Europe Location Data | POI, Geospatial, Foot Traffic Data, Sentiment data, Business Listings Data & Store Location | 251 Millions+ POI Data Mapped
# | 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 |
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 |
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 |
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 | 002fcc33d377c2ee796626787f353243a9d49e80 | |
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 | 00b45e0db4bc0274d319ea9e3a3eadc4d350dbb2 | |
date
|
DateTime | 2021-09-01T00:00:00+00:00 | |
period
|
String | weekdays | |
time_period
|
String | (10-12) Late Morning | |
popularity
|
Float | 20.41 |
Attribute | Type | Example | Mapping |
---|---|---|---|
poi_id
|
String | c68f02f049e223437c2c6584cf44bef551ba045d | |
name
|
String | &Walsh | |
street_address
|
String | 900 Broadway # 203 New York | |
latitude
|
Float | 40.7388288 | |
longitude
|
Float | -73.9896311 | |
industry
|
String | Freelance | |
category
|
String | Design agency | |
date_refreshed
|
DateTime | 2023-09-13T00:00:00+00:00 | |
country
|
String | united states | |
state
|
String | new york | |
county
|
String | new york | |
city
|
String | new york | |
stars
|
|||
rooms
|
|||
price_class
|
|||
sentiment
|
|||
popularity
|
|||
hours_popular
|
|||
main_clusters
|
|||
most_discussed_topics
|
|||
spoken_languages
|
|||
traveler_origin
|
|||
traveler_type
|
|||
String | Phone Number | ||
website
|
|||
date_first_presence
|
DateTime | 2019-06-19T00:00:00+00:00 | |
date_closed
|
Attribute | Type | Example | Mapping |
---|---|---|---|
poi_id
|
String | 0025accf05d317904c5ef8927adaa2733d6fae98 | |
type
|
String | service_available | |
value
|
String | wheelchair_accessible_entrance | |
date_last_checked
|
DateTime | 2023-09-12T00:00:00+00:00 |
Attribute | Type | Example | Mapping |
---|---|---|---|
poi_id
|
String | 00b45e0db4bc0274d319ea9e3a3eadc4d350dbb2 | |
date
|
DateTime | 2021-09-01T00:00:00+00:00 | |
popularity
|
Float | 48.2 |
Attribute | Type | Example | Mapping |
---|---|---|---|
poi_id
|
String | 00b45e0db4bc0274d319ea9e3a3eadc4d350dbb2 | |
date
|
DateTime | 2021-09-01T00:00:00+00:00 | |
reviews
|
Integer | 4 | |
sentiment
|
Integer | 55 |
Description
Country Coverage
History
Volume
137 | Online Sources Monitored |
195 | Countries Mapped |
200 | Million Points of Interest Mapped |
320 | Billion Pieces of Online Content Analyzed Each Day |
Pricing
License | Starts at |
---|---|
One-off purchase | Available |
Monthly License | Available |
Yearly License | Available |
Usage-based | Available |
Suitable Company Sizes
Quality
Delivery
Use Cases
Categories
Related Searches
Related Products
Frequently asked questions
What is Europe Location Data POI, Geospatial, Foot Traffic Data, Sentiment data, Business Listings Data & Store Location 251 Millions+ POI Data Mapped?
Our unparalleled combination of points-of-interest (POI) data enriched with Sentiment and Foot Traffic Data KPIs will empower your decision making. We provide the most accurate and comprehensive POI / Location data, enriched with Business Listings Data and customer insights.
What is Europe Location Data POI, Geospatial, Foot Traffic Data, Sentiment data, Business Listings Data & Store Location 251 Millions+ POI Data Mapped used for?
This product has 5 key use cases. The Data Appeal Company recommends using the data for Location Intelligence, Out-of-home (OOH) Advertising, Retail Site Selection, Sentiment Analysis, 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 Europe Location Data POI, Geospatial, Foot Traffic Data, Sentiment data, Business Listings Data & Store Location 251 Millions+ POI Data Mapped?
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 Europe Location Data POI, Geospatial, Foot Traffic Data, Sentiment data, Business Listings Data & Store Location 251 Millions+ POI Data Mapped go?
This product has 5 years of historical coverage. It can be delivered on a daily, weekly, monthly, quarterly, yearly, real-time, and on-demand basis.
Which countries does Europe Location Data POI, Geospatial, Foot Traffic Data, Sentiment data, Business Listings Data & Store Location 251 Millions+ 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 Europe Location Data POI, Geospatial, Foot Traffic Data, Sentiment data, Business Listings Data & Store Location 251 Millions+ POI Data Mapped cost?
Pricing information for Europe Location Data POI, Geospatial, Foot Traffic Data, Sentiment data, Business Listings Data & Store Location 251 Millions+ 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 Europe Location Data POI, Geospatial, Foot Traffic Data, Sentiment data, Business Listings Data & Store Location 251 Millions+ POI Data Mapped?
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 .json, .csv, and .xls format.
What is the data quality of Europe Location Data POI, Geospatial, Foot Traffic Data, Sentiment data, Business Listings Data & Store Location 251 Millions+ 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 Europe Location Data POI, Geospatial, Foot Traffic Data, Sentiment data, Business Listings Data & Store Location 251 Millions+ POI Data Mapped?
This product has 3 related products. These alternatives include Global Point-of-Interest Data POI, Geospatial, Sentiment (Reviews), Footfall, Business Listings & Store Location 251 Millions+ POI Data Mapped, OpenWeb Ninja Yelp Consumer Review Data & Ratings, Local Business Listings Data, Restaurants, Home Services + More Global Coverage Real-Time API, and Unacast Foot Traffic Data Global. You can compare the best Location Data providers and products via Datarade’s data marketplace and get the right data for your use case.