beacon
DOM Ready Event with an s.t()
Business Requirement: Track each step of the checkout process as separate page views in a Single Page Application (SPA).
Configuration:
Direct Call Event: Triggered explicitly by the application code when a user moves to the next step.
s.t() beacon: Sends a page view beacon, suitable for capturing page views in SPAs.
Explanation:
Direct Call Event: Allows developers to indicate specific points in the SPA where analytics tracking should occur.
s.t() beacon: Suitable for recording page views, capturing each step in the checkout flow as a separate page view.
Verification: According to Adobe Launch documentation, using Direct Call Events with s.t() beacons is the recommended approach for tracking page views in SPAs (Adobe Launch Implementation Guide).
While auditing the Adobe Analytics implementation, an Architect finds that the hourly unique visitor report is 3 hours behind.
What is causing this issue?
Increased unique variable values
Increased number of users running repots
New variables enabled for report suite
An unexpected traffic spike
Overview of the Issue: The hourly unique visitor report being 3 hours behind indicates a delay in data processing within Adobe Analytics.
Potential Causes: The delay could be due to several factors such as increased data volume, server performance issues, or unexpected traffic spikes.
Explanation:
Increased unique variable values: This could slow down processing, but it typically affects data collection rather than causing such a significant delay.
Increased number of users running reports: This might slow down the user interface and report generation, but not data processing itself.
New variables enabled for report suite: This usually affects the data collection stage and can cause delays but would not typically result in a consistent 3-hour lag.
An unexpected traffic spike: A sudden increase in traffic can overload data processing servers, causing delays in reporting as the system tries to catch up with the increased data volume.
Verification: According to Adobe's documentation, data processing delays are often caused by unexpected traffic spikes that increase the volume of data beyond typical processing capacity (Adobe Analytics Documentation).
An Architect needs to update mobile data collection to comply with company and legal guidelines (GDPR, CCPA). The Architect discovers the Android version of their mobile application tracks the latitude, longitude, and iBeacon data. Tracking specific geographic data is now considered out of compliance with company guidelines, and must be updated.
Which call must be removed?
getGeoCoordinates
trackState
trackAction
trackLocation
Business Requirement: Ensure compliance with GDPR and CCPA by updating mobile data collection practices.
Tracking Methods:
getGeoCoordinates: Retrieves geographical coordinates but is typically not the method used for tracking purposes.
trackState: Tracks the state of the application and user interaction.
trackAction: Tracks specific user actions within the application.
trackLocation: Explicitly tracks geographic location data, including latitude, longitude, and iBeacon data.
Explanation:
trackLocation: Must be removed to comply with regulations as it directly tracks and transmits geographic location data.
Verification: According to Adobe Mobile Services documentation, removing the trackLocation call ensures compliance with data protection regulations by eliminating the collection of sensitive geographic data (Adobe Mobile SDK Guide).
While auditing an Adobe Analytics implementation, an Architect discovers that reports built using the Marketing Channel dimension show a large proportion of "None'' visits.
Which two steps should be taken to diagnose the problem? (Choose two.)
Break down "None1' Marketing Channel by Tracking Code
Review Marketing Channel Processing Rules
Review Marketing Channel Data Feeds
Check that Internal URL Filters are configured correctly
Review Marketing Channel Data Connector settings
Overview of the Issue: The "None" value in Marketing Channel reports indicates visits that are not attributed to any of the defined marketing channels.
Potential Diagnostic Steps:
Break down "None" Marketing Channel by Tracking Code: This can provide insights but does not directly address the underlying configuration issues.
Review Marketing Channel Processing Rules: Ensures that the rules are correctly defined and applied. Incorrect or missing rules can result in visits being categorized as "None".
Review Marketing Channel Data Feeds: Useful for data validation but not for configuration troubleshooting.
Check that Internal URL Filters are configured correctly: Ensures that internal traffic is filtered out and does not interfere with marketing channel attribution.
Review Marketing Channel Data Connector settings: Relevant for integrations but not for basic processing rule configurations.
Explanation:
Review Marketing Channel Processing Rules: Essential to verify that all necessary rules are correctly set up to attribute visits to the correct channels.
Check that Internal URL Filters are configured correctly: Ensures that visits from internal sources do not affect marketing channel data, preventing incorrect attribution to "None".
Verification: According to Adobe Analytics Implementation documentation, reviewing processing rules and internal URL filters is crucial for accurate channel attribution (Adobe Analytics Implementation Guide).
TESTED 18 Feb 2025