vmartinez

The _________________ panel within AMC is a repository of Amazon-authored SQL templates and includes associated use cases, instructions, and a guide to interpret the results.

• Paid features
• Schema explorer
• Query editor
• Instructional queries

 

Explanation: The correct answer is **Instructional queries** because the **Instructional queries** panel within Amazon Marketing Cloud (AMC) serves as a repository for Amazon-authored SQL templates. This panel includes a variety of pre-built query templates that are designed to help users quickly start their analysis. It also provides associated use cases, detailed instructions, and a guide on how to interpret the results, making it easier for users, especially those who are new to AMC, to understand and apply common SQL queries for their advertising campaigns. This resource is particularly helpful for users looking to perform specific analyses without having to write SQL queries from scratch. The other options, such as Schema explorer, Query editor, and Paid features, do not focus on providing instructional SQL templates in the same way the **Instructional queries** panel does.

 

This table contains impression and click events from Sponsored Products (SP), Sponsored Brands (SB), and Sponsored Display (SD) campaigns.

• adserver_traffic
• dsp_impressions_by_user_segments:
• conversions_with_relevance
• sponsored_ads_traffic

 

Explanation:

The correct answer is **sponsored_ads_traffic** because this table specifically contains impression and click events from Amazon’s advertising campaigns, including Sponsored Products, Sponsored Brands, Sponsored Display, and Sponsored Television. These campaigns are part of Amazon’s advertising suite, and the **sponsored_ads_traffic** table aggregates data related to the traffic driven by these ad types, including both impressions and clicks, which are essential metrics for evaluating the performance of sponsored ads. The other options, such as conversions_with_relevance, adserver_traffic, and dsp_impressions_by_user_segments, focus on different types of data or ad-related events not directly tied to these specific campaign types.

 

 

Why is it considered a good best practice to exclude NULL user_id values from reach and frequency queries?

 

• Reach and frequency cannot be accurately determined for NULL user_id values, so this group is excluded to prevent NULL user_id values from skewing the results.
• Because NULL user_id values are deemed invalid traffic in post-impression server-side models.
• This would be redundant; records with NULL user_id values have been removed upstream of query processing anyway.

 

Explanation: The correct answer is **Reach and frequency cannot be accurately determined for NULL user_id values, so this group is excluded to prevent NULL user_id values from skewing the results** because NULL user_id values indicate that the specific user information is missing or unavailable. Since reach and frequency metrics are designed to track unique users and the frequency with which they are exposed to ads, having NULL values for user IDs makes it impossible to accurately attribute these metrics to specific individuals. Including such records would lead to inaccurate calculations, potentially distorting the results and leading to misleading conclusions. Therefore, excluding NULL user_id values ensures the integrity of the reach and frequency analysis, allowing for more accurate measurement of campaign performance.

 

Super Power Batteries, a consumer packaged goods brand, is new to AMC and wants to learn more about what tables are available to query. Where in the AMC UI can they find this information?

• Submitted queries
• Query editor
• Instance info
• Schema explorer

 

Explanation:

The correct answer is **Schema explorer** because the Schema Explorer in the AMC (Amazon Marketing Cloud) user interface provides users with a comprehensive view of all the available tables and their structure within the AMC environment. It allows users, like Super Power Batteries, to explore the different tables, fields, and relationships in order to better understand the data they can query. This tool is essential for discovering which tables are relevant to their analysis and for navigating through the available datasets. The other options, such as Submitted queries, Query editor, and Instance info, focus on different aspects of query creation or instance management but do not provide direct access to a list of all available tables like the Schema Explorer does.

 

 

Which of the following statements is true about using queries within the instructional query library?

 

• Instructional query templates cannot be modified ahead of running
• Query templates can be edited to include relevant dimensions and metrics for your use case
• Queries can be uploaded by AMC users and saved for future use

 

Explanation: The correct answer is **Query templates can be edited to include relevant dimensions and metrics for your use case** because within the Instructional Query Library (IQL) in Amazon Marketing Cloud (AMC), query templates are provided to help users get started with common types of analyses. These templates are editable, allowing users to customize them by adding or modifying dimensions, metrics, and filters to fit their specific use case. This flexibility enables users to tailor the provided templates to their unique analytical needs, ensuring that the queries align with the data they are interested in analyzing. The other options are incorrect because users can indeed modify the query templates and save them for future use, making them adaptable for ongoing analysis. Additionally, the statement that templates cannot be modified ahead of running is false, as users are encouraged to edit and adjust them before executing the queries.

 

If you want to understand more about which product or pixel your conversion events are associated with, which field in the amazon_attributed_events_* tables should you leverage?

• tracked_item
• conversion
• tracked_asin
• ad_product_type

 

Explanation:

The correct answer is **tracked_item** because the **tracked_item** field in the amazon_attributed_events_* tables is specifically used to identify the product or pixel associated with a conversion event. This field provides the information about the specific item that was tracked and resulted in a conversion, allowing you to link the conversion data back to the relevant product or pixel. This is essential for understanding which products or pixels contributed to conversions in your advertising campaigns. The other fields, such as ad_product_type, conversion, and tracked_asin, are related to different aspects of the data but do not directly provide the product or pixel association in the way that **tracked_item** does.