Urban Mobility & Transportation Insights

The Data

This dataset provides comprehensive insights into transportation networks and urban mobility through hyper-local geographic and demographic analytics. By leveraging real-time and historical data, it enables city planners, transportation agencies, and businesses to optimize urban mobility strategies with precision.

What’s inside

These are just the highlights we've pulled out. If you think there could be a fit, let us know and we'll introduce you directly to the vendor for trial access.

• Traffic Zones: Detailed geographic shapes overlaid with demographic data from the 2022 census.

• Grid Data: Hyper-local production and attraction flows mapped to a 200x200-meter grid.

• GTFS Data: Comprehensive routes, stops, and trip details in a standard GTFS format for seamless integration.

• Shapefiles (Shp): Transport ticketing and tracking data, road networks, and census classifications.

• Size & Scale:

  • 345 active projects worldwide

  • 102,000+ connected buses

  • 2.4 million unique users

  • 525 million app uses annually

Example Use Cases

Here are a few popular examples to spark ideas. If you'd like a sounding board or help building a specific use case, ask to speak with our data team.

• Predictive Traffic & Demand Forecasting: Train AI models to predict peak congestion times, commuter behavior, and demand for public transit, enabling better route optimization and urban planning.

• Alternative Data for Investment Strategies: Analyze real-time transit patterns, road congestion, and commuter volumes to identify economic activity trends and leading indicators for hedge fund investment decisions.

• Insurance Risk Modeling: Assess accident-prone areas and commuter density to refine insurance risk pricing models, improve underwriting accuracy, and adjust coverage policies based on transportation risks.

• Hyper-Targeted Advertising & Site Selection: Identify high-traffic areas for digital billboards, retail store placements, and geo-targeted marketing campaigns based on real commuter movement data.

• Logistics & Fleet Optimization: Use historical and real-time transit flows to optimize delivery schedules, reduce fuel costs, and enhance last-mile logistics for e-commerce and transportation companies.

The Source

This dataset aggregates real-time tracking and historical transit analytics from transportation networks, mapped onto a hyper-local geographic grid. With a strong presence in Brazil and expanding global coverage, this data empowers stakeholders with precise insights into urban mobility trends, allowing for data-driven decision-making at scale.

Looking for a unique or hard-to-find dataset?

Submit a free data request, and we’ll find it for you. At Tiki, we specialize in sourcing and delivering datasets that have never been available before. Whether you need a niche dataset for a specific application or a large-scale dataset for deep analysis, our team is ready to help—just tell us what you’re looking for.