Global Leading Multinational Retailer Data

#	dataplor_id	parent_location	name	main_category	sub_category	sub_sub_category	business_category	naics_code	sic_code	chain_id	chain_name	parent_chain_path	chain_uuid_path	store_number	stock_ticker	phone	address	address2	h3_index	neighborhood	city	state	postal_code	country_code	country	latitude	longitude	dataplor_status	data_quality_confidence_score	open_closed_status	open_closed_status_confidence_score	opened_on	closed_on	website	monday_open	monday_close	tuesday_open	tuesday_close	wednesday_open	wednesday_close	thursday_open	thursday_close	friday_open	friday_close	saturday_open	saturday_close	sunday_open	sunday_close
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Volume

300K

Retail Locations

Avail. Formats

.json and .csv

File

Coverage

249

Countries

History

years

[Sample] Multinational_Retailers_Sample.csv

Attribute	Type	Example	Mapping
dataplor_id	String	1a8bf50b-ce0c-4851-b0c7-25f14ae1825a	POI ID
parent_location	String
name	String	Lululemon	POI Name
main_category	String	retail	POI Category
sub_category	String		POI Sub-category
sub_sub_category	String		POI Sub-category
business_category	String	clothing_store	Product Category
naics_code	Float	458110	Company NAICS Code
sic_code	Float	0279	Company SIC Code
chain_id	String	lululemon	Brand ID
chain_name	String	Lululemon Athletica	Brand Name
parent_chain_path	String
chain_uuid_path	String
store_number	String
stock_ticker	String	NASDAQ:LULU	Stock Ticker
phone	String	+# (###) ####-####	POI Telephone
address	String	#+##	Address
address2	String	# ****** , *****, #####, ***	Address
h3_index	String	8f53645a6074b43
neighborhood	String	Nob Hill	Neighborhood Name
city	String	Al Khiran	City Name
state	String	الاحمدي	State Name
postal_code	Integer	600001	Postal Code
country_code	String	kw	Country Code Alpha-2
country	String	Kuwait	Country Name
latitude	Float	28.67379542	Latitude
longitude	Float	48.34778541	Longitude
dataplor_status	String	active
data_quality_confidence_score	String	0.729513774
open_closed_status	String	open
open_closed_status_confidence_score	Float	0.303
opened_on	String	2023-10-13T00:00:00+00:00
closed_on	String
website	String	https://www.apple.com	Website
monday_open	String	0:00	POI Opening Hours
monday_close	String	0:00	POI Opening Hours
tuesday_open	String	0:00	POI Opening Hours
tuesday_close	String	0:00	POI Opening Hours
wednesday_open	String	0:00	POI Opening Hours
wednesday_close	String	0:00	POI Opening Hours
thursday_open	String	0:00	POI Opening Hours
thursday_close	String	0:00	POI Opening Hours
friday_open	String	0:00	POI Opening Hours
friday_close	String	0:00	POI Opening Hours
saturday_open	String	0:00	POI Opening Hours
saturday_close	String	0:00	POI Opening Hours
sunday_open	String	0:00	POI Opening Hours
sunday_close	String	0:00	POI Opening Hours

Product Attributes

Attribute	Type	Example	Mapping
dataplor_id	String	4bc53f9d-c148-43d8-93a5-2e04f12cc53f	POI ID
parent_location	String	4bc53f9d-c148-43d8-93a5-2e04f12cc53f	Placekey
name	String	Culver's Burgers	POI Name
main_category	String	dining	POI Category
sub_category	String	diner	POI Sub-category
sub_sub_category	String	diner	POI Sub-category
business_category	String	fast_food_restaurant	Product Category
naics_code	Float	722515	Company NAICS Code
sic_code	Float	5812	Company SIC Code
chain_id	String	culvers	Brand ID
chain_name	String	Culver's	Brand Name
store_number	String	#213	Location ID
stock_ticker	String	SBUX:NASDAQ	Stock Ticker
phone	String	+###########	POI Telephone
address	String	#### *	Address
address2	String	***** ###	Address
neighborhood	String	Downers Grove	Neighborhood Name
city	String	Topeka	City Name
state	String	Kansas	State Name
postal_code	String	66604	Postal Code
country_code	String	US	Country Code Alpha-2
country	String	United States of America (the)	Country Name
latitude	Float	39.0485	Latitude
longitude	Float	-95.7622	Longitude
dataplor_status	String	active/inactive
data_quality_confidence_score	String	0.88
open_closed_status	String	Open/Temporarily Closed/Permanently Closed/Open
open_closed_status_confidence_score	Float	0.95
opened_on	String	2007-11-19	POI Opening Hours
closed_on	String	2020-09-04

dataplor's Global Leading Multinational Retail Location Dataset covers 300K+ locations across 250 countries and territories, making it one of the most comprehensive retail datasets available. This global dataset is particularly valued for its ability to provide updates in real-time.

In the global retail market, strategic decision-making is paramount. dataplor’s Leading Global Retailers dataset provides an unparalleled view of worldwide leading multinational retailers, empowering businesses with the actionable insights needed to conquer the market. Data Points for Precision: -Retailer Profiles: In-depth information on top multinational retail corporations, including official names, and parent companies. -Business Classification: Precise categorization by retail segment (e.g., apparel, electronics, grocery), business model (e.g., department store, hypermarket, specialty retailer), and target market demographics, ensuring granular analysis. -Location Precision: Exact street addresses and geographic coordinates for pinpoint mapping and strategic planning. -Store Attributes: Comprehensive details such as corporate assigned store number, and open/close status. Empowering Use Cases: -Market Entry and Expansion: Identify lucrative markets with untapped potential, assess the competitive landscape dominated by multinational players, and pinpoint optimal locations for new store openings or international expansions. -Competitive Intelligence: Gain deep insights into the strategies, store formats and geographic distribution of leading multinational retailers to inform your own business decisions and benchmark performance. -Targeted Marketing and Promotions: Develop hyper-targeted campaigns based on location demographics, competitor proximity, and local preferences in key markets. -Supply Chain Optimization: Streamline global sourcing, distribution logistics, and inventory management by understanding the location of key retail hubs, demand fluctuations, and regional preferences. -Investment and Risk Analysis: Evaluate potential investment opportunities in the global retail sector by assessing market saturation, growth potential, and risk factors associated with specific regions and retail segments.

Africa (58)

Algeria

Angola

Benin

Botswana

Burkina Faso

Burundi

Cabo Verde

Cameroon

Central African Republic

Chad

Comoros

Congo

Congo (Democratic Republic of the)

Côte d'Ivoire

Djibouti

Egypt

Equatorial Guinea

Eritrea

Ethiopia

Gabon

Gambia

Ghana

Guinea

Guinea-Bissau

Kenya

Lesotho

Liberia

Libya

Madagascar

Malawi

Mali

Mauritania

Mauritius

Mayotte

Morocco

Mozambique

Namibia

Niger

Nigeria

Rwanda

Réunion

Saint Helena, Ascension and Tristan da Cunha

Sao Tome and Principe

Senegal

Seychelles

Sierra Leone

Somalia

South Africa

South Sudan

Sudan

Swaziland

Tanzania, United Republic of

Togo

Tunisia

Uganda

Western Sahara

Zambia

Zimbabwe

Asia (51)

Afghanistan

Armenia

Azerbaijan

Bahrain

Bangladesh

Bhutan

Brunei Darussalam

Cambodia

China

Cyprus

Georgia

Hong Kong

India

Indonesia

Iran (Islamic Republic of)

Iraq

Israel

Japan

Jordan

Kazakhstan

Korea (Democratic People's Republic of)

Korea (Republic of)

Kuwait

Kyrgyzstan

Lao People's Democratic Republic

Lebanon

Macao

Malaysia

Maldives

Mongolia

Myanmar

Nepal

Oman

Pakistan

Palestine, State of

Philippines

Qatar

Saudi Arabia

Singapore

Sri Lanka

Syrian Arab Republic

Taiwan

Tajikistan

Thailand

Timor-Leste

Turkey

Turkmenistan

United Arab Emirates

Uzbekistan

Vietnam

Yemen

Europe (51)

Albania

Andorra

Austria

Belarus

Belgium

Bosnia and Herzegovina

Bulgaria

Croatia

Czech Republic

Denmark

Estonia

Faroe Islands

Finland

France

Germany

Gibraltar

Greece

Guernsey

Holy See

Hungary

Iceland

Ireland

Isle of Man

Italy

Jersey

Latvia

Liechtenstein

Lithuania

Luxembourg

Macedonia (the former Yugoslav Republic of)

Malta

Moldova (Republic of)

Monaco

Montenegro

Netherlands

Norway

Poland

Portugal

Romania

Russian Federation

San Marino

Serbia

Slovakia

Slovenia

Spain

Svalbard and Jan Mayen

Sweden

Switzerland

Ukraine

United Kingdom

Åland Islands

North America (13)

Belize

Bermuda

Canada

Costa Rica

El Salvador

Greenland

Guatemala

Honduras

Mexico

Nicaragua

Panama

Saint Pierre and Miquelon

United States of America

Oceania (25)

American Samoa

Australia

Cook Islands

Fiji

French Polynesia

Guam

Kiribati

Marshall Islands

Micronesia (Federated States of)

Nauru

New Caledonia

New Zealand

Niue

Norfolk Island

Northern Mariana Islands

Palau

Papua New Guinea

Pitcairn

Samoa

Solomon Islands

Tokelau

Tonga

Tuvalu

Vanuatu

Wallis and Futuna

Other (9)

Antarctica

Bouvet Island

British Indian Ocean Territory

Christmas Island

Cocos (Keeling) Islands

French Southern Territories

Heard Island and McDonald Islands

South Georgia and the South Sandwich Islands

United States Minor Outlying Islands

South America (42)

Anguilla

Antigua and Barbuda

Argentina

Aruba

Bahamas

Barbados

Bolivia (Plurinational State of)

Bonaire, Sint Eustatius and Saba

Brazil

Cayman Islands

Chile

Colombia

Cuba

Curaçao

Dominica

Dominican Republic

Ecuador

Falkland Islands (Malvinas)

French Guiana

Grenada

Guadeloupe

Guyana

Haiti

Jamaica

Martinique

Montserrat

Paraguay

Peru

Puerto Rico

Saint Barthélemy

Saint Kitts and Nevis

Saint Lucia

Saint Martin (French part)

Saint Vincent and the Grenadines

Sint Maarten (Dutch part)

Suriname

Trinidad and Tobago

Turks and Caicos Islands

Uruguay

Venezuela (Bolivarian Republic of)

Virgin Islands (British)

Virgin Islands (U.S.)

20 years of historical data

300,000

Retail Locations

Free sample available

10% discount if you buy via Datarade

License	Starts at
One-off purchase	Not available
Monthly License	Not available
Yearly License	Not available
Usage-based	$0.09$0.08 / record

Request detailed pricing

Methods

Frequency

Format

Audience Extension Company Analysis

Finance

Consumer Data Enrichment

Third Party Logistics (3PL)

Store Location Data Point of Interest (POI) Data Business Location Data Retail Data Retail Store Data

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249 countries covered

20 years of historical data

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What is Global Leading Multinational Retailer Data?

dataplor’s Global Leading Multinational Retail Location Dataset covers 300K+ locations across 250 countries and territories, making it one of the most comprehensive retail datasets available. This global dataset is particularly valued for its ability to provide updates in real-time.

What is Global Leading Multinational Retailer Data used for?

This product has 5 key use cases. dataplor recommends using the data for Audience Extension, Company Analysis, Finance, Consumer Data Enrichment, and Third Party Logistics (3PL). Global businesses and organizations buy Store Location Data from dataplor to fuel their analytics and enrichment.

Who can use Global Leading Multinational Retailer Data?

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

How far back does the data in Global Leading Multinational Retailer Data go?

This product has 20 years of historical coverage. It can be delivered on a weekly, monthly, real-time, and on-demand basis.

Which countries does Global Leading Multinational Retailer Data cover?

This product includes data covering 249 countries like USA, China, Japan, Germany, and India. dataplor is headquartered in United States of America.

How much does Global Leading Multinational Retailer Data cost?

Pricing for Global Leading Multinational Retailer Data starts at USD0.09 per record . dataplor offers a 10% discount when you buy data from them through Datarade. Connect with dataplor to get a quote and arrange custom pricing models based on your data requirements.

How can I get Global Leading Multinational Retailer Data?

Businesses can buy Store Location Data from dataplor and get the data via S3 Bucket and SFTP. Depending on your data requirements and subscription budget, dataplor can deliver this product in .json and .csv format.

What is the data quality of Global Leading Multinational Retailer Data?

You can compare and assess the data quality of dataplor using Datarade’s data marketplace. dataplor has received 3 reviews from clients.

What are similar products to Global Leading Multinational Retailer Data?

This product has 3 related products. These alternatives include Global Independent & Multi-National Retail Location Data, Grepsr Comprehensive Dataset of Walgreens US Stores Across the United States, and Global Store Location Data Business Location Data Places Data: Categorized Branded Retail Locations. You can compare the best Store Location Data providers and products via Datarade’s data marketplace and get the right data for your use case.

Starts at

$0.09$0.08 / record

License	Starts at
One-off purchase	Not available
Monthly License	Not available
Yearly License	Not available
Usage-based	$0.09$0.08 / record

Verified Provider

9h Avg. response time

100% Response rate

Global Leading Multinational Retailer Data

Data Dictionary

Description

Country Coverage

History

Volume

Pricing

Suitable Company Sizes

Delivery

Use Cases

Categories

Related Searches

Related Products

Frequently asked questions

dataplor
Globally scaled, dynamically updated and human-reviewed accurate location data.

Trusted by

Global Leading Multinational Retailer Data

Data Dictionary

Description

Country Coverage

History

Volume

Pricing

Suitable Company Sizes

Delivery

Use Cases

Categories

Related Searches

Related Products

Frequently asked questions

dataplor Globally scaled, dynamically updated and human-reviewed accurate location data.

Trusted by

dataplor
Globally scaled, dynamically updated and human-reviewed accurate location data.