Google Merchant Center top brands table

Overview

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 .

The data is written to a table named BestSellers_TopBrands_ MERCHANT_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

Query examples

Top brands for a given category and country

The following SQL query returns top brands for the Smartphones category in the US.

 SELECT 
  
 rank 
 , 
  
 previous_rank 
 , 
  
 brand 
 FROM 
  
  dataset 
 
 . 
 BestSellers_TopBrands_ merchant_id 
 
 WHERE 
  
 _PARTITIONDATE 
  
 = 
  
 ' YYYY-MM-DD 
' 
  
 AND 
  
 ranking_category 
  
 = 
  
 267 
  
 /*Smartphones*/ 
  
 AND 
  
 ranking_country 
  
 = 
  
 'US' 
 ORDER 
  
 BY 
  
 rank

Products of top brands in your inventory

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

  
 WITH 
  
 latest_top_brands 
  
 AS 
  
 ( 
  
 SELECT 
  
 * 
  
 FROM 
  
  dataset 
 
 . 
 BestSellers_TopBrands_ merchant_id 
 
  
 WHERE 
  
 _PARTITIONDATE 
  
 = 
  
 ' YYYY-MM-DD 
' 
  
 ), 
  
 latest_products 
  
 AS 
  
 ( 
  
 SELECT 
  
 product 
 . 
 * 
 , 
  
 product_category_id 
  
 FROM 
  
  dataset 
 
 . 
 Products_ merchant_id 
 
  
 AS 
  
 product 
 , 
  
 UNNEST 
 ( 
 product 
 . 
 google_product_category_ids 
 ) 
  
 AS 
  
 product_category_id 
 , 
  
 UNNEST 
 ( 
 destinations 
 ) 
  
 AS 
  
 destination 
 , 
  
 UNNEST 
 ( 
 destination 
 . 
 approved_countries 
 ) 
  
 AS 
  
 approved_country 
  
 WHERE 
  
 _PARTITIONDATE 
  
 = 
  
 ' YYYY-MM-DD 
' 
  
 ) 
  
 SELECT 
  
 top_brands 
 . 
 brand 
 , 
  
 ( 
 SELECT 
  
 name 
  
 FROM 
  
 top_brands 
 . 
 ranking_category_path 
  
 WHERE 
  
 locale 
  
 = 
  
 'en-US' 
 ) 
  
 AS 
  
 ranking_category 
 , 
  
 top_brands 
 . 
 ranking_country 
 , 
  
 top_brands 
 . 
 rank 
 , 
  
 products 
 . 
 product_id 
 , 
  
 products 
 . 
 title 
  
 FROM 
  
 latest_top_brands 
  
 AS 
  
 top_brands 
  
 INNER 
  
 JOIN 
  
 latest_products 
  
 AS 
  
 products 
  
 ON 
  
 top_brands 
 . 
 google_brand_id 
  
 = 
  
 products 
 . 
 google_brand_id 
  
 AND 
  
 top_brands 
 . 
 ranking_category 
  
 = 
  
 product_category_id 
  
 AND 
  
 top_brands 
 . 
 ranking_country 
  
 = 
  
 products 
 . 
 approved_country