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.

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

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