Identify and understand consumer behavior patterns and trends
Aggregated Foot Traffic & Mobility Data
Volume
History
Frecuency
Formats
CSV, JSON, XLX, SQL
Common use cases
Other companies are using this dataset for:
Location Intelligence & Analytics
Retail Analytics
Ideal for industries like:
This alternative dataset, available for all countries, includes enriched raw mobility data and visitation at POIs.
Background
Each record represents a ping sent by a mobile device at a specific time and location. We obtain this information from trustworthy technology providers through partnerships with location-based applications. The entire process complies with relevant privacy laws like GDPR and CCPA.
We process large datasets using complex calculations to simplify data science and machine learning for customer behavior analysis.
Featured attributes of the data
Device speed: We estimate device speed by analyzing the distance between observations to differentiate vehicle, pedestrian, and stationary observations.
Night base of the device: We estimate where the anonymized device spends the night.
Day base of the device: Based on their weekday work location, we calculate the most common daytime location of the device.
Income level: To determine the income level of a device, we analyze the neighborhood where it is being used at night and cross-reference it with socioeconomic data that we have access to.
The inferred income level is determined based on the availability and quality of census data in the respective country and may be presented as a relative wealth index or a currency-calculated income.
POI visited: We use multiple POI databases to estimate check-ins at various locations. The scope and depth of POI databases can vary significantly by country.
Category of visited POI: Each POI observation includes a standardized location category (e.g. supermarkets, coffee shops).
Delivery schemas
We can deliver the data in three different formats:
Full dataset: One record per mobile ping. Experienced teams with large computing budgets should consume these extensive datasets.
Visitation stream: One record per attributable visit. This smaller dataset retains the most valuable elements for understanding POI visits and consumer behavior.
Audience profiles: One record per mobile device in a given period (usually monthly). All visitation data is grouped by category, making it easier to identify consumer types and create user cohorts.
Methodology
- Update Frequency: Monthly, Quarterly or Yearly updates
- Data Delivery Methods: SFTP, Feed API, Email, S3 Bucket
- Delivery Formats: CSV, JSON, XLX, SQL
- Geographic Coverage: All countries.
Differentiators of our custom datasets
This dataset provides enriched mobility and foot traffic data for different countries, including visitation at points of interest. Answer questions like:
- How frequently do anonymized users visit a location? Is it a daily or monthly occurrence, or is it a one-time visit?
- What are the average visit rates?
- Which places do people usually visit? Is it a park, supermarket, restaurant, or other location?
- What are the social characteristics of anonymized users who visit a specific point of interest (POI)? How can we break it down by type: Residents, workers, and visitors?
- What is the mobility pattern of people during night and day hours?
- How frequently do anonymized users visit on different days of the week and hours of the day?
Data Sample & Dictionary
- Request a simple data sample here.
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Why PREDIK Data-Driven?
We have more than 14 years of experience developing modern data mining techniques and generating data-driven solutions for corporations worldwide.
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