Google Merchant Center top products

Overview

Caution: BigQuery will no longer support this version of the Top products 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. For more information about best sellers, see the description in Supported Reports.

The data is written to a table named BestSellers_TopProducts_MERCHANT_ID if you are using an individual Merchant ID, or BestSellers_TopProducts_AGGREGATOR_ID if you're using an MCA account.

Schema

The BestSellers_TopProducts_ table has the following schema:

Column	BigQuery data type	Description	Sample field
rank_timestamp	TIMESTAMP	Date and time when the rank was published.	2020-03-14 00:00:00 UTC
rank_id	STRING	Rank identifier to join against the Product Inventory table.	2020-03-14:AU:100:2:product
rank	INTEGER	The popularity rank of the product on Shopping ads 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.	2
previous_rank	INTEGER	The change in rank over the previous 7 days.	4
ranking_country	STRING	Country code used for ranking.	AU
ranking_category	INTEGER	Google product category ID used for ranking.	5181
ranking_category_path	RECORD, REPEATED	Google product category full path for each locale used for ranking.
ranking_category_path.locale	STRING		en-AU
ranking_category_path.name	STRING		Luggage & Bags
relative_demand	RECORD	A product's estimated demand in relation to the product 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 product's estimated demand in relation to the product 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
product_title	RECORD, REPEATED	Product title.
product_title.locale	STRING		en-AU
product_title.name	STRING		ExampleBrand Backpack
gtins	STRING, REPEATED	Global Trade Item Number (GTIN).	07392158680955
brand	STRING	Brand of the item.	ExampleBrand
google_brand_id	STRING	Google brand ID of the item.	11887454107284768328
google_product_category	INTEGER	Google product category ID of the item.	100
google_product_category_path	RECORD, REPEATED	Google product category full path of the item.
google_product_category_path.locale	STRING		en-US
google_product_category_path.name	STRING		Luggage & Bags > Backpacks
price_range	RECORD	Price range: lower and upper (with no decimals) and currency. The price does not include shipping costs.	n/a
price_range.min	NUMERIC		115
price_range.max	NUMERIC		147
price_range.currency	STRING		AUD

Understanding the data

• Ranking categories are subject to change over time.
• The Google product category in the BestSellers_TopProducts_Inventory_ table might be different from the Google Product Category in the Products_ table. The Products_ table surfaces a retailer provided value of Google product category.
• For products in your inventory, the price range in BestSellers_TopProducts_ might differ from the Products_PriceBenchmarks_ table. Price benchmarks metrics are calculated over a different time period. The price ranges in BestSellers_TopProducts_ reflect prices of different variants of the product, whereas the price ranges in Products_PriceBenchmarks_ only refer to a single variant.
• Some products in your inventory might not have a rank for each category in the path. We limit the number of products per category to 10,000, and in some sub-categories we don't publish any ranking.

Example

Products might have a rank for each category within the product category path. For example, a Google Pixel 4 phone is classified as Electronics > Communications > Telephony > Mobile Phones. The Pixel 4 will have a separate ranking for Electronics, Communications, Telephony, and Mobile Phones. Use ranking_category_path in addition to ranking_country to determine the depth of category that you want to see a ranking for.

In the example below, an ExampleBrand Backpack contains a separate ranking for both the Luggage & Bags and Backpacks categories. Select "Backpacks" and "AU" to see what its ranking is in Australia in the Backpacks category.

Ranking for Luggage & Bags

product_title	ExampleBrand Backpack
ranking_country	AU
ranking_category	5181
ranking_category_path	Luggage & Bags
Rank	40
google_product_category	100
google_product_category_path	Luggage & Bags > Backpacks

Ranking for Luggage & Bags > Backpacks

product_title	ExampleBrand Backpack
ranking_country	AU
ranking_category	100
ranking_category_path	Luggage & Bags > Backpacks
rank	4
google_product_category	100
google_product_category_path	Luggage & Bags > Backpacks