Amazon Marketing Cloud

AMC Sponsored Ads Keywords Query : Enhance Keyword Targeting on Amazon

Archit Arora

27 Dec 2023

It’s no secret that keyword targeting plays a crucial role in driving the audience to our product page on Amazon. Amazon marketing cloud-sponsored ads query

But what if we told you that you can improve your Sponsored Ads keyword targeting strategy using Amazon Marketing Cloud?

Indeed, Amazon’s marketing cloud has proven to be a valuable source of data-driven insights related to products, campaigns, and targets since its launch.

In this blog post, we will help you learn how to use Sponsored Ads queries in Amazon Marketing Cloud to go beyond the basic understanding of search terms and unveil interesting insights.

In-depth Traffic and Conversion Data for Search Terms

Amazon already provides a search term report within the campaign manager for sponsored ads. This report gives us key performance metrics such as impressions, clicks, spending, sales, and more, offering a detailed view of the specific search terms that lead customers to our product page and contribute to conversions.

Now, what sets Amazon’s marketing cloud apart in terms of usefulness?

The Amazon Marketing Cloud elevates this by providing even more detailed information. It goes beyond the basics, offering insights into page views, brand halo purchases, new-to-brand purchases, and other metrics for each search term. These insights are not accessible in your standard sponsored search term report but prove invaluable for fine-tuning your Amazon keyword targeting strategy.

For instance, here is an SQL query that we used to find the detailed page views, purchases, and new-to-brand purchases for the search terms:

SELECT
  targeting AS keyword,
  customer_search_term,
  match_type,
  campaign,
  ad_product_type,
  SUM(total_detail_page_view) AS total_dpv,
  SUM(total_purchases) AS total_purchases,
	SUM(new_to_brand) AS new_to_brand,
FROM
  amazon_attributed_events_by_traffic_time
WHERE
  match_type IN('PHRASE', 'BROAD', 'EXACT')
GROUP BY
  1,
  2,
  3,
  4,
  5

Output example:

Interpretation:

Based on the above example of search term data, it can be observed that Keyword 1 and Keyword 3 have a very high new-to-brand order share, while Keyword 2 has the lowest share. Therefore, it could be used in refining the keyword strategy to drive more new-to-brand orders.

Revealing Customers' Pre-Purchase Search Insights with AMC

While the regular search term report helps you understand how customers were searching immediately before they made a purchase, understanding the complete search narrative goes beyond final purchase keywords.

With Amazon Marketing Cloud, you can understand how customers were searching before the last search that led to the attributed purchase.

Here is the instructional SQL query that you can use to retrieve this data:

WITH searches AS (
  SELECT
    DISTINCT user_id,
    customer_search_term AS search_term,
    campaign,
    ad_product_type,
    event_dt
  FROM
    TABLE(
      extend_time_window(
        'sponsored_ads_traffic',
        -- OPTIONAL UPDATE: the lookback window from the optional 30-days.
        'P30D',
        'P0D'
      )
    )
  WHERE
    match_type IN('PHRASE', 'BROAD', 'EXACT')
    AND user_id IS NOT NULL
),
searches_ranked AS (
  SELECT
    user_id,
    search_term,
    campaign,
    ad_product_type,
    event_dt,
    RANK() OVER(
      PARTITION BY user_id
      ORDER BY
        event_dt ASC
    ) AS time_rank
  FROM
    searches
),
attributed_conversions_user AS (
  SELECT
    a.user_id,
    customer_search_term AS attributed_search_term,
    search_term,
    a.campaign,
    a.ad_product_type,
    SUM(total_purchases) AS total_purchases
  FROM
    amazon_attributed_events_by_conversion_time a
    JOIN searches_ranked s ON s.user_id = a.user_id
    AND s.campaign = a.campaign
    AND s.ad_product_type = a.ad_product_type
  WHERE
    event_dt < conversion_event_dt
    AND total_purchases > 0
    AND time_rank = 1
  GROUP BY
    1,
    2,
    3,
    4,
    5
)
SELECT
  search_term AS first_search_term,
  attributed_search_term AS attributed_search_term,
  SUM(total_purchases) AS total_purchases
FROM
  attributed_conversions_user
GROUP BY
  1,
  2

Output example:

Interpretation:

In the first scenario, where customers searched solely for ‘dog toys’ as their initial and attributed search terms during the specified period, there were only 62 total purchases. In the second scenario, when customers first searched for ‘dog toys’ and then for ‘dog toys for aggressive chewers’, the number of purchases was 4.1 times higher.

How Adbrew can help you?

Introducing the all-new Amazon Marketing Cloud Dashboard!

Now, advertisers and brands without SQL expertise can effortlessly harness the full potential of AMC.

Our user-friendly platform features intuitive graphs and visualizations for various AMC queries, allowing you to analyze data seamlessly. Take quick actions directly from the analysis for a smoother and more efficient marketing process

Ready to get started with Adbrew?

Adbrew provides cutting-edge automation, expertly curated strategies, and data-driven insights for brands to thrive on Amazon.

Final Thoughts on Amazon Marketing Cloud Sponsored Keyword Query:

Analyzing customer search terms through the Amazon Marketing Cloud reveals valuable insights. It unveils the keywords that generate higher new-to-brand orders and drive “brand halo” conversions. Taking a closer look at the “first vs. attributed” search term query goes even deeper, exposing what customers searched for right before making their final purchase. Armed with this in-depth information, you can refine your marketing approaches, optimize customer engagement, and ultimately enhance the overall effectiveness of your campaigns.