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.
While preparing for a new analytics implementation for a site, you begin conducting stakeholder interviews. Part of the conversation includes defining KPIs, including custom success events.
Which are two examples of custom success events on a site? (Choose two.)
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.
A coworker creates the calculated metric named "Orders / Visits" in Adobe Analytics to determine the percentage of visits that purchased something on the company's website.
The coworker includes the calculated metric in the Products report. The coworker notices that the sum of the orders for the products is greater than the total orders shown in the report.
What should the Architect do?
The issue arises because the calculated metric 'Orders / Visits' is not aggregating correctly at the product level in the Products report. To resolve this, the Architect should create a calculated metric that uses the Total versions of the Orders and Visits metrics. This ensures that the calculation is performed on the overall totals rather than individual line items, providing an accurate percentage of visits that resulted in purchases.
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 beginning a full re-architecture of their website. They will use Adobe Launch as the tag management system. How should an Architect recommend that the data layer object be generated each time a page is requested?
The best practice for generating the data layer object each time a page is requested is to use server-side code to include the data layer in a <script> block in the page HTML's <head> section. This ensures that the data layer is available as soon as the page starts loading and can be used by Adobe Launch and other scripts. By having the data layer generated server-side, it reduces reliance on the client-side code and ensures the data is consistent and accurate for each page load.
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