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PREDIK Data-Driven Aggregated Foot Traffic Data: Custom Datasets wi...
PREDIK Data-Driven Aggregated Foot Traffic Data: Custom Datasets with Enriche...
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PREDIK Data-Driven Aggregated Foot Traffic Data: Custom Datasets with Enriched Raw Mobility Data and Visitation at POIs product image in hero

PREDIK Data-Driven Aggregated Foot Traffic Data: Custom Datasets with Enriched Raw Mobility Data and Visitation at POIs

Predik Data-driven
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#
device_id
id_type
latitude
longitude
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
country
locality
sublocality
neighborhood
postal_code
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
2 xxxxxx Xxxxxxxx Xxxxxxx Xxxxx xxxxxx xxxxxxxxxx Xxxxx xxxxxxxxxx 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 Xxxxx xxxxxxxxxx Xxxxxxx Xxxxx xxxxxxxxxx Xxxxxx xxxxxx Xxxxxxxxx xxxxx Xxxxxxxxxx xxxxxx
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Request Data Sample
Avail. Formats
.json, .csv, and .xls
File
Coverage
12
Countries
History
4
years

Data Dictionary

Product Attributes
Attribute Type Example Mapping
device_id
 2a9d0617-355b-4f38-92e1-e7b77ec301b3
id_type
 aaid
latitude
 Float 12.9110403060913 Latitude
longitude
 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
country
 String India Country Name
locality
 Bengaluru
sublocality
 Bengal
neighborhood
 String little India Neighborhood Name
postal_code
 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 Mobility & 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

North America (8)
Costa Rica
El Salvador
Guatemala
Honduras
Mexico
Nicaragua
Panama
United States of America
South America (4)
Colombia
Dominican Republic
Ecuador
Puerto Rico

History

4 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.
Request detailed pricing

Suitable Company Sizes

Small Business
Medium-sized Business
Enterprise

Delivery

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

Use Cases

Location Intelligence
Location Analytics
Foot Traffic Analytics
Retail Analytics
Customer Data Insights

Categories

Related Searches

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Frequently asked questions

What is PREDIK Data-Driven Aggregated Foot Traffic Data: Custom Datasets with Enriched Raw Mobility Data and Visitation at POIs?

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

What is PREDIK Data-Driven Aggregated Foot Traffic Data: Custom Datasets with Enriched Raw Mobility Data and Visitation at POIs used for?

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

Who can use PREDIK Data-Driven Aggregated Foot Traffic Data: Custom Datasets with Enriched Raw Mobility Data and Visitation at POIs?

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 Aggregated Foot Traffic Data: Custom Datasets with Enriched Raw Mobility Data and Visitation at POIs go?

This product has 4 years of historical coverage. It can be delivered on a monthly, quarterly, and yearly basis.

Which countries does PREDIK Data-Driven Aggregated Foot Traffic Data: Custom Datasets with Enriched Raw Mobility Data and Visitation at POIs cover?

This product includes data covering 12 countries like USA, Mexico, Colombia, Ecuador, and Dominican Republic. Predik Data-driven is headquartered in United States of America.

How much does PREDIK Data-Driven Aggregated Foot Traffic Data: Custom Datasets with Enriched Raw Mobility Data and Visitation at POIs cost?

Pricing information for PREDIK Data-Driven Aggregated Foot Traffic Data: Custom Datasets with Enriched Raw Mobility Data and Visitation at POIs 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 Aggregated Foot Traffic Data: Custom Datasets with Enriched Raw Mobility Data and Visitation at POIs?

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 Aggregated Foot Traffic Data: Custom Datasets with Enriched Raw Mobility Data and Visitation at POIs?

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 Aggregated Foot Traffic Data: Custom Datasets with Enriched Raw Mobility Data and Visitation at POIs?

This product has 3 related products. These alternatives include PREDIK Data-Driven I US Aggregated Foot Traffic Data & Visit Data I Analyze the US South Eastern Area, Customer Journey Europe Aggregated Foot Traffic Data GDPR-Compliant, and Mobility Data Premium Consumer Visitation Insights To Inform Operations and Marketing Decisions Foot Traffic Data Mobility Data. 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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