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Amazon Marketing Cloud Certification Questions & Answers

95 questions · 0 with full explanations · Updated

The Amazon Marketing Cloud Certification covers Amazon's clean-room analytics environment: how AMC data is structured, writing SQL queries against it, and turning results such as overlap and path-to-conversion analysis into audience and media decisions.

Where to take it
Amazon Ads Learning Console
Cost
Free
Who it's for
Analysts and advanced Amazon advertisers comfortable with SQL.

How to pass the Amazon Marketing Cloud exam

  • Learn the main AMC tables and what each event type represents.
  • Practise aggregation and filtering functions, since query questions are common.
  • Understand AMC's privacy thresholds and why small result sets are withheld.

Topics covered

Amazon Ads (61)Analytics & Reporting (16)Audiences & Targeting (13)Attribution Models (5)

Recently updated questions

  1. 1Columns in the HIGH and VERY_HIGH aggregation threshold categories cannot be used when applying ____________ to your query.
  2. 2SELECT supply_source, SUM (total_cost)/100000000 AS total_cost_dollars, ((SUM (total_cost)/100000000)/SUM (impressions)) *1000 AS avg_cpm, SUM (impressions) AS impressions FROM dsp_inventory GROUP BY 1 SELECT supply_source, SUM (total_cost)/100000 AS total_cost_dollars, ((SUM (total_cost)/100000)/SUM (impressions)) *1000 AS avg_cpm, SUM (impressions) AS impressions FROM dsp_impressions GROUP BY 1,2 SELECT supply_source, SUM (total_cost)/100000 AS total_cost_dollars, ((SUM (total_cost)/100000)/SUM (impressions)) *1000 AS avg_cpm, SUM (impressions) AS impressions FROM dsp_impressions GROUP BY 1 The correct answer is: SELECT supply_source, SUM (total_cost)/100000 AS total_cost_dollars, ((SUM (total_cost)/100000)/SUM (impressions)) *1000 AS avg_cpm, SUM (impressions) AS impressions FROM dsp_impressions GROUP BY 1 Explanation: That’s the correct query. Here is an explanation of the adaptation and why it works: The adapted query focuses on aggregating the desired metrics at the supply_source level, utilizing fields available in the dsp_impressions table: SQL SELECT supply_source, SUM(total_cost) / 100000 AS total_cost_dollars, ((SUM(total_cost) / 100000) / SUM(impressions)) * 1000 AS avg_cpm, SUM(impressions) AS impressions FROM dsp_impressions GROUP BY 1 🔍 Explanation of Changes The core principle of the adaptation is to replace the previous grouping dimensions with the single dimension required: supply_source .Multiple correct
  3. 3SELECT total_impressions SUM (impressions) AS device_type FROM campaign, supply_source GROUP BY 1,2,3 SELECT campaign, supply_source, SUM (impressions) AS impressions FROM device_type GROUP BY 1,2 SELECT campaign, supply_source, device_type, SUM (impressions) AS impressions FROM dsp_impressions GROUP BY 1,2,3 The correct answer is: SELECT campaign, supply_source, device_type, SUM (impressions) AS impressions FROM dsp_impressions GROUP BY 1,2,3 Explanation: The correct query to get the total impressions delivered per campaign, per supply source, and per device type is: SQL SELECT campaign, supply_source, device_type, SUM(impressions) AS impressions FROM dsp_impressions GROUP BY 1, 2, 3 ✅ Explanation of the Query This is a standard and efficient SQL query structure for use in Amazon Marketing Cloud (AMC) .Multiple correct
  4. 4Since the amazon_attributed_events_* tables contain ad-attributed conversions across all of your Amazon Ads media, you can aggregate them by sponsored ads vs. Amazon DSP using the __________.
  5. 5Why is the AMC sandbox a helpful environment for testing queries?

All Amazon Marketing Cloud questions

  1. 1Columns in the HIGH and VERY_HIGH aggregation threshold categories cannot be used when applying ____________ to your query.
  2. 2SELECT supply_source, SUM (total_cost)/100000000 AS total_cost_dollars, ((SUM (total_cost)/100000000)/SUM (impressions)) *1000 AS avg_cpm, SUM (impressions) AS impressions FROM dsp_inventory GROUP BY 1 SELECT supply_source, SUM (total_cost)/100000 AS total_cost_dollars, ((SUM (total_cost)/100000)/SUM (impressions)) *1000 AS avg_cpm, SUM (impressions) AS impressions FROM dsp_impressions GROUP BY 1,2 SELECT supply_source, SUM (total_cost)/100000 AS total_cost_dollars, ((SUM (total_cost)/100000)/SUM (impressions)) *1000 AS avg_cpm, SUM (impressions) AS impressions FROM dsp_impressions GROUP BY 1 The correct answer is: SELECT supply_source, SUM (total_cost)/100000 AS total_cost_dollars, ((SUM (total_cost)/100000)/SUM (impressions)) *1000 AS avg_cpm, SUM (impressions) AS impressions FROM dsp_impressions GROUP BY 1 Explanation: That’s the correct query. Here is an explanation of the adaptation and why it works: The adapted query focuses on aggregating the desired metrics at the supply_source level, utilizing fields available in the dsp_impressions table: SQL SELECT supply_source, SUM(total_cost) / 100000 AS total_cost_dollars, ((SUM(total_cost) / 100000) / SUM(impressions)) * 1000 AS avg_cpm, SUM(impressions) AS impressions FROM dsp_impressions GROUP BY 1 🔍 Explanation of Changes The core principle of the adaptation is to replace the previous grouping dimensions with the single dimension required: supply_source .Multiple correct
  3. 3SELECT total_impressions SUM (impressions) AS device_type FROM campaign, supply_source GROUP BY 1,2,3 SELECT campaign, supply_source, SUM (impressions) AS impressions FROM device_type GROUP BY 1,2 SELECT campaign, supply_source, device_type, SUM (impressions) AS impressions FROM dsp_impressions GROUP BY 1,2,3 The correct answer is: SELECT campaign, supply_source, device_type, SUM (impressions) AS impressions FROM dsp_impressions GROUP BY 1,2,3 Explanation: The correct query to get the total impressions delivered per campaign, per supply source, and per device type is: SQL SELECT campaign, supply_source, device_type, SUM(impressions) AS impressions FROM dsp_impressions GROUP BY 1, 2, 3 ✅ Explanation of the Query This is a standard and efficient SQL query structure for use in Amazon Marketing Cloud (AMC) .Multiple correct
  4. 4Since the amazon_attributed_events_* tables contain ad-attributed conversions across all of your Amazon Ads media, you can aggregate them by sponsored ads vs. Amazon DSP using the __________.
  5. 5Why is the AMC sandbox a helpful environment for testing queries?
  6. 6How long can AMC accrue and retain Amazon Ads events?
  7. 7Which function can be used to append a string to ID fields (i.e., campaign_id) to prevent issues when reading the values in Excel?
  8. 8Performance reporting, such as Path to Conversion reporting, can be constrained to specific conversion events (e.g. purchases of a specific ASIN).
  9. 9Which action can be used to determine if NULL values are a natural occurrence within your report or the result of aggregation thresholds?
  10. 10Where can you find the details of the entities (Amazon DSP, sponsored ads, etc.) linked to an AMC Instance?
  11. 11Considering the amazon_attributed_events_ tables contain ad-attributed conversions across all of your Amazon Ads media, which of the following fields would allow you to aggregate them by sponsored ads vs. Amazon DSP?
  12. 12Which field in the amazon_attributed_events_ tables should you leverage if you want to understand more about which product or pixel your conversion events are associated with?
  13. 13Which panel within the AMC UI contains a repository of Amazon-authored SQL templates along with use cases, instructions and examples of query results.
  14. 14You can activate AMC rule-based audiences on _____________.
  15. 15Developers can access AMC APIs via the Amazon Ads API gateway.
  16. 16You are writing a query and would like to know the total impressions that have been delivered per campaign, per supply_source, and per device_type. Which of the following represents how you should write the query?
  17. 17Which statement about rule-based audiences is incorrect?
  18. 18Which of the following statements about the amazon_attributed_events_* tables is true.
  19. 19Which of these statements is false regarding the amazon_attributed_events_by_conversion_time table?
  20. 20Which of the following statements about AMC lookalike (LAL) audiences is false?
  21. 21Which of the following statements about paid features (beta) is false?
  22. 22Custom parameters help make queries more reusable because they __________.
  23. 23Cost and fee fields are always reported in microcents.
  24. 24If 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?
  25. 25The ___________ function can be used to append a string to ID fields (such as campaign_id), preventing issues reading the accurate ID values within Excel.
  26. 26A 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.
  27. 27When analyzing the relationship between frequency and purchase rate, what actionable insight can you leverage for campaign optimization?
  28. 28Which of these exploratory queries would allow you to generate a list of all Amazon DSP creative active during your chosen time window?
  29. 29Why should you wait until 14 days after the end date of your query date range to run analyses that leverage the amazon_attributed_events_by_traffic_time table?
  30. 30What is the Amazon Ads attribution lookback window?
  31. 31Which of these is NOT a method of optimizing your AMC SQL?
  32. 32user_id values cannot be viewed in the AMC user interface or downloaded from AMC.
  33. 33Why would this query fail? SELECT campaign, SUM(impressions) AS impressions FROM dsp_impressions
  34. 34Clicks are considered conversion events and appear as individual records within the amazon_attributed_events_* tables.
  35. 35The _____________ field in the conversions_with_relevance table categorizes the relationship between the conversion event and the campaign it is relevant to.
  36. 36There is no universal methodology or join key that can be used to combine tables in all query scenarios.
  37. 37What is the max window over which AMC can accrue Amazon Ads events?
  38. 38What is an exploratory query?
  39. 39Which of these statements is true regarding recurring query automation?
  40. 40To minimize the number of values rendered NULL due to aggregation thresholds, you can:
  41. 41How can you determine if NULL values are the result of aggregation thresholds or a natural occurrence within your report?
  42. 42Which environment allows you to inspect AMC tables at record level?
  43. 43Why is it considered a good best practice to exclude NULL user_id values from reach and frequency queries?
  44. 44Which of these use cases can be achieved when using Amazon Ads events in conjunction with first-party inputs?
  45. 45When determining total impressions served over a given date range, you can use dsp_impressions or dsp_views.
  46. 46Rule-based audience creation leverages a separate set of tables than those utilized for AMC reporting.
  47. 47Conversions measured via Events Manager can be made available for querying in AMC.
  48. 48What is a primary usage of the UNION ALL function in AMC queries?
  49. 49You can use a _________ filter to limit your query results based on one or more conditions.
  50. 50What are the two ways to access AMC?

Frequently asked questions

Do I need to know SQL?

Yes, a working knowledge of SQL helps. Several questions ask which functions or query structure produce a given result.

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