vmartinez

Columns in the HIGH and VERY_HIGH aggregation threshold categories cannot be used when applying ____________ to your query.

• first-party insights
• aggregation functions such as SUM or AVG
• WHERE filters with literal (static) values
• UNION or JOIN functions

or

• WHERE filters
• JOIN functions
• third-party insights
• first-party insights

 

Explanation:

The correct answer is **WHERE filters with literal (static) values** because columns in the HIGH and VERY_HIGH aggregation threshold categories are typically derived from dynamic values or calculations that involve aggregation or other query functions. These columns cannot be used directly with **WHERE filters that apply static, literal values** because their values are not static and are calculated based on the context of the query. For example, a filter that attempts to use a literal value to restrict data based on dynamic aggregations would result in an error or incorrect results. Instead, such columns are intended to be used with more flexible query functions like aggregation or within calculations that adapt to the query context. The other options—aggregation functions, first-party insights, and UNION or JOIN functions—do not inherently conflict with the use of HIGH and VERY_HIGH threshold categories in the same way.

 

 

Which table would you leverage for a query when your objective is to understand how your current audience strategy is performing for your campaigns?

 

• dsp_impressions_by_matched_segments
• amazon_attributed_events_by_conversion_time
• conversions_with_relevance

 

Explanation: The correct answer is **dsp_impressions_by_matched_segments** because this table is specifically designed to help you understand how your current audience strategy is performing for your campaigns. It provides detailed insights into the impressions served through Amazon DSP, broken down by audience segments that have been matched to your campaigns. By using this table, you can evaluate the effectiveness of different audience segments, track engagement, and assess how well your audience targeting strategy is driving impressions and potentially conversions. The other tables, such as **conversions_with_relevance** and **amazon_attributed_events_by_conversion_time**, focus more on conversion tracking and attribution, which are important but do not directly provide insights into audience strategy performance.

 

 

Which of the following statements about paid features (beta) is false?

 

• Paid features are offered as a monthly subscription and can be managed by the administrator of your AMC account
• Paid features allow advertisers to upload their own first-party insights to better understand the shopping journey
• Paid features provide access to subscription-based tables that can be used in conjunction with the standard tables available in AMC

 

Explanation: The correct answer is **Paid features allow advertisers to upload their own first-party insights to better understand the shopping journey** because this statement is false. Paid features in Amazon Marketing Cloud (AMC) provide access to subscription-based data and insights, often from Amazon or third-party sources, but they do not directly allow advertisers to upload their own first-party data for integration within AMC. While advertisers can use their own first-party data in certain scenarios, the paid features themselves are typically focused on enhancing existing Amazon Ads data with external insights, not enabling the upload of first-party insights. The other statements are true: paid features are subscription-based and managed by the account administrator, and they provide access to additional tables that can complement the standard AMC data.

 

Where can you activate AMC rule-based audiences?

 

• Seller Central
• Amazon DSP
• Amazon Ad Server
• Amazon Clean Rooms

 

Explanation:

The correct answer is **Amazon DSP** because AMC audiences are activated within Amazon DSP (Demand-Side Platform). Amazon DSP allows advertisers to leverage audience data created in Amazon Marketing Cloud (AMC) for ad targeting in display, video, and other programmatic advertising formats across Amazon’s network. By integrating AMC audiences into DSP, advertisers can target specific user segments based on their behaviors, interests, and other attributes derived from the audience analysis in AMC. The other options, such as Amazon Clean Rooms, Seller Central, and AMC APIs, are not designed for the activation of audiences in the same way that Amazon DSP is, making DSP the correct platform for this purpose.

 

 

When determining total impressions served over a given date range, you can use dsp_impressions or dsp_views.

 

• True

 

• False

 

Explanation: The correct answer is **False** because when determining total impressions served over a given date range, you cannot simply use dsp_impressions or dsp_views alone. The dsp_impressions table tracks the number of impressions served, while dsp_views typically tracks the number of times an ad was viewed or interacted with. To accurately determine the total impressions served, a more comprehensive approach is needed that involves the correct usage of relevant tables and metrics, including filtering out duplicates and ensuring that all impression-related data is accounted for across different events. Additionally, the data in these tables might not represent the total impressions in the desired timeframe without additional context or processing.

 

What is an exploratory query?

• A query run to understand what is live within your connected Amazon Ads accounts or to quickly get campaign IDs or other values used to filter in another query
• A query that tests whether a specific audience segment or segments may prove valuable for your campaign’s key performance indicators (KPIs)
• A query that asseses the efficacy of your marketing strategy; insights from this type of query can be used to refine your Amazon Ads media mix
• A query that tests whether a specific supply source may prove valuable for your campaign’s key performance indicators (KPIs)

 

Explanation:

The correct answer is **A query run to understand what is live within your connected Amazon Ads accounts or to quickly get campaign IDs or other values used to filter in another query** because an **exploratory query** is typically used to gather quick insights or data points, such as identifying what campaigns are currently active or retrieving campaign IDs and other relevant values. These queries are not focused on detailed analysis or testing specific KPIs, but rather on exploring and understanding the data landscape, making it easier to design more targeted, in-depth queries later. The exploratory query helps users familiarize themselves with the available data, so they can decide what further information is needed for deeper analysis. The other options, while related to analysis and performance, describe queries that are more focused on specific testing or strategic assessment rather than simple data exploration.