• SELECT campaign, COUNT (DISTINCT user_id) AS purchasers, SUM (purchases) AS purchases FROM amazon_attributed_events_by_traffic_time GROUP BY 1
• SELECT campaign, COUNT (DISTINCT user_id) AS purchasers, SUM (purchases) AS purchases FROM conversions GROUP BY 1
• SELECT campaign, COUNT (DISTINCT user_id) AS purchasers, SUM (purchases) AS purchases FROM amazon_attributed_events_by_traffic_time WHERE purchases = 1 GROUP BY 1

The correct answer is: SELECT campaign, COUNT (DISTINCT user_id) AS purchasers, SUM (purchases) AS purchases FROM amazon_attributed_events_by_traffic_time WHERE purchases = 1 GROUP BY 1

Explanation: In the context of Amazon Marketing Cloud (AMC) SQL queries and the event-level data tables (like amazon_attributed_events_by_traffic_time), the column that determines a purchase is purchases.

The key to isolating only purchase records is the WHERE clause:

• WHERE purchases = 1: This condition explicitly filters the data set to include only those rows where a purchase event occurred. In AMC’s schema, the purchases column will have a value of 1 for a record that includes an attributed purchase, and 0 or NULL for other traffic or conversion events (like impressions or clicks) that did not result in a purchase.

Without this specific WHERE clause, the query would include all records from the table, even those that were just impressions or clicks, and the resulting SUM(purchases) would still be a count of total purchases, but the underlying data rows would not be only purchase records.