AC

How would you adapt this query to limit results to Sponsored Products keyword targeting only? SELECT ad_product_type, targeting, customer_search_term, match_type, SUM (spend)/100000000 AS total_cost_dollars, ((SUM (spend)/100000000)/SUM (impressions)) *1000 AS avg_cpm, SUM (impressions) AS impressions, SUM (clicks) AS clicks, (SUM (clicks)/SUM (impressions)) AS ctr FROM sponsored_ads_traffic WHERE match_type IN (‘PHRASE’, ‘BROAD’, ‘EXACT’) GROUP BY 1,2,3,4

Adjust FROM statement to: FROM sponsored_products
Add LIMIT clause: LIMIT sponsored_products
Adjust SELECT statement to include the sponsored_products field
Adjust WHERE statement to: WHERE match_type IN (‘PHRASE’, ‘BROAD’, ‘EXACT’) AND ad_product_type = ‘sponsored_products’

Correct Answer

Adjust WHERE statement to: WHERE match_type IN (‘PHRASE’, ‘BROAD’, ‘EXACT’) AND ad_product_type = ‘sponsored_products’

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About the Amazon Marketing Cloud Certification

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.

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Related Amazon Marketing Cloud questions

  1. 1SELECT 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
  2. 2SELECT 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
  3. 3If 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?
  4. 4Which of these analyses can be accomplished with an overlap query?
  5. 5AMC audiences is an API-only feature.
  6. 6Which table should you use in a query meant to help you choose new Amazon audiences that may benefit your Amazon DSP campaign performance?