vmartinez

 

What is required to access AMC APIs?

 

• Connecting your organization’s AWS account to AMC
• Requesting access from Amazon customer service
• Installing a plugin in your browser

 

 

Which signals are not available within AMC?

 

• Ad-relevant conversions with a 60-day lookback window
• Ad-attributed conversions with a 14-day lookback window
• Ad-relevant conversions with a 28-day lookback window

 

Explanation: The correct answer is **Ad-relevant conversions with a 60-day lookback window** because within Amazon Marketing Cloud (AMC), ad-relevant conversions are typically available with a 28-day or 14-day lookback window, but not with a 60-day lookback window. The 14-day lookback window is commonly used to track ad-attributed conversions, capturing relevant customer actions that occur within that period after exposure to an ad. A 28-day window is also used for certain types of conversions, but a 60-day lookback window is not part of the standard data available within AMC for ad-relevant conversions. This limitation ensures that data remains manageable and relevant to shorter-term marketing strategies and trends.

 

The _________ field contains the pseudonymous ad identifier associated with a given impression. It is often used in calculations to understand unique reach volumes.

 

• purchases
• user_id
• request_tag
• halo_code

 

Explanation: The correct answer is **user_id** because the **user_id** field contains the pseudonymous ad identifier associated with a given impression. This identifier is used to track unique users across multiple impressions, allowing for the calculation of unique reach volumes. By using **user_id**, advertisers can understand how many distinct individuals were exposed to an ad, which helps in analyzing the reach of a campaign and preventing double-counting of impressions for the same user. This field is essential for measuring unique reach and understanding how many unique customers interact with an ad. The other options, such as request_tag, purchases, and halo_code, are related to different aspects of campaign tracking but do not specifically serve as the pseudonymous ad identifier for unique reach analysis.

 

 

Which two functions can be used together to filter records based on presence of a string within a column’s values?

 

• WHERE, SIMILAR TO
• WHERE, COLLECT
• WHERE, LIKE
• WHERE, CONCAT

 

Explanation: The correct answer is **WHERE, SIMILAR TO** because the **WHERE** clause is used to filter records based on specific conditions, and the **SIMILAR TO** function in SQL allows for pattern matching with more advanced regular expression-like syntax compared to **LIKE**. When combined, **WHERE, SIMILAR TO** can filter records based on the presence of a string or pattern within a column’s values, making it more flexible for complex string matching scenarios. This combination enables more precise filtering of records by allowing patterns to be specified in a more robust way. The **WHERE, LIKE** combination is also commonly used, but **SIMILAR TO** provides greater flexibility for pattern matching. The other options, **COLLECT** and **CONCAT**, do not serve the purpose of filtering based on string presence within a column.

 

If you run multiple Amazon DSP and sponsored ads campaigns and reached similar audiences, which query can help you understand your customers’ conversion paths that have the highest conversion rate?

• Path to Conversion by Campaign Groups
• Audience Overlap Analysis
• Sponsored Products and DSP Display Overlap

 

Explanation:

The correct answer is **Path to Conversion by Campaign Groups** because this query helps analyze the customer journey by identifying the most effective conversion paths that lead to high conversion rates across multiple Amazon DSP and sponsored ads campaigns. By grouping campaigns together, the query provides insights into how different campaign types contribute to conversions, allowing advertisers to see which combinations of DSP and sponsored ads are most effective in driving conversions. This analysis helps in understanding how customers interact with various ads and the sequence of engagements that lead to successful conversions. The other options, such as Sponsored Products and DSP Display Overlap or Audience Overlap Analysis, focus on audience reach and overlap but do not provide the same detailed analysis of conversion paths.

 

A single on-Amazon transaction that includes multiple ASINs from your brand will be represented by a single conversion event within each of the amazon_attributed_events_* tables.

• True
• False

 

Explanation:

The correct answer is **False** because a single on-Amazon transaction that includes multiple ASINs from the same brand will typically be represented by multiple conversion events in the amazon_attributed_events_* tables. Each ASIN within the transaction is considered an individual product and will have its own conversion event recorded, even though they are part of the same transaction. This ensures that the attribution data for each individual ASIN is accurately captured, providing insights into which specific products contributed to the overall conversion, rather than grouping them under a single conversion event for the entire transaction.