PredictHQ's Intelligent Event Data Sample | Hospitality, Travel & Tourism Data | Customisable Geolocation and POI | Get accurate Polygon Data!

#	id	duplicate_of_id	parent_event_id	title	description	category	labels	start	end	predicted_end	timezone	duration	country	lat	lon	placekey	scope	place_hierarchies	venue_id	venue_name	venue_formatted_address	rank	local_rank	phq_attendance	predicted_event_spend_total	predicted_event_spend_accommodation	predicted_event_spend_hospitality	predicted_event_spend_transportation	impact_patterns	first_seen	updated	state	cancelled	postponed	deleted_reason	brand_safe
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#	id	duplicate_of_id	parent_event_id	title	description	category	labels	start	end	predicted_end	timezone	duration	country	lat	lon	placekey	scope	place_hierarchies	venue_id	venue_name	venue_formatted_address	rank	local_rank	phq_attendance	predicted_event_spend_total	predicted_event_spend_accommodation	predicted_event_spend_hospitality	predicted_event_spend_transportation	impact_patterns	first_seen	updated	state	cancelled	postponed	deleted_reason	brand_safe
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Volume

10.7K

records

Avail. Formats

.json and .csv

File

Coverage

249

Countries

History

months

[Sample] PredictHQ-HospitalityTravelTourism-Events-EifelTower-Jan2023-Jul2023.csv

Attribute	Type	Example	Mapping
id	String	4u7oiZVA6Ub4pqQejM
duplicate_of_id
parent_event_id
title	String	Versailles - Christmas School Holidays
description
category	String	school-holidays
labels	String	holiday,school,christmas-holiday
start	DateTime	2022-12-17T00:00:00+00:00
end	DateTime	2023-01-02T23:59:59+00:00
predicted_end
timezone
duration	Integer	1468799
country	String	FR	Country Name
lat	Float	48.801408	Latitude
lon	Float	2.130122	Longitude
placekey	String	222-22t@5yv-j89-g6k	Placekey
scope	String	region
place_hierarchies	String	6295630>6255148>3017382>3012874
venue_id
venue_name	String		Location Name
venue_formatted_address
rank	Integer	90
local_rank
phq_attendance
predicted_event_spend_total
predicted_event_spend_accommodation
predicted_event_spend_hospitality
predicted_event_spend_transportation
impact_patterns
first_seen	DateTime	2021-08-08T20:51:27+00:00
updated	DateTime	2023-08-12T15:02:05+00:00
state	String	active	State Name
cancelled
postponed
deleted_reason
brand_safe

[Sample] PredictHQ-HospitalityTravelTourism-Events-EifelTower-Sep2023-Mar2024.csv

Attribute	Type	Example	Mapping
id	String	3xhKQX4EYeFe6fK4Kh
duplicate_of_id
parent_event_id
title	String	Paris - Summer School Holidays
description
category	String	school-holidays
labels	String	holiday,school,summer-holiday
start	DateTime	2023-07-08T00:00:00+00:00
end	DateTime	2023-09-03T23:59:59+00:00
predicted_end
timezone
duration	Integer	5011199
country	String	FR
lat	Float	48.856614
lon	Float	2.3522219
placekey	String	222-22t@5yv-j89-g6k	Placekey
scope	String	region
place_hierarchies	String	6295630>6255148>3017382>3012874
venue_id
venue_name
venue_formatted_address
rank	Integer	90
local_rank
phq_attendance
predicted_event_spend_total
predicted_event_spend_accommodation
predicted_event_spend_hospitality
predicted_event_spend_transportation
impact_patterns
first_seen	DateTime	2023-01-19T20:13:30+00:00
updated	DateTime	2024-01-11T04:18:37+00:00
state	String	active
cancelled
postponed
deleted_reason
brand_safe

Free sample dataset of attended, non-attended, and unscheduled events around your preferred location. These categories play a crucial role in generating domestic, inbound, and outbound tourism activity - which drives transportation, accommodation, retail, restaurants, and other demand.

Events such as concerts, school holidays or conferences are powerful tourism attractions. Used by hospitality, travel, and tourism industry providers, PredictHQ’s data can help quickly identify key events that impact locations and behaviors to enhance targeted event-based marketing or foster local tourism partnerships. By better understanding which types of events attract the most tourists, you’re able to easily adjust your strategy to maximize demand and improve forecasting. Data also includes Predicted Event Spend, a dollar figure that reflects the predicted amount of retail, accommodation, and transportation spending in a specific area as a result of a major event. At the core of this figure sits our market leading global event coverage, predicted event attendance, local accommodation demand, aviation demand, third party data and more to give you greater geographical context of the scale of the economic impact an event will have. Location: Pick your favourite location Visibility Window: 6-Months Historical Categories: community, concerts, conferences, expos, festivals, performing arts, sports, academic, daylight savings, observances, politics, public holidays, school holidays, airport delays, disasters, health warnings, severe weather, terror Fields Included: - Title - Category - Labels - Description - Start date and time - End date and time - Predicted end time - Timezone - Country - Lat / Lon - Venue Name - Venue Address - Rank (PHQ Rank, Local Rank) - PHQ Attendance - Event status - Place Hierarchy - Created/updated timestamps - Predicted event spend total - Predicted event spend accommodation - Predicted event spend hospitality - Predicted event spend transportation Polygon information: PredictHQ's polygons enable you to see the full area impacted by an event represented as a shape, because many types of events don't occur neatly at a point on a map. That means you will get a much more accurate picture of impact. Data samples including polygons are available upon request. Data quality: PredictHQ's data quality is one of its key strengths: 1) We have developed a set of Quality Standards for Processing Demand Causal Factors (QSPD), which are used to define the criteria for high-quality event data. By following these standards, PredictHQ ensures that their data meets the highest levels of quality. 2) We use more than 450 data sources to collect event data, including public records, social media, and ticketing websites. 3) We have built thousands of machine learning models that standardize, verify, enrich, and rank every single event. 4) On average we process 28 million events and 422,000 entities every day 5) We track the quality of our data over time and make improvements as needed. About PredictHQ: PredictHQ is the world’s first and only company that provides the missing context for the biggest external factor that impacts businesses demand – events. PredictHQ’s intelligent data of verified global events enables businesses to forecast shifts in demand from events to be able to adjust their inventory, make changes to labor, dynamically price and operate more efficiently. Think conferences, sports games, college graduations, floods, and more. PredictHQ brings all events into one place, combines it with world-first tools and intelligence to allow organizations to better predict and respond to changing customer demand created by events in an easy, reliable, and scalable way. We meet customers exactly where they are, ensuring they can access our data the way that suits them best. Learn more about PredictHQ's real-world event data by visiting our Developer and Data Science Documentation: https://docs.predicthq.com/ Keywords: attended events, attendance, sports, festivals, expos, conferences, concerts, performing arts, community, polygon, consumer spending, predicted spend, location information, demand intelligence, financial data, venue location, accommodation, transportation, restaurant, demand intelligence, event intelligence, event categorisation, business insights, event tracking, historical event data, even impact analysis, event-driven decisions, predictive analytics, hospitality, travel, tourism, aviation, flight, ride-sharing, transportation, mobility, school holiday, observances, public holidays, election, campaign, holiday, delays, polygon, mapping, location, weather, severe weather, historical weather,

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.)

6 months of historical data

10,700

records

Free sample available

PredictHQ has not published pricing information for this product yet. You can request detailed pricing information below.

Request detailed pricing

Methods

Frequency

Format

Demand Forecasting

Delivery Optimization

Workforce Optimization

Event Visibility

Dynamic Pricing

Event Data Point of Interest (POI) Data Tourist Attraction Data Polygon Data Tourism Data

10.7K records

101 countries covered

6 months of historical data

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249 countries covered

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33M Locations

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20 years of historical data

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What is PredictHQ’s Intelligent Event Data Sample Hospitality, Travel & Tourism Data Customisable Geolocation and POI Get accurate Polygon Data!?

What is PredictHQ’s Intelligent Event Data Sample Hospitality, Travel & Tourism Data Customisable Geolocation and POI Get accurate Polygon Data! used for?

This product has 5 key use cases. PredictHQ recommends using the data for Demand Forecasting, Delivery Optimization, Workforce Optimization, Event Visibility, and Dynamic Pricing. Global businesses and organizations buy Event Data from PredictHQ to fuel their analytics and enrichment.

Who can use PredictHQ’s Intelligent Event Data Sample Hospitality, Travel & Tourism Data Customisable Geolocation and POI Get accurate Polygon Data!?

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

How far back does the data in PredictHQ’s Intelligent Event Data Sample Hospitality, Travel & Tourism Data Customisable Geolocation and POI Get accurate Polygon Data! go?

This product has 6 months of historical coverage. It can be delivered on a hourly, daily, weekly, real-time, and on-demand basis.

Which countries does PredictHQ’s Intelligent Event Data Sample Hospitality, Travel & Tourism Data Customisable Geolocation and POI Get accurate Polygon Data! cover?

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

How much does PredictHQ’s Intelligent Event Data Sample Hospitality, Travel & Tourism Data Customisable Geolocation and POI Get accurate Polygon Data! cost?

Pricing information for PredictHQ’s Intelligent Event Data Sample Hospitality, Travel & Tourism Data Customisable Geolocation and POI Get accurate Polygon Data! is available by getting in contact with PredictHQ. Connect with PredictHQ to get a quote and arrange custom pricing models based on your data requirements.

How can I get PredictHQ’s Intelligent Event Data Sample Hospitality, Travel & Tourism Data Customisable Geolocation and POI Get accurate Polygon Data!?

Businesses can buy Event Data from PredictHQ and get the data via S3 Bucket, UI Export, and REST API. Depending on your data requirements and subscription budget, PredictHQ can deliver this product in .json and .csv format.

What is the data quality of PredictHQ’s Intelligent Event Data Sample Hospitality, Travel & Tourism Data Customisable Geolocation and POI Get accurate Polygon Data!?

You can compare and assess the data quality of PredictHQ using Datarade’s data marketplace. PredictHQ appears on selected Datarade top lists ranking the best data providers, including June Provider Spotlight.

What are similar products to PredictHQ’s Intelligent Event Data Sample Hospitality, Travel & Tourism Data Customisable Geolocation and POI Get accurate Polygon Data!?

This product has 3 related products. These alternatives include PredictHQ’s Intelligent Event Data Hospitality, Travel & Tourism Data Tourist Attraction Data Eiffel Tower, Paris September 2023 - March 2024, The Data Appeal Hospitality, Travel and Tourism Data API, Dataset 200 Million+ POI Data Mapped Coverage from 2019, and Grepsr Yelp Resturants Address and Reviews Data Global Coverage with Custom and On-demand Datasets. You can compare the best Event Data providers and products via Datarade’s data marketplace and get the right data for your use case.

Pricing available upon request

Verified Provider

100% Response rate

PredictHQ's Intelligent Event Data Sample | Hospitality, Travel & Tourism Data | Customisable Geolocation and POI | Get accurate Polygon Data!

Data Dictionary

Description

Country Coverage

History

Volume

Pricing

Suitable Company Sizes

Delivery

Use Cases

Categories

Related Searches

Related Products

Frequently asked questions

PredictHQ
You can't prepare for what you can't see coming

Trusted by

PredictHQ's Intelligent Event Data Sample | Hospitality, Travel & Tourism Data | Customisable Geolocation and POI | Get accurate Polygon Data!

Data Dictionary

Description

Country Coverage

History

Volume

Pricing

Suitable Company Sizes

Delivery

Use Cases

Categories

Related Searches

Related Products

Frequently asked questions

PredictHQ You can't prepare for what you can't see coming

Trusted by

PredictHQ
You can't prepare for what you can't see coming