Google Merchant Center top brands table

Overview

Caution: BigQuery will no longer support the report that exports theTop brands table on September 1, 2025. We recommend that you migrate to use the new best sellers reportinstead. For more information about migrating to the new report, seeMigrate the best sellers report.

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

The data is written to a table namedBestSellers_TopBrands_MERCHANT_ID.

Schema

TheBestSellers_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 theGoogle 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

Query examples

Top brands for a given category and country

The following SQL query returns top brands for theSmartphones category inthe US.

SELECTrank,previous_rank,brandFROMdataset.BestSellers_TopBrands_merchant_idWHERE_PARTITIONDATE='YYYY-MM-DD'ANDranking_category=267/*Smartphones*/ANDranking_country='US'ORDERBYrank

Note: For more information about product categories, including a full list ofcategory codes, see Definition:google_product_category.

Products of top brands in your inventory

The following SQL query returns a list of products in your inventory from topbrands, listed by category and country.

WITHlatest_top_brandsAS(SELECT*FROMdataset.BestSellers_TopBrands_merchant_idWHERE_PARTITIONDATE='YYYY-MM-DD'),latest_productsAS(SELECTproduct.*,product_category_idFROMdataset.Products_merchant_idASproduct,UNNEST(product.google_product_category_ids)ASproduct_category_id,UNNEST(destinations)ASdestination,UNNEST(destination.approved_countries)ASapproved_countryWHERE_PARTITIONDATE='YYYY-MM-DD')SELECTtop_brands.brand,(SELECTnameFROMtop_brands.ranking_category_pathWHERElocale='en-US')ASranking_category,top_brands.ranking_country,top_brands.rank,products.product_id,products.titleFROMlatest_top_brandsAStop_brandsINNERJOINlatest_productsASproductsONtop_brands.google_brand_id=products.google_brand_idANDtop_brands.ranking_category=product_category_idANDtop_brands.ranking_country=products.approved_country