The Data Appeal | Online Travel Agency (OTA) Data | API, Dataset | 200 Million+ POI Data Mapped
# | poi_id |
type |
value |
date_last_checked |
---|---|---|---|---|
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 |
# | poi_id |
name |
street_address |
latitude |
longitude |
industry |
category |
date_refreshed |
country |
state |
county |
city |
stars |
rooms |
price_class |
sentiment |
popularity |
hours_popular |
main_clusters |
most_discussed_topics |
spoken_languages |
traveler_origin |
traveler_type |
website |
date_first_presence |
date_closed |
|
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | xxxxxxxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxx | Xxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxx | xxxxx | xxxxxxxx | xxxxxxx | Xxxxx | Xxxxxxxx |
2 | xxxxxxxxxx | xxxxxx | Xxxxxxxxx | xxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxx | xxxxxx | xxxxxxx | xxxxxxx | Xxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx | xxxxxx | Xxxxxxxx | Xxxxxxx | Xxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxxx |
3 | xxxxxxxxx | Xxxxxxx | xxxxxxxx | xxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | xxxxx | xxxxxxx | xxxxxxxxx | Xxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxxx | Xxxxx | xxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxx | Xxxxxxx | xxxxxxx |
4 | Xxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxx | xxxxxx | Xxxxxxxxx | xxxxx | Xxxxxxxxxx | xxxxxx | xxxxx | xxxxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxx | xxxxx | xxxxxxxx | xxxxxx | Xxxxxxxxxx |
5 | xxxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | xxxxxxxx | xxxxxxxxxx | Xxxxxx | xxxxxxxxx | Xxxxx | xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxx | xxxxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxxx | xxxxxxxx |
6 | Xxxxxxxx | Xxxxxxxx | xxxxxxxx | xxxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx | Xxxxx | Xxxxxx | Xxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxx | Xxxxxxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxx |
7 | 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 | xxxxxxx | Xxxxxxxx |
8 | xxxxx | Xxxxxx | xxxxxx | xxxxxxxx | xxxxxxx | Xxxxx | Xxxxxxxxx | Xxxxx | Xxxxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | xxxxxxx | xxxxxxxxxx | xxxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxxxx | xxxxxxx | Xxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxx |
9 | xxxxxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxx | Xxxxx | xxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | xxxxxxx | Xxxxxxxx | xxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxxxxx | xxxxxxx | Xxxxx | xxxxxxxxx | xxxxxxxx |
10 | Xxxxxxxx | xxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxx | Xxxxx | Xxxxx | Xxxxxxx | xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxx | xxxxxx | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxx |
... | xxxxxxx | Xxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxxxx | Xxxxxxx | Xxxxxxx | xxxxxxxx | xxxxx | Xxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxxxxxx | Xxxxxxx |
# | poi_id |
day_of_week |
period_time |
open_time |
close_time |
date_last_checked |
---|---|---|---|---|---|---|
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 |
# | poi_id |
date |
period |
time_period |
popularity |
---|---|---|---|---|---|
1 | xxxxxxxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxxxx | Xxxxx |
2 | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx |
3 | xxxxxxxxx | Xxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxx |
4 | Xxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxx |
5 | Xxxxx | Xxxxxx | xxxxx | xxxxxxxx | xxxxxxx |
6 | Xxxxx | Xxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxx |
7 | xxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxx |
8 | Xxxxx | xxxxxx | xxxxxxx | xxxxxxx | Xxxxx |
9 | xxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxx | Xxxxx |
10 | Xxxxxxx | xxxxxx | Xxxxxxxx | Xxxxxxx | Xxxxx |
... | xxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxx |
# | poi_id |
date |
popularity |
---|---|---|---|
1 | xxxxxxxxxx | Xxxxxxxxx | xxxxxx |
2 | xxxxxxxxxx | Xxxxx | Xxxxxx |
3 | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx |
4 | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxx |
5 | xxxxxxxxx | Xxxxxxx | xxxxxx |
6 | Xxxxx | xxxxxxxxxx | xxxxxx |
7 | Xxxxxxxxxx | xxxxxx | Xxxxx |
8 | Xxxxxx | xxxxx | xxxxxxxx |
9 | xxxxxxx | Xxxxx | Xxxxxxxx |
10 | xxxxxxxxxx | xxxxxx | Xxxxxxxxx |
... | xxxxxx | Xxxxxxxxx | Xxxxxxxxx |
# | poi_id |
date |
reviews |
sentiment |
---|---|---|---|---|
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 |
Data Dictionary
Attribute | Type | Example | Mapping |
---|---|---|---|
poi_id
|
String | 00079d7ee78a1f5047e5ac2d22957f68624f3508 | |
type
|
String | openings | |
value
|
String | friday_open | |
date_last_checked
|
DateTime | 2023-09-12T00:00:00+00:00 |
Attribute | Type | Example | Mapping |
---|---|---|---|
poi_id
|
String | a233450ccdeda5967d3d914f145ee8e3fc143494 | |
name
|
String | (CVO) Captive Vision Outdoor | |
street_address
|
String | level 1/84 Union St Pyrmont | |
latitude
|
Float | -33.8697258 | |
longitude
|
Float | 151.1972593 | |
industry
|
String | Freelance | |
category
|
String | Corporate office | |
date_refreshed
|
DateTime | 2023-09-13T00:00:00+00:00 | |
country
|
String | australia | |
state
|
String | new south wales | |
county
|
String | sydney | |
city
|
String | sydney | |
stars
|
|||
rooms
|
|||
price_class
|
|||
sentiment
|
Integer | 100 | |
popularity
|
Float | 22.15 | |
hours_popular
|
|||
main_clusters
|
String | [{"cluster": "Staff","sentiment": 100.00}] | |
most_discussed_topics
|
String | [{"topic": "team","sentiment": 100.00}] | |
spoken_languages
|
String | [{"language": "en","sentiment": 100.00,"percentage": 100.... | |
traveler_origin
|
|||
traveler_type
|
|||
String | Phone Number | ||
website
|
String | https://captivevision.com.au/ | |
date_first_presence
|
DateTime | 2021-02-25T00:00:00+00:00 | |
date_closed
|
Attribute | Type | Example | Mapping |
---|---|---|---|
poi_id
|
String | 00079d7ee78a1f5047e5ac2d22957f68624f3508 | |
day_of_week
|
Integer | 0 | |
period_time
|
Integer | 1 | |
open_time
|
String | Closed | |
close_time
|
|||
date_last_checked
|
DateTime | 2023-09-12T00:00:00+00:00 |
Attribute | Type | Example | Mapping |
---|---|---|---|
poi_id
|
String | 018651b315bec21033a53be77b9d24f571e1a980 | |
date
|
DateTime | 2021-09-01T00:00:00+00:00 | |
period
|
String | weekdays | |
time_period
|
String | (05-10) Early Morning | |
popularity
|
Float | 22.46 |
Attribute | Type | Example | Mapping |
---|---|---|---|
poi_id
|
String | 018651b315bec21033a53be77b9d24f571e1a980 | |
date
|
DateTime | 2021-09-01T00:00:00+00:00 | |
popularity
|
Float | 30.26 |
Attribute | Type | Example | Mapping |
---|---|---|---|
poi_id
|
String | 018651b315bec21033a53be77b9d24f571e1a980 | |
date
|
DateTime | 2021-09-01T00:00:00+00:00 | |
reviews
|
Integer | 1 | |
sentiment
|
Integer | 100 |
Attribute | Type | Example | Mapping |
---|---|---|---|
String | 9fbf6902-3259-43e0-b84d-c802b1940899 | POI ID | |
String | POI Name | ||
String | Address | ||
Decimal | 40.786342970476895 | Latitude | |
Decimal | -119.2065156609571 | Longitude | |
String | Advertising | Company Industry | |
String | POI Category | ||
date_refreshed
|
Date | ||
String | United States of America | Country Name | |
String | California | State Name | |
String | Bernalillo County | County Name | |
String | Berlin | City Name | |
stars
|
Integer | ||
rooms
|
Integer | ||
price_class
|
Integer | ||
sentiment
|
Decimal | ||
popularity
|
Decimal | ||
hours_popular
|
String | {"monday":null,"tuesday":"afternoon","wednesday":"late_mo... | |
main_clusters
|
Decimal | [{"cluster": "Atmosphere","sentiment": 76.99},{"cluster":... | |
most_discussed_topics
|
Decimal | [{"topic": "service","sentiment": 78.57},{"topic": "staff... | |
spoken_languages
|
Decimal | [{"language": "it","sentiment": 85.93,"percentage": 94.39... | |
traveler_origin
|
Decimal | [{"country": "it","sentiment": 84.67,"percentage": 19.93}... | |
traveler_type
|
Decimal | [{"traveler_type": "couple","sentiment": 83.51,"ercentage... | |
String | Company Phone Number | ||
String | https://www.ibm.com | Company Website | |
date_first_presence
|
Date | ||
date_closed
|
Date |
Description
Country Coverage
History
Volume
137 | Online Sources Monitored |
195 | Countries Mapped |
251 | Million Points of Interest Mapped |
320 | Billion Pieces of Online Content Analyzed Each Day |
Pricing
Suitable Company Sizes
Quality
Delivery
Use Cases
Categories
Related Searches
Related Products
Frequently asked questions
What is The Data Appeal Online Travel Agency (OTA) Data API, Dataset 200 Million+ POI Data Mapped?
Connect with our experts and harness the power of our comprehensive Online Travel Agency (OTA) Data, Hotel Rates & Pricing Data, Tourism and POI Data. Dive into a treasure of insights, including Travel Booking Data and traveler’s Sentiment Data. 180+ countries and coverage since 2019.
What is The Data Appeal Online Travel Agency (OTA) Data API, Dataset 200 Million+ POI Data Mapped used for?
This product has 5 key use cases. The Data Appeal Company recommends using the data for Location Intelligence, Retail Site Selection, Sentiment Analysis, Marketing Data Enrichment, and Point of Interest (POI) Mapping. Global businesses and organizations buy Hotel Rates & Pricing Data from The Data Appeal Company to fuel their analytics and enrichment.
Who can use The Data Appeal Online Travel Agency (OTA) Data API, Dataset 200 Million+ POI Data Mapped?
This product is best suited if you’re a Medium-sized Business or Enterprise looking for Hotel Rates & Pricing Data. Get in touch with The Data Appeal Company to see what their data can do for your business and find out which integrations they provide.
How far back does the data in The Data Appeal Online Travel Agency (OTA) Data API, Dataset 200 Million+ POI Data Mapped go?
This product has 4 years of historical coverage. It can be delivered on a daily, weekly, monthly, quarterly, yearly, real-time, and on-demand basis.
Which countries does The Data Appeal Online Travel Agency (OTA) Data API, Dataset 200 Million+ POI Data Mapped cover?
This product includes data covering 249 countries like USA, China, Japan, Germany, and India. The Data Appeal Company is headquartered in Italy.
How much does The Data Appeal Online Travel Agency (OTA) Data API, Dataset 200 Million+ POI Data Mapped cost?
Pricing information for The Data Appeal Online Travel Agency (OTA) Data API, Dataset 200 Million+ POI Data Mapped is available by getting in contact with The Data Appeal Company. Connect with The Data Appeal Company to get a quote and arrange custom pricing models based on your data requirements.
How can I get The Data Appeal Online Travel Agency (OTA) Data API, Dataset 200 Million+ POI Data Mapped?
Businesses can buy Hotel Rates & Pricing Data from The Data Appeal Company and get the data via S3 Bucket, SFTP, Email, and REST API. Depending on your data requirements and subscription budget, The Data Appeal Company can deliver this product in .csv and .xls format.
What is the data quality of The Data Appeal Online Travel Agency (OTA) Data API, Dataset 200 Million+ POI Data Mapped?
The Data Appeal Company has reported that this product has the following quality and accuracy assurances: 80% match rate. You can compare and assess the data quality of The Data Appeal Company using Datarade’s data marketplace. The Data Appeal Company has received 3 reviews from clients. The Data Appeal Company appears on selected Datarade top lists ranking the best data providers, including Who’s New on Datarade? .
What are similar products to The Data Appeal Online Travel Agency (OTA) Data API, Dataset 200 Million+ POI Data Mapped?
This product has 3 related products. These alternatives include The Data Appeal Hospitality, Travel and Tourism Data API, Dataset 200 Million+ POI Data Mapped Coverage from 2019, Hotel Rates & Pricing Data One Stop Destination For All Hospitality, Travel & Tourism Data Tourism Data Free Customized Data Sample Available, and Grepsr Trip Advisor Property Address and Reviews Global Coverage with Custom and On-demand Datasets. You can compare the best Hotel Rates & Pricing Data providers and products via Datarade’s data marketplace and get the right data for your use case.