PREDIK Data-Driven: Geospatial Data | USA | Tailor-made datasets: Foot traffic & Places Data product image in hero

PREDIK Data-Driven: Geospatial Data | USA | Tailor-made datasets: Foot traffic & Places Data

Predik Data-driven
4.2(3)Badge iconVerified Data Provider
#
device_id
id_type
horizontal_accuracy
timestamp
device_os
source_id
publisher_id
app_id
location_context
geohash
year
month
geohash3
geohash5
geohash6
geohash7
geohash8
geohash9
clave_device_dia
day_of_week
day
hour
distance_center
day_type
hour_type
distance_type
clave_device_dia_hora
in_polygon
kmh
ob_type
device_home_geohash
device_work_geohash
device_work_distance_center
rwi
administrative_area_level_1
administrative_area_level_2
administrative_area_level_3
route
political
locality
sublocality
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 xxxxxxxxxx xxxxxx Xxxxxxxxx xxxxxx Xxxxxxxxx Xxxxxxxxx xxxxxxxxxx Xxxxxx Xxxxx xxxxxx xxxxxxx xxxxxxx Xxxxx xxxxxx Xxxxxxxxxx xxxxxxxx xxxxxx Xxxxx Xxxxxxx
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Request Data Sample
Avail. Formats
.json, .csv, and .xls
File
Coverage
235
Countries
History
5
years

Data Dictionary

Product Attributes
Attribute Type Example Mapping
device_id
2a9d0617-355b-4f38-92e1-e7b77ec301b3
id_type
aaid
Float 12.9110403060913 Latitude
Float 77.5614013671875 Longitude
horizontal_accuracy
6
timestamp
1625553768000
device_os
Android
source_id
33
publisher_id
7aae836893ea29f8299763b7759f64fd599766eb543dc7b7d7d80ba7e...
app_id
2d901e3e08149bcede68d4563cf24058f8f4949c7e5f06b2e6b165851...
location_context
0
geohash
tdr1kyqkr8ke
year
2021
month
7
geohash3
tdr
geohash5
tdr1k
geohash6
tdr1ky
geohash7
tdr1kyq
geohash8
tdr1kyqk
geohash9
tdr1kyqkr
clave_device_dia
2a9d0617-355b-4f38-92e1-e7b77ec301b318814
day_of_week
2
day
6
hour
1
distance_center
2014
day_type
weekday
hour_type
work_hour
distance_type
<200
clave_device_dia_hora
2a9d0617-355b-4f38-92e1-e7b77ec301b3188141
in_polygon
1
kmh
1.14440916824341
ob_type
pedestrian
device_home_geohash
tdr1kyqk
device_work_geohash
tdr1kyqk
device_work_distance_center
<200
rwi
25-35
administrative_area_level_1
Karnataka
administrative_area_level_2
Bangalore Urban
administrative_area_level_3
bangalore
route
6th Main Road
political
Bendre Nagar
String India Country Name
locality
Bengaluru
sublocality
Bengal
String little India Neighborhood Name
String 560070 Postal Code

Description

Data to identify and understand consumer behavior patterns and trends with Foot traffic and anonymized and aggregated mobility data.
This Location Data & Foot traffic dataset available for all countries include enriched raw mobility data and visitation at POIs to answer questions such as:  -How often do people visit a location? (daily, monthly, absolute, and averages).  -What type of places do they visit ? (parks, schools, hospitals, etc)  -Which social characteristics do people have in a certain POI? - Breakdown by type: residents, workers, visitors.  -What's their mobility like enduring night hours & day hours?   -What's the frequency of the visits partition by day of the week and hour of the day? Extra insights -Visitors´ relative income Level.  -Visitors´ preferences as derived by their visits to shopping, parks, sports facilities, churches, among others.  Overview & Key Concepts  Each record corresponds to a ping from a mobile device, at a particular moment in time and at a particular latitude and longitude. We procure this data from reliable technology partners, which obtain it through partnerships with location-aware apps. All the process is compliant with applicable privacy laws.  We clean and process these massive datasets with a number of complex, computer-intensive calculations to make them easier to use in different data science and machine learning applications, especially those related to understanding customer behavior.  Featured attributes of the data Device speed: based on the distance between each observation and the previous one, we estimate the speed at which the device is moving. This is particularly useful to differentiate between vehicles, pedestrians, and stationery observations.  Night base of the device: we calculate the approximated location of where the device spends the night, which is usually their home neighborhood.  Day base of the device: we calculate the most common daylight location during weekdays, which is usually their work location.  Income level: we use the night neighborhood of the device, and intersect it with available socioeconomic data, to infer the device’s income level. Depending on the country, and the availability of good census data, this figure ranges from a relative wealth index to a currency-calculated income.  POI visited: we intersect each observation with a number of POI databases, to estimate check-ins to different locations. POI databases can vary significantly, in scope and depth, between countries.  Category of visited POI: for each observation that can be attributable to a POI, we also include a standardized location category (park, hospital, among others).  Coverage: Worldwide.  Delivery schemas  We can deliver the data in three different formats:  Full dataset: one record per mobile ping. These datasets are very large, and should only be consumed by experienced teams with large computing budgets.  Visitation stream: one record per attributable visit. This dataset is considerably smaller than the full one but retains most of the more valuable elements in the dataset. This helps understand who visited a specific POI, characterize and understand the consumer's behavior.  Audience profiles: one record per mobile device in a given period of time (usually monthly). All the visitation stream is aggregated by category. This is the most condensed version of the dataset and is very useful to quickly understand the types of consumers in a particular area and to create cohorts of users. 

Country Coverage

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 (49)
Afghanistan
Armenia
Azerbaijan
Bahrain
Bangladesh
Bhutan
Brunei Darussalam
Cambodia
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
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 (1)
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.)

History

5 years of historical data

Pricing

Free sample available
Predik Data-driven has not published pricing information for this product yet. You can request detailed pricing information below.

Suitable Company Sizes

Small Business
Medium-sized Business
Enterprise

Delivery

Methods
S3 Bucket
SFTP
Email
Feed API
Frequency
weekly
monthly
quarterly
yearly
Format
.json
.csv
.xls
.sql

Use Cases

Location Intelligence
Audience Insights
Retail Analytics
Customer Data Insights
Address Data Enrichment

Categories

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Frequently asked questions

What is PREDIK Data-Driven: Geospatial Data USA Tailor-made datasets: Foot traffic & Places Data?

Data to identify and understand consumer behavior patterns and trends with Foot traffic and anonymized and aggregated mobility data.

What is PREDIK Data-Driven: Geospatial Data USA Tailor-made datasets: Foot traffic & Places Data used for?

This product has 5 key use cases. Predik Data-driven recommends using the data for Location Intelligence, Audience Insights, Retail Analytics, Customer Data Insights, and Address Data Enrichment. Global businesses and organizations buy Location Data from Predik Data-driven to fuel their analytics and enrichment.

Who can use PREDIK Data-Driven: Geospatial Data USA Tailor-made datasets: Foot traffic & Places Data?

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

How far back does the data in PREDIK Data-Driven: Geospatial Data USA Tailor-made datasets: Foot traffic & Places Data go?

This product has 5 years of historical coverage. It can be delivered on a weekly, monthly, quarterly, and yearly basis.

Which countries does PREDIK Data-Driven: Geospatial Data USA Tailor-made datasets: Foot traffic & Places Data cover?

This product includes data covering 235 countries like USA, Japan, Germany, India, and United Kingdom. Predik Data-driven is headquartered in United States of America.

How much does PREDIK Data-Driven: Geospatial Data USA Tailor-made datasets: Foot traffic & Places Data cost?

Pricing information for PREDIK Data-Driven: Geospatial Data USA Tailor-made datasets: Foot traffic & Places Data is available by getting in contact with Predik Data-driven. Connect with Predik Data-driven to get a quote and arrange custom pricing models based on your data requirements.

How can I get PREDIK Data-Driven: Geospatial Data USA Tailor-made datasets: Foot traffic & Places Data?

Businesses can buy Location Data from Predik Data-driven and get the data via S3 Bucket, SFTP, Email, and Feed API. Depending on your data requirements and subscription budget, Predik Data-driven can deliver this product in .json, .csv, .xls, and .sql format.

What is the data quality of PREDIK Data-Driven: Geospatial Data USA Tailor-made datasets: Foot traffic & Places Data?

You can compare and assess the data quality of Predik Data-driven using Datarade’s data marketplace. Predik Data-driven has received 3 reviews from clients. Predik Data-driven appears on selected Datarade top lists ranking the best data providers, including Best +8 Airport APIs for Travel Data.

What are similar products to PREDIK Data-Driven: Geospatial Data USA Tailor-made datasets: Foot traffic & Places Data?

This product has 3 related products. These alternatives include The Data Appeal Global Business Location Data 200 Million+ POI Data Mapped Coverage from 2019 API, Dataset, Grepsr Comprehensive Dataset of Fast-food Chains’ Store (Starbucks, Mcdonalds, Subway, & more) Location, and Echo Analytics POI Data Europe 82M Locations Available Worldwide Points of Interest (POIs). You can compare the best Location Data providers and products via Datarade’s data marketplace and get the right data for your use case.

Pricing available upon request

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