footflow
footflow is a geospatial analytics platform that generates modelled estimates of footfall and pedestrian proximity metrics at a highly granular level, enabling evidence-based planning decisions. The tool supports site benchmarking, layout optimization, and predictive forecasting of how building massing and land use changes affect pedestrian movement. It is currently in its final test phase with ten UK local authorities, including Barking & Dagenham, Bolton, and the City of London.
- Data & Analytics
- Mobility & Transportation
- Software Only
- Government Technology
- Property Technology
Funding
Founders
Founder details are not available yet.
Product
Problem
Urban planners, property developers, and local authorities often rely on outdated, coarse-grained, or inconsistent footfall data, making it difficult to accurately assess site viability, optimize land use, or predict the pedestrian impact of new developments. Existing tools lack the granularity and predictive capability needed for evidence-based decision-making, leading to suboptimal planning outcomes.
Solution
footflow provides a geospatial analytics platform that generates modelled estimates of footfall and pedestrian proximity metrics at an unrivalled level of granularity. The tool enables users to benchmark individual sites, optimize layout and land use mix, and run predictive forecasts of how building massing and land use changes will affect pedestrian movement. By using advanced spatial and statistical models, footflow delivers consistent, reliable metrics that help organizations make data-driven planning decisions. The platform is designed to be accessible to a wide range of users, from local authorities to private developers, and is currently in its final test phase with ten UK local authorities.
Target Audience
Primary customers are UK local authorities, urban planners, property developers, and transport consultants seeking reliable footfall data and predictive analytics for planning and development projects.
Features
- Generates modelled estimates of footfall at different times of the day and week for comprehensive site benchmarking
- Produces proximity metrics quantifying pedestrian access to a range of land uses at a highly granular scale, enabling users to view how it varies across a site
- Enables predictive forecasting of how building massing and land use changes impact pedestrian footfall, supporting scenario testing
- Uses advanced spatial and statistical models, with plans to integrate spatial AI techniques such as natural-language spatial interpretation, visual recognition, and generative spatial mapping
- Provides a common definition of pedestrian infrastructure to overcome biases from different professional perspectives, including highway engineering, mall leasing, transit planning, and events crowd management