Google Merchant Center top brands table

Overview

Caution: BigQuery will no longer support the report that exports the Top brands table on July 1st, 2025. We recommend that you migrate to use the new Best Sellers report instead.

Best sellers data helps merchants understand the most popular brands and products in Shopping ads and unpaid listings. For more information about best sellers, see the description in Supported reports.

If you are using an individual Merchant ID, the data is written to a table named BestSellers_TopBrands_MERCHANT_ID. If you are using a multi-client account (MCA), the data is written to a table named BestSellers_TopBrands_AGGREGATOR_ID.

Schema

The BestSellers_TopBrands_ table has the following schema:

Column	BigQuery data type	Description	Example data
rank_timestamp	TIMESTAMP	Date and time when the rank was published.	2020-05-30 00:00:00 UTC
rank_id	STRING	Unique identifier for the rank.	2020-05-30:FR:264:120:brand
rank	INTEGER	The popularity rank of the brand on Shopping ads and unpaid listings for the ranking_country and ranking_category. Popularity is based on the estimated number of products sold. The rank updates daily. The data included in metrics might be delayed by up 2 days.	120
previous_rank	INTEGER	The change in rank over the previous 7 days.	86
ranking_country	STRING	Country code used for ranking.	FR
ranking_category	INTEGER	Google product category ID used for ranking.	264
ranking_category_path	RECORD, REPEATED	The full path of the Google product category used for ranking in each locale.
ranking_category_path.locale	STRING	The locale of the category path.	en-US
ranking_category_path.name	STRING	A human-readable name for the category path.	Electronics > Communications > Telephony > Mobile Phone Accessories
relative_demand	RECORD	A brand's estimated demand in relation to the brand with the highest popularity rank in the same category and country.
relative_demand.bucket	STRING		Very high
relative_demand.min	INTEGER		51
relative_demand.max	INTEGER		100
previous_relative_demand	RECORD	A brand's estimated demand in relation to the brand with the highest popularity rank in the same category and country over the previous 7 days.
previous_relative_demand.bucket	STRING		Very high
previous_relative_demand.min	INTEGER		51
previous_relative_demand.max	INTEGER		100
brand	STRING	Brand of the item.	Example Brand Name
google_brand_id	STRING	Google brand ID of the item.	11887454107284768325