The Veraset team recently joined a live seminar session with Dewey and academic researchers to dive into their device-level visit data. The team walked us through how their visit data is collected, processed, and used by teams looking for actionable foot traffic insights.
Below is a clear summary of the session to help you explore how Visit Data could support your research. If you would like to learn more, check out the full seminar for more details and answers to common questions.
An overview of Veraset Visit Data
Veraset Visit Data is a structured dataset that shows when an anonymized mobile device visits a specific place. It goes beyond just raw GPS pings by using a detailed process to create high-confidence visit records tied to real-world locations.
Data is collected from consented, privacy-compliant location signals from mobile apps. Veraset then takes several additional steps to ensure accuracy. It starts by filtering out noisy signals and then applies clustering techniques, such as DBSCAN, to identify meaningful stops. These stops are matched to POIs using a detailed location database. For complex, dense locations like shopping malls, a learning-to-rank model is then used to pick the most likely destination from nearby options, resulting in a verified visit event that includes the visit’s duration, location, and context.
What makes Veraset Visit Data different from other location datasets?
Unlike many location datasets that provide raw GPS signals with limited context, Veraset makes it easy for users to access data that is analysis-ready, saving researchers significant time and complexity.
- Spend less time on data cleanup and more time on insights. Other providers often deliver raw pings requiring extensive filtering, clustering, and POI matching. Veraset handles this heavy lifting, delivering pre-processed, structured visit records that clearly show when and where people visit places.
- Understand movement in any community. Veraset gathers data from a large network of sources, offering wide geographic and demographic coverage. This makes it easier to study a range of communities, from dense cities to suburban areas, and reduces bias that can occur in smaller datasets.
- Encounter fewer false positives. Veraset applies advanced filtering and scoring methods (dwell time, speed, and entry-exit checks) to ensure visits are detected with high accuracy. This makes the dataset more reliable for serious research.
- Privacy forward, compliance-ready. Data is anonymized and sourced under strict privacy frameworks, ensuring it can be used confidently in academic workflows without added compliance hurdles.
Together, these features make Veraset a trusted, scalable source for mobility analysis without the engineering overhead commonly required with device-level data.
Using Veraset data in academic research
Veraset Visit Data is already supporting a range of academic research projects across universities and instirutions:
- Public policy and economics: Study access to essential services and equity.
- Urban studies and geography: Examine migration, disaster response, and neighborhood change.
- Urban planning: Identify infrastructure gaps and guide development decisions.
- Business and economics: Analyze retail dynamics, advertising effectiveness, and consumer behavior.
- Public health: Study relationships between mobility and health outcomes or care access.
- Environmental studies: Track transportation patterns or park utilization.
Whether studying economic development, commuting behavior, or neighborhood change, Veraset Visit Data offers a powerful tool for exploring questions related to mobility, space, and community dynamics, opening new research possibilities across disciplines.
Access Veraset data for your academic research
Veraset data can be accessed via the Dewey Data platform with an insitutional data subscription. Explore documentation and FAQs for more details, and don't hesitate to reach out to Dewey to discuss access.