Consumer Edge Web Scraping Consumer Data | SKU-Level Purchase Data | 350M Transactions, 11K Brands, 190 Countries, 11 Years History

#	as_of	reporting_period	observation_type	model_year	make	is_new	store_region	comparability	days_on_site	initial_value	final_value	units
1	xxxxxxxxxx	Xxxxxxxxx	xxxxxx	xxxxxxxxxx	Xxxxx	Xxxxxx	Xxxxxxxxxx	Xxxxxx	Xxxxxxxxx	Xxxxxxxxxx	xxxxxxxxx	Xxxxxxxxx
2	xxxxxxxxx	Xxxxxxx	xxxxxx	Xxxxx	xxxxxxxxxx	xxxxxx	Xxxxxxxxxx	xxxxxx	Xxxxx	Xxxxxx	xxxxx	xxxxxxxx
3	xxxxxxx	Xxxxx	Xxxxxxxx	xxxxxxxxxx	xxxxxx	Xxxxxxxxx	xxxxxx	Xxxxxxxxx	Xxxxxxxxx	xxxxxxxxxx	Xxxxxx	Xxxxx
4	xxxxxx	xxxxxxx	xxxxxxx	Xxxxx	xxxxxx	Xxxxxxxxxx	xxxxxxxx	xxxxxx	Xxxxx	Xxxxxxx	xxxxxx	Xxxxxxxx
5	Xxxxxxx	Xxxxx	xxxxxx	xxxxxxxxxx	Xxxxx	xxxxxxxxxx	xxxxxxxxx	Xxxxxxx	xxxxxxxx	xxxxxxxx	Xxxxxxxxxx	Xxxxxxxx
6	Xxxxxxxx	xxxxxxxxx	Xxxxxxxxxx	Xxxxxx	Xxxxxxxxx	xxxxx	xxxxxxx	xxxxxxxxx	Xxxxxx	Xxxxxxx	Xxxxxxxxx	xxxxxxxxx
7	xxxxxxxxx	Xxxxx	xxxxxxxx	Xxxxxxx	xxxxxxxxx	Xxxxxxx	xxxxx	Xxxxxxx	xxxxxxx	Xxxxx	xxxxxxxxxx	Xxxxxxx
8	Xxxxx	xxxxxxxxxx	Xxxxxx	xxxxxx	Xxxxxxxxx	xxxxx	Xxxxxxxxxx	xxxxxx	xxxxx	xxxxxxxx	Xxxxxx	Xxxxxxxxxx
9	xxxxxxxxx	Xxxxxxxxxx	xxxxxxxx	xxxxx	Xxxxxx	xxxxxxxxxx	xxxxxxxxx	xxxxx	xxxxx	xxxxxxxx	xxxxxx	Xxxxxxxxxx
10	xxxxxxxxxx	Xxxxx	xxxxxxx	Xxxxxxxx	Xxxxxxx	xxxxx	xxxxxxxx	xxxxxxxxxx	Xxxxxx	xxxxxxxxx	Xxxxx	xxxxx
...	xxxxxxxxx	xxxxxxx	Xxxxxxxxx	Xxxxxxx	xxxxxxxxxx	Xxxxx	xxxxxxxxx	xxxxxxx	Xxxxxx	xxxxxxxxx	xxxxx	Xxxxxxx

#	as_of	reporting_period	observation_type	model_year	make	body_type	irc_location	days_on_site	initial_value	final_value	units
1	xxxxxxxxxx	Xxxxxxxxx	xxxxxx	xxxxxxxxxx	Xxxxx	Xxxxxx	Xxxxxxxxxx	Xxxxxx	Xxxxxxxxx	Xxxxxxxxxx	xxxxxxxxx
2	Xxxxxxxxx	xxxxxxxxx	Xxxxxxx	xxxxxx	Xxxxx	xxxxxxxxxx	xxxxxx	Xxxxxxxxxx	xxxxxx	Xxxxx	Xxxxxx
3	xxxxx	xxxxxxxx	xxxxxxx	Xxxxx	Xxxxxxxx	xxxxxxxxxx	xxxxxx	Xxxxxxxxx	xxxxxx	Xxxxxxxxx	Xxxxxxxxx
4	xxxxxxxxxx	Xxxxxx	Xxxxx	xxxxxx	xxxxxxx	xxxxxxx	Xxxxx	xxxxxx	Xxxxxxxxxx	xxxxxxxx	xxxxxx
5	Xxxxx	Xxxxxxx	xxxxxx	Xxxxxxxx	Xxxxxxx	Xxxxx	xxxxxx	xxxxxxxxxx	Xxxxx	xxxxxxxxxx	xxxxxxxxx
6	Xxxxxxx	xxxxxxxx	xxxxxxxx	Xxxxxxxxxx	Xxxxxxxx	Xxxxxxxx	xxxxxxxxx	Xxxxxxxxxx	Xxxxxx	Xxxxxxxxx	xxxxx
7	xxxxxxx	xxxxxxxxx	Xxxxxx	Xxxxxxx	Xxxxxxxxx	xxxxxxxxx	xxxxxxxxx	Xxxxx	xxxxxxxx	Xxxxxxx	xxxxxxxxx
8	Xxxxxxx	xxxxx	Xxxxxxx	xxxxxxx	Xxxxx	xxxxxxxxxx	Xxxxxxx	Xxxxx	xxxxxxxxxx	Xxxxxx	xxxxxx
9	Xxxxxxxxx	xxxxx	Xxxxxxxxxx	xxxxxx	xxxxx	xxxxxxxx	Xxxxxx	Xxxxxxxxxx	xxxxxxxxx	Xxxxxxxxxx	xxxxxxxx
10	xxxxx	Xxxxxx	xxxxxxxxxx	xxxxxxxxx	xxxxx	xxxxx	xxxxxxxx	xxxxxx	Xxxxxxxxxx	xxxxxxxxxx	Xxxxx
...	xxxxxxx	Xxxxxxxx	Xxxxxxx	xxxxx	xxxxxxxx	xxxxxxxxxx	Xxxxxx	xxxxxxxxx	Xxxxx	xxxxx	xxxxxxxxx

#	as_of	reporting_period	genre	avg_concurrent_players	total_visits	total_hours_played
1	xxxxxxxxxx	Xxxxxxxxx	xxxxxx	xxxxxxxxxx	Xxxxx	Xxxxxx
2	Xxxxxxxxxx	Xxxxxx	Xxxxxxxxx	Xxxxxxxxxx	xxxxxxxxx	Xxxxxxxxx
3	xxxxxxxxx	Xxxxxxx	xxxxxx	Xxxxx	xxxxxxxxxx	xxxxxx
4	Xxxxxxxxxx	xxxxxx	Xxxxx	Xxxxxx	xxxxx	xxxxxxxx
5	xxxxxxx	Xxxxx	Xxxxxxxx	xxxxxxxxxx	xxxxxx	Xxxxxxxxx
6	xxxxxx	Xxxxxxxxx	Xxxxxxxxx	xxxxxxxxxx	Xxxxxx	Xxxxx
7	xxxxxx	xxxxxxx	xxxxxxx	Xxxxx	xxxxxx	Xxxxxxxxxx
8	xxxxxxxx	xxxxxx	Xxxxx	Xxxxxxx	xxxxxx	Xxxxxxxx
9	Xxxxxxx	Xxxxx	xxxxxx	xxxxxxxxxx	Xxxxx	xxxxxxxxxx
10	xxxxxxxxx	Xxxxxxx	xxxxxxxx	xxxxxxxx	Xxxxxxxxxx	Xxxxxxxx
...	Xxxxxxxx	xxxxxxxxx	Xxxxxxxxxx	Xxxxxx	Xxxxxxxxx	xxxxx

#	as_of	reporting_period	observation_type	category	country	comparability	units	value
1	xxxxxxxxxx	Xxxxxxxxx	xxxxxx	xxxxxxxxxx	Xxxxx	Xxxxxx	Xxxxxxxxxx	Xxxxxx
2	Xxxxxxxxx	Xxxxxxxxxx	xxxxxxxxx	Xxxxxxxxx	xxxxxxxxx	Xxxxxxx	xxxxxx	Xxxxx
3	xxxxxxxxxx	xxxxxx	Xxxxxxxxxx	xxxxxx	Xxxxx	Xxxxxx	xxxxx	xxxxxxxx
4	xxxxxxx	Xxxxx	Xxxxxxxx	xxxxxxxxxx	xxxxxx	Xxxxxxxxx	xxxxxx	Xxxxxxxxx
5	Xxxxxxxxx	xxxxxxxxxx	Xxxxxx	Xxxxx	xxxxxx	xxxxxxx	xxxxxxx	Xxxxx
6	xxxxxx	Xxxxxxxxxx	xxxxxxxx	xxxxxx	Xxxxx	Xxxxxxx	xxxxxx	Xxxxxxxx
7	Xxxxxxx	Xxxxx	xxxxxx	xxxxxxxxxx	Xxxxx	xxxxxxxxxx	xxxxxxxxx	Xxxxxxx
8	xxxxxxxx	xxxxxxxx	Xxxxxxxxxx	Xxxxxxxx	Xxxxxxxx	xxxxxxxxx	Xxxxxxxxxx	Xxxxxx
9	Xxxxxxxxx	xxxxx	xxxxxxx	xxxxxxxxx	Xxxxxx	Xxxxxxx	Xxxxxxxxx	xxxxxxxxx
10	xxxxxxxxx	Xxxxx	xxxxxxxx	Xxxxxxx	xxxxxxxxx	Xxxxxxx	xxxxx	Xxxxxxx
...	xxxxxxx	Xxxxx	xxxxxxxxxx	Xxxxxxx	Xxxxx	xxxxxxxxxx	Xxxxxx	xxxxxx

#	as_of	reporting_period	region	direct_checkout	num_sellers	num_sellers_with_sales	items_sold	reviews_added	total_listings	total_favorites
1	xxxxxxxxxx	Xxxxxxxxx	xxxxxx	xxxxxxxxxx	Xxxxx	Xxxxxx	Xxxxxxxxxx	Xxxxxx	Xxxxxxxxx	Xxxxxxxxxx
2	xxxxxxxxx	Xxxxxxxxx	xxxxxxxxx	Xxxxxxx	xxxxxx	Xxxxx	xxxxxxxxxx	xxxxxx	Xxxxxxxxxx	xxxxxx
3	Xxxxx	Xxxxxx	xxxxx	xxxxxxxx	xxxxxxx	Xxxxx	Xxxxxxxx	xxxxxxxxxx	xxxxxx	Xxxxxxxxx
4	xxxxxx	Xxxxxxxxx	Xxxxxxxxx	xxxxxxxxxx	Xxxxxx	Xxxxx	xxxxxx	xxxxxxx	xxxxxxx	Xxxxx
5	xxxxxx	Xxxxxxxxxx	xxxxxxxx	xxxxxx	Xxxxx	Xxxxxxx	xxxxxx	Xxxxxxxx	Xxxxxxx	Xxxxx
6	xxxxxx	xxxxxxxxxx	Xxxxx	xxxxxxxxxx	xxxxxxxxx	Xxxxxxx	xxxxxxxx	xxxxxxxx	Xxxxxxxxxx	Xxxxxxxx
7	Xxxxxxxx	xxxxxxxxx	Xxxxxxxxxx	Xxxxxx	Xxxxxxxxx	xxxxx	xxxxxxx	xxxxxxxxx	Xxxxxx	Xxxxxxx
8	Xxxxxxxxx	xxxxxxxxx	xxxxxxxxx	Xxxxx	xxxxxxxx	Xxxxxxx	xxxxxxxxx	Xxxxxxx	xxxxx	Xxxxxxx
9	xxxxxxx	Xxxxx	xxxxxxxxxx	Xxxxxxx	Xxxxx	xxxxxxxxxx	Xxxxxx	xxxxxx	Xxxxxxxxx	xxxxx
10	Xxxxxxxxxx	xxxxxx	xxxxx	xxxxxxxx	Xxxxxx	Xxxxxxxxxx	xxxxxxxxx	Xxxxxxxxxx	xxxxxxxx	xxxxx
...	Xxxxxx	xxxxxxxxxx	xxxxxxxxx	xxxxx	xxxxx	xxxxxxxx	xxxxxx	Xxxxxxxxxx	xxxxxxxxxx	Xxxxx

#	as_of	reporting_period	order_count	user_count
1	xxxxxxxxxx	Xxxxxxxxx	xxxxxx	xxxxxxxxxx
2	Xxxxx	Xxxxxx	Xxxxxxxxxx	Xxxxxx
3	Xxxxxxxxx	Xxxxxxxxxx	xxxxxxxxx	Xxxxxxxxx
4	xxxxxxxxx	Xxxxxxx	xxxxxx	Xxxxx
5	xxxxxxxxxx	xxxxxx	Xxxxxxxxxx	xxxxxx
6	Xxxxx	Xxxxxx	xxxxx	xxxxxxxx
7	xxxxxxx	Xxxxx	Xxxxxxxx	xxxxxxxxxx
8	xxxxxx	Xxxxxxxxx	xxxxxx	Xxxxxxxxx
9	Xxxxxxxxx	xxxxxxxxxx	Xxxxxx	Xxxxx
10	xxxxxx	xxxxxxx	xxxxxxx	Xxxxx
...	xxxxxx	Xxxxxxxxxx	xxxxxxxx	xxxxxx

#	as_of	reporting_period	observation_type	state	acquisition_count	acquisition_value	added_count	added_value	active_count	active_value	active_initial_value	removed_count	removed_value	removed_initial_value	sold_count	sold_value	sold_acquisition_value
1	xxxxxxxxxx	Xxxxxxxxx	xxxxxx	xxxxxxxxxx	Xxxxx	Xxxxxx	Xxxxxxxxxx	Xxxxxx	Xxxxxxxxx	Xxxxxxxxxx	xxxxxxxxx	Xxxxxxxxx	xxxxxxxxx	Xxxxxxx	xxxxxx	Xxxxx	xxxxxxxxxx
2	xxxxxx	Xxxxxxxxxx	xxxxxx	Xxxxx	Xxxxxx	xxxxx	xxxxxxxx	xxxxxxx	Xxxxx	Xxxxxxxx	xxxxxxxxxx	xxxxxx	Xxxxxxxxx	xxxxxx	Xxxxxxxxx	Xxxxxxxxx	xxxxxxxxxx
3	Xxxxxx	Xxxxx	xxxxxx	xxxxxxx	xxxxxxx	Xxxxx	xxxxxx	Xxxxxxxxxx	xxxxxxxx	xxxxxx	Xxxxx	Xxxxxxx	xxxxxx	Xxxxxxxx	Xxxxxxx	Xxxxx	xxxxxx
4	xxxxxxxxxx	Xxxxx	xxxxxxxxxx	xxxxxxxxx	Xxxxxxx	xxxxxxxx	xxxxxxxx	Xxxxxxxxxx	Xxxxxxxx	Xxxxxxxx	xxxxxxxxx	Xxxxxxxxxx	Xxxxxx	Xxxxxxxxx	xxxxx	xxxxxxx	xxxxxxxxx
5	Xxxxxx	Xxxxxxx	Xxxxxxxxx	xxxxxxxxx	xxxxxxxxx	Xxxxx	xxxxxxxx	Xxxxxxx	xxxxxxxxx	Xxxxxxx	xxxxx	Xxxxxxx	xxxxxxx	Xxxxx	xxxxxxxxxx	Xxxxxxx	Xxxxx
6	xxxxxxxxxx	Xxxxxx	xxxxxx	Xxxxxxxxx	xxxxx	Xxxxxxxxxx	xxxxxx	xxxxx	xxxxxxxx	Xxxxxx	Xxxxxxxxxx	xxxxxxxxx	Xxxxxxxxxx	xxxxxxxx	xxxxx	Xxxxxx	xxxxxxxxxx
7	xxxxxxxxx	xxxxx	xxxxx	xxxxxxxx	xxxxxx	Xxxxxxxxxx	xxxxxxxxxx	Xxxxx	xxxxxxx	Xxxxxxxx	Xxxxxxx	xxxxx	xxxxxxxx	xxxxxxxxxx	Xxxxxx	xxxxxxxxx	Xxxxx
8	xxxxx	xxxxxxxxx	xxxxxxx	Xxxxxxxxx	Xxxxxxx	xxxxxxxxxx	Xxxxx	xxxxxxxxx	xxxxxxx	Xxxxxx	xxxxxxxxx	xxxxx	Xxxxxxx	xxxxxxxxx	Xxxxxxxx	xxxxxxxx	Xxxxxxxx
9	Xxxxxxxx	xxxxxxxx	xxxxxxxxx	Xxxxxxx	Xxxxxxxxx	xxxxxxxx	xxxxx	Xxxxxxxxxx	xxxxxxxxxx	xxxxxx	Xxxxx	Xxxxxxx	Xxxxx	Xxxxxx	Xxxxx	Xxxxxxxxx	xxxxxx
10	xxxxxxxx	Xxxxxxxxx	Xxxxxx	Xxxxxxxxxx	Xxxxxx	Xxxxx	Xxxxxxx	xxxxxxxxx	Xxxxx	xxxxx	Xxxxxx	xxxxxxxxx	xxxxxxx	xxxxxxxxx	Xxxxxxxxxx	xxxxxxxxx	Xxxxx
...	Xxxxx	Xxxxxxxxx	xxxxxxxxxx	xxxxxx	xxxxxxxxx	xxxxxxx	Xxxxxxx	Xxxxxxxxxx	Xxxxxxxxxx	Xxxxxxxx	Xxxxxxxxx	xxxxx	Xxxxxxx	xxxxxxxxxx	Xxxxxxxxx	Xxxxxxxx	xxxxxxxxxx

Volume

350M

Annual Transactions

Data Quality

100%

Consumer Spend Accounted for In-Channel for Tracked Products

Avail. Formats

.csv and .xls

File

Coverage

Countries

History

years

[Sample] CE-Web-Scraping-Automotive-CWH-Data-Sample.csv

Attribute	Type	Example
as_of	String	2024-01-02 10:00:00.000000 UTC
reporting_period	String	2020-08-19 00:00:00.000000 UTC
observation_type	String	sales
model_year	Integer	1995
make	String	CORONADO
is_new	Integer	0
store_region	String	West South Central
comparability	Boolean	t
days_on_site	Integer	0
initial_value	Float	8566.3828125
final_value	Float	8566.3828125
units	Float	0.9962068796157836

[Sample] CE-Web-Scraping-Automotive-CVNA-Data-Sample.csv

Attribute	Type	Example
as_of	String	6/3/2017 10:00
reporting_period	String	5/6/2017
observation_type	String	pending
model_year	Integer	2011
make	String	Hyundai
body_type	String	Sedan
irc_location	String	Winder-GA
days_on_site	Integer	25
initial_value	Float	9209.37
final_value	Float	9209.37
units	Float	0.995607

[Sample] CE-Web-Scraping-Entertainment-RBLX-Data-Sample.csv

Attribute	Type	Example
as_of	String	2024-05-22 10:00:00.000000 UTC
reporting_period	String	2023-07-17 00:00:00.000000 UTC
genre
avg_concurrent_players	Integer	559
total_visits	Integer	154376
total_hours_played	Integer	13220

[Sample] CE-Web-Scraping-Health-Wellness-LULU-Data-Sample.csv

Attribute	Type	Example
as_of	String	2023-04-16 10:00:00.000000 UTC
reporting_period	String	2016-12-13 00:00:00.000000 UTC
observation_type	String	observed
category	String	men
country	String	CA
comparability	Boolean	f
units	Float	4086.0
value	Float	312217.0

[Sample] CE-Web-Scraping-Marketplace-ETSY-Data-Sample.csv

Attribute	Type	Example
as_of	String	2023-04-16 22:00:00.000000 UTC
reporting_period	String	2019-11-17 00:00:00.000000 UTC
region	String	Asia
direct_checkout	Boolean	t
num_sellers	Integer	13
num_sellers_with_sales	Integer	0
items_sold	Float	0.0
reviews_added	Float	0.0
total_listings	Float	275.353
total_favorites	Float	2.5989999999999998

[Sample] CE-Web-Scraping-Other-PZZA-Data-Sample.csv

Attribute	Type	Example
as_of	String	2023-04-16 10:00:00.000000 UTC
reporting_period	String	2018-10-10 00:00:00.000000 UTC
order_count	Integer	167457
user_count	Integer	7424

[Sample] CE-Web-Scraping-Real-Estate-Offerpad-Data-Sample.csv

Attribute	Type	Example
as_of	String	2024-05-22 10:00:00.000000 UTC
reporting_period	String	2016-01-11 00:00:00.000000 UTC
observation_type	String	estimated
state	String	AZ
acquisition_count	Integer	1
acquisition_value	Integer	392795
added_count	Integer	0
added_value	Integer	0
active_count	Integer	0
active_value	Integer	0
active_initial_value	Integer	0
removed_count	Integer	0
removed_value	Integer	0
removed_initial_value	Integer	0
sold_count	Integer	0
sold_value	Integer	0
sold_acquisition_value	Integer	0

Product Attributes

Attribute	Type	Example
Symbol	String	H
Transaction Date	Date	2021-11-27
Transaction Count	Float	12.37
Spend Amount	Float	691.28
Currency	String	USD
Industry Name	String	Leisure & Recreation
Subindustry Name	String	Movie Theatres

Web provides insights into global ecommerce consumer spending in near real-time, with web monitoring data from across the internet combined with our proprietary attribution and analytics to estimate purchase details including inventory, purchase date, sale amount, SKUs ordered, and more.

Consumer Edge is a leader in alternative consumer data for public and private investors and corporate clients. Web includes web scraping purchase data of over 350M consumer transactions from 11K brands and 190 countries. With over 11 years of history, KPIs tracked include parent company, website, items sold, value of items sold, inventory, and purchase data. Tickers tracked include: • BKNG • CARG • CARS • CPRT • CVNA • ETSY • IAA • KMX • LAD • OPAD • OPEN • POSH • PTON • PZZA • RBLX • SAH • SPOT • TRIP Consumer Edge’s web scraping purchase data offers insights into sectors such as: • Automotive • Real Estate • Marketplaces • Lodging • Entertainment Public and private investors can leverage insights from CE’s synthetic data to forecast quarterly earnings with more precision, leverage inventory as a leading indicator of future sales, combine with other datasets like transaction data for more holistic analysis, and explore product trends by brand, industry, category, and more with granular SKU-level data.

Asia (15)

Bahrain

Cyprus

Hong Kong

Indonesia

Israel

Japan

Korea (Republic of)

Kuwait

Lebanon

Qatar

Saudi Arabia

Singapore

Taiwan

Thailand

Turkey

Europe (29)

Austria

Belgium

Bulgaria

Croatia

Czech Republic

Denmark

Finland

France

Germany

Greece

Hungary

Iceland

Ireland

Italy

Luxembourg

Malta

Netherlands

Norway

Poland

Portugal

Romania

Russian Federation

Slovakia

Slovenia

Spain

Sweden

Switzerland

Ukraine

United Kingdom

North America (9)

Canada

Costa Rica

El Salvador

Guatemala

Honduras

Mexico

Nicaragua

Panama

United States of America

Oceania (2)

Australia

New Zealand

South America (6)

Bolivia (Plurinational State of)

Brazil

Chile

Colombia

Ecuador

Uruguay

11 years of historical data

350 million	Annual Transactions
190	Countries Covered
11,000	Brands
11	Years History
18	Tickers

Free sample available

License	Starts at
One-off purchase	Not available
Monthly License	Not available
Yearly License	Available
Usage-based	Not available

Request detailed pricing

Self-reported by the provider

100%

Consumer Spend Accounted for In-Channel for Tracked Products

100%

Total US Sales Coverage

100%

Correlation with Reported KPIs for 50+ Tickers

Methods

Frequency

Format

Ecommerce Analysis

Web Data Collection

Ecommerce Data Enrichment

Web Data Scraping

Web Data Enrichment

Web Scraping Data Web Search Data Ecommerce Purchases Data Web Activity Data SKU-Level Transaction Data

350M Annual Transactions

100% Consumer Spend Accounted for In-Channel for Tracked Products

61 countries covered

Web provides insights into global ecommerce consumer spending in near real-time, with web monitoring data from across the internet combined with our propriet...

1.5B rows

98% Accuracy

249 countries covered

We make the web your dataset and offer fully customizable data feeds at scale to meet your needs.

100M rows

100% match rate

249 countries covered

Get structured Data from websites by TagX. Use the potential of Public web data with our top-notch web scraping solutions. Our solution is powered by robust ...

100B Rows

100% Quality Rate

249 countries covered

Discover the ultimate web scraping tool of 2024 for unlocking valuable insights. Effortlessly extract web data for ecommerce, real estate, and beyond. Harnes...

What is Consumer Edge Web Scraping Consumer Data SKU-Level Purchase Data 350M Transactions, 11K Brands, 190 Countries, 11 Years History?

What is Consumer Edge Web Scraping Consumer Data SKU-Level Purchase Data 350M Transactions, 11K Brands, 190 Countries, 11 Years History used for?

This product has 5 key use cases. Consumer Edge recommends using the data for Ecommerce Analysis, Web Data Collection, Ecommerce Data Enrichment, Web Data Scraping, and Web Data Enrichment. Global businesses and organizations buy Web Scraping Data from Consumer Edge to fuel their analytics and enrichment.

Who can use Consumer Edge Web Scraping Consumer Data SKU-Level Purchase Data 350M Transactions, 11K Brands, 190 Countries, 11 Years History?

This product is best suited if you’re a Small Business, Medium-sized Business, or Enterprise looking for Web Scraping Data. Get in touch with Consumer Edge to see what their data can do for your business and find out which integrations they provide.

How far back does the data in Consumer Edge Web Scraping Consumer Data SKU-Level Purchase Data 350M Transactions, 11K Brands, 190 Countries, 11 Years History go?

This Data Feed has 11 years of historical coverage. It can be delivered on a weekly basis.

Which countries does Consumer Edge Web Scraping Consumer Data SKU-Level Purchase Data 350M Transactions, 11K Brands, 190 Countries, 11 Years History cover?

This product includes data covering 61 countries like USA, Japan, Germany, United Kingdom, and France. Consumer Edge is headquartered in United States of America.

How much does Consumer Edge Web Scraping Consumer Data SKU-Level Purchase Data 350M Transactions, 11K Brands, 190 Countries, 11 Years History cost?

Pricing information for Consumer Edge Web Scraping Consumer Data SKU-Level Purchase Data 350M Transactions, 11K Brands, 190 Countries, 11 Years History is available by getting in contact with Consumer Edge. Connect with Consumer Edge to get a quote and arrange custom pricing models based on your data requirements.

How can I get Consumer Edge Web Scraping Consumer Data SKU-Level Purchase Data 350M Transactions, 11K Brands, 190 Countries, 11 Years History?

Businesses can buy Web Scraping Data from Consumer Edge and get the data via S3 Bucket and UI Export. Depending on your data requirements and subscription budget, Consumer Edge can deliver this product in .csv and .xls format.

What is the data quality of Consumer Edge Web Scraping Consumer Data SKU-Level Purchase Data 350M Transactions, 11K Brands, 190 Countries, 11 Years History?

Consumer Edge has reported that this product has the following quality and accuracy assurances: 100% Consumer Spend Accounted for In-Channel for Tracked Products, 100% Total US Sales Coverage, 100% Correlation with Reported KPIs for 50+ Tickers. You can compare and assess the data quality of Consumer Edge using Datarade’s data marketplace.

What are similar products to Consumer Edge Web Scraping Consumer Data SKU-Level Purchase Data 350M Transactions, 11K Brands, 190 Countries, 11 Years History?

This Data Feed has 3 related products. These alternatives include Consumer Edge Web Scraping Data Expedia & Travel SKU-Level Purchase Data 350M Transactions, 11K Brands, 190 Countries, 11 Yrs History, CrawlBee Web Scraping Data Web Data Extraction Web Data Web Activity Data, and TagX Web Scraping Services Extract & Analyze Data Scrape Ecommerce websites. You can compare the best Web Scraping Data providers and products via Datarade’s data marketplace and get the right data for your use case.

Pricing available upon request

License	Starts at
One-off purchase	Not available
Monthly License	Not available
Yearly License	Available
Usage-based	Not available

Verified Provider

2h Avg. response time

100% Response rate

Consumer Edge Web Scraping Consumer Data | SKU-Level Purchase Data | 350M Transactions, 11K Brands, 190 Countries, 11 Years History

Data Dictionary

Description

Geography

History

Volume

Pricing

Suitable Company Sizes

Quality

Delivery

Use Cases

Categories

Related Searches

Related Products

Frequently asked questions

Consumer Edge
Data-Driven Insights Focused on the Global Consumer

Trusted by

Consumer Edge Web Scraping Consumer Data | SKU-Level Purchase Data | 350M Transactions, 11K Brands, 190 Countries, 11 Years History

Data Dictionary

Description

Geography

History

Volume

Pricing

Suitable Company Sizes

Quality

Delivery

Use Cases

Categories

Related Searches

Related Products

Frequently asked questions

Consumer Edge Data-Driven Insights Focused on the Global Consumer

Trusted by

Consumer Edge
Data-Driven Insights Focused on the Global Consumer