Table Name:
brand_search_terms_by_asin
The Brand Analytics Top Search Terms table helps brand-registered vendors and sellers see their share of clicks and conversions by ASIN by search term. You provide an ASIN, and Amazon provides the top search terms where your ASIN was one of the top 3 products. It is mainly used for keyword research and competitive monitoring.
Business questions & scenarios
What is this data useful for?
- Search trends: How are this item’s top search terms changing over time? What terms are becoming less relevant?
- Competitive monitoring: What brands earn the most clicks on my terms? What terms do my competitors’ products rank for and how do they perform?
- Conversion opportunities: For what term/ASIN combinations do we have high click share, but low conversion share?
- Retail Media: What terms should we spend more money on? To promote which ASINs?
Schema & update details
UI Report path | |
Amazon update frequency | Weekly, with up to 24-48 hour latency
Monthly, with up to 24-48 hour latency |
Reason update frequency | Weekly
Monthly |
Granularity [?] | 1 row per:
-_partneruuid
- custom_search_asin
- date
- period
- search_term |
Historical data & change management
Time Period | WEEKLY | MONTHLY |
History available from Amazon | 52 weeks | 12 months |
Reason lookback period | 1 week | 1 month |
We perform a historical backfill when you subscribe. ASINs may be changed once per month. Newly-added ASINs will begin receiving weekly updates.
Data dictionary: fields in this table
Table & data nuances
- Amazon will provide data for any ASIN, not just ones registered to your brand.
- “Search Frequency Rank” (
search_frequency_rank
) shows how common the search term is for all of Amazon, not a specific ASIN. - Unlike Search Query Performance, this data set includes relative data (rank, share) instead of actuals.
- Amazon provides
How to query this table
The example query below will provide all available weekly data for your account.
- Change
‘WEEKLY’
in the where clause to‘MONTHLY’
if needed. - To filter to a particular ASIN, add a filter to the where clause, e.g.
and custom__search_asin = 'B123456789’
SELECT
_partneruuid,
date,
period,
search_term,
search_frequency_rank,
no1_clicked_brand,
no2_clicked_brand,
no3_clicked_brand,
no1_clicked_category,
no2_clicked_category,
no3_clicked_category,
no1_clicked_asin,
no1_product_title,
no1_click_share,
no1_conversion_share,
no2_clicked_asin,
no2_product_title,
no2_click_share,
no2_conversion_share,
no3_clicked_asin,
no3_product_title,
no3_click_share,
no3_conversion_share
FROM brand_search_terms_asin
-- change period to MONTHLY below for monthly data
where period = 'WEEKLY'
Example query output
_partneruuid | date | period | search_term | search_frequency_rank | no1_clicked_brand | no2_clicked_brand | no3_clicked_brand | no1_clicked_category | no2_clicked_category | no3_clicked_category | no1_clicked_asin | no1_product_title | no1_click_share | no1_conversion_share | no2_clicked_asin | no2_product_title | no2_click_share | no2_conversion_share | no3_clicked_asin | no3_product_title | no3_click_share | no3_conversion_share |
abcde12345 | 12/3/2023 0:00 | WEEKLY | garden chairs | 145040 | Brand Z | Brand X | Brand Y | Home | B00000001 | Prod Title 1 | 6.38 | 1.1 | B000000011 | Prod Title 11 | 4.14 | 2.2 | B00000021 | Product Title 31 | 3.45 | 1.1 | ||
abcde12345 | 2/4/2024 0:00 | WEEKLY | beach buckets | 23768 | Brand X | Brand Y | Brand Z | Home | B00000002 | Prod Title 2 | 19.59 | 5.12 | B000000012 | Prod Title 12 | 14.33 | 5.12 | B00000022 | Product Title 32 | 6.53 | 1.57 | ||
abcde12345 | 2/4/2024 0:00 | WEEKLY | garden buckets | 25185 | Brand X | Brand Y | Brand Z | Home | Kitchen | B00000003 | Prod Title 3 | 21.61 | 8.77 | B000000013 | Prod Title 13 | 10.73 | 2.63 | B00000023 | Product Title 33 | 10.26 | 0.88 | |
abcde12345 | 1/14/2024 0:00 | WEEKLY | garden beach | 108492 | Brand Y | Brand Z | Brand X | Home | B00000004 | Prod Title 4 | 30.77 | 3.51 | B000000014 | Prod Title 14 | 7.86 | 0 | B00000024 | Product Title 34 | 5.35 | 0 | ||
abcde12345 | 1/14/2024 0:00 | WEEKLY | the beach | 190954 | Brand Z | Brand X | Brand Y | Home | B00000005 | Prod Title 5 | 22.83 | 18.52 | B000000015 | Prod Title 15 | 13.01 | 1.23 | B00000025 | Product Title 35 | 7.51 | 2.47 | ||
abcde12345 | 1/14/2024 0:00 | WEEKLY | gardening on the beach | 197340 | Brand Z | Brand X | Brand Y | Home | Outdoors | B00000006 | Prod Title 6 | 7.16 | 2.17 | B000000016 | Prod Title 16 | 4.48 | 2.17 | B00000026 | Product Title 36 | 2.99 | 2.17 | |
abcde12345 | 2/4/2024 0:00 | WEEKLY | beach in the garden | 27133 | Brand X | Brand Y | Brand Z | Home | Kitchen | Beauty | B00000007 | Prod Title 7 | 3.72 | 0 | B000000017 | Prod Title 17 | 3.62 | 0 | B00000027 | Product Title 37 | 2.75 | 1.18 |
abcde12345 | 12/3/2023 0:00 | WEEKLY | gardening at night | 148242 | Brand X | Brand Y | Brand Z | Home | B00000008 | Prod Title 8 | 30.28 | 3.85 | B000000018 | Prod Title 18 | 5.99 | 1.92 | B00000028 | Product Title 38 | 4.4 | 0 | ||
abcde12345 | 2/4/2024 0:00 | WEEKLY | sand bucket | 47090 | Brand Z | Brand X | Brand Y | Home | Baby | B00000009 | Prod Title 9 | 21.68 | 3.38 | B000000019 | Prod Title 19 | 15.12 | 0 | B00000029 | Product Title 39 | 5.73 | 1.35 | |
abcde12345 | 3/3/2024 0:00 | WEEKLY | beach blanket | 1956505 | Brand Z | Brand X | Brand Y | Home | B00000010 | Prod Title 10 | 25 | 0 | B000000020 | Prod Title 20 | 9.38 | 0 | B00000030 | Product Title 40 | 9.38 | 0 |
- Business questions & scenarios
- Schema & update details
- Historical data & change management
- Data dictionary: fields in this table
- Table & data nuances
- How to query this table
- Example query output
- Related pages