The Data Appeal | Visit Data | API, Dataset | 200 Million+ POI Data Mapped from 2019 | Track Customer Sentiment and Customer Feedback
# | 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 |
phone |
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 | 000fa3715dcc4d1477f4e8a7b58275047fe956cc | |
type
|
String | openings | |
value
|
String | sunday_closed | |
date_last_checked
|
DateTime | 2023-09-12T00:00:00+00:00 |
Attribute | Type | Example | Mapping |
---|---|---|---|
poi_id
|
String | 5cac4e490a15bdf354bdec649929a4617c6941ab | |
name
|
String | $tudio20 | |
street_address
|
String | 20 Rue Montmartre, 75001 Paris, France | |
latitude
|
Float | 48.864635 | |
longitude
|
Float | 2.346322 | |
industry
|
String | Personal care | |
category
|
String | Tatoo studio | |
date_refreshed
|
DateTime | 2023-09-13T00:00:00+00:00 | |
country
|
String | france | |
state
|
String | île-de-france | |
county
|
String | paris | |
city
|
String | paris, 2e arrondissement | |
stars
|
|||
rooms
|
|||
price_class
|
|||
sentiment
|
Float | 95.95 | |
popularity
|
Float | 50.97 | |
hours_popular
|
|||
main_clusters
|
String | [{"cluster": "Atmosphere","sentiment": 95.18},{"cluster":... | |
most_discussed_topics
|
String | [{"topic": "girl","sentiment": 100.00},{"topic": "welcome... | |
spoken_languages
|
String | [{"language": "fr","sentiment": 97.06,"percentage": 94.84... | |
traveler_origin
|
|||
traveler_type
|
|||
phone
|
String | ||
website
|
String | https://www.planity.com/studio-20-75001-paris | |
date_first_presence
|
DateTime | 2019-05-14T00:00:00+00:00 | |
date_closed
|
Attribute | Type | Example | Mapping |
---|---|---|---|
poi_id
|
String | 000fa3715dcc4d1477f4e8a7b58275047fe956cc | |
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 | 0069b002902d9f362c680f63fd4e9a6d6b9d7bb5 | |
date
|
DateTime | 2021-09-01T00:00:00+00:00 | |
period
|
String | weekdays | |
time_period
|
String | (12-15) Early Afternoon | |
popularity
|
Float | 6.81 |
Attribute | Type | Example | Mapping |
---|---|---|---|
poi_id
|
String | 0069b002902d9f362c680f63fd4e9a6d6b9d7bb5 | |
date
|
DateTime | 2021-09-01T00:00:00+00:00 | |
popularity
|
Float | 48.2 |
Attribute | Type | Example | Mapping |
---|---|---|---|
poi_id
|
String | 0069b002902d9f362c680f63fd4e9a6d6b9d7bb5 | |
date
|
DateTime | 2021-09-01T00:00:00+00:00 | |
reviews
|
Integer | 4 | |
sentiment
|
Integer | 75 |
Attribute | Type | Example | Mapping |
---|---|---|---|
String | 9fbf6902-3259-43e0-b84d-c802b1940899 | POI ID | |
name
|
String | ||
street_address
|
String | ||
Decimal | 40.786342970476895 | Latitude | |
Decimal | -119.2065156609571 | Longitude | |
String | Advertising | Company Industry | |
category
|
String | ||
date_refreshed
|
Date | ||
country
|
String | ||
state
|
String | ||
county
|
String | ||
city
|
String | ||
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... | |
phone
|
String | ||
website
|
String | ||
date_first_presence
|
Date | ||
date_closed
|
Date |
Description
Geography
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 Visit Data API, Dataset 200 Million+ POI Data Mapped from 2019 Track Customer Sentiment and Customer Feedback?
Elevate your market strategy using our comprehensive Visit Data, Location Data, and Mobility Data, sourced from 130+ reliable providers, all GDPR compliant. Unlock insights including detailed business locations, POI data, Sentiment Analysis, and Real-Time Foot Traffic Data alongside GIS Data.
What is The Data Appeal Visit Data API, Dataset 200 Million+ POI Data Mapped from 2019 Track Customer Sentiment and Customer Feedback 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 Location Data from The Data Appeal Company to fuel their analytics and enrichment.
Who can use The Data Appeal Visit Data API, Dataset 200 Million+ POI Data Mapped from 2019 Track Customer Sentiment and Customer Feedback?
This product is best suited if you’re a Medium-sized Business or Enterprise looking for Location 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 Visit Data API, Dataset 200 Million+ POI Data Mapped from 2019 Track Customer Sentiment and Customer Feedback go?
This Tabular Data 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 Visit Data API, Dataset 200 Million+ POI Data Mapped from 2019 Track Customer Sentiment and Customer Feedback 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 Visit Data API, Dataset 200 Million+ POI Data Mapped from 2019 Track Customer Sentiment and Customer Feedback cost?
Pricing information for The Data Appeal Visit Data API, Dataset 200 Million+ POI Data Mapped from 2019 Track Customer Sentiment and Customer Feedback 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 Visit Data API, Dataset 200 Million+ POI Data Mapped from 2019 Track Customer Sentiment and Customer Feedback?
Businesses can buy Location 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 Visit Data API, Dataset 200 Million+ POI Data Mapped from 2019 Track Customer Sentiment and Customer Feedback?
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 Visit Data API, Dataset 200 Million+ POI Data Mapped from 2019 Track Customer Sentiment and Customer Feedback?
This Tabular Data has 3 related products. These alternatives include The Data Appeal GIS Data Places Data Store Location Data Business Location Data 200 Million + POI Data Mapped API, Dataset, Factori Global Location Intelligence Data Geospatial:Foot Print:Places Data , and Xtract.io - Point of Interest (POI Data) Global Location Data 6M+ POI. You can compare the best Location Data providers and products via Datarade’s data marketplace and get the right data for your use case.