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How to Use Data to Improve Public Transport User Experience

While public transportation plays a critical role in keeping cities moving, the user experience is not always ideal. However, we take an in-depth look at how we can improve this experience through data analytics.

GTFS data usage

The Importance of User Experience

The success of a public transport system is not only measured by on-time arrival or wide coverage. How users perceive the system determines whether they will use it again and again.

User Experience Improvement with Data Analytics

Passenger Flow Analysis: Data is analyzed to determine which stops are the busiest, at which times the most passengers are traveling. This can help reduce congestion by allocating more vehicles or organizing frequent services.

Real-Time Applications: Passengers can see in real time when the bus or train will arrive, reducing the stress of waiting time.

Analyzing Passenger Feedback: Passenger feedback is analyzed to determine which areas need improvement.

Route Optimization: Data analytics are used to identify the most popular routes and delays on these routes. This can help plan faster and more efficient routes.

Comfort Analysis: Occupancy rates on buses or trains are analyzed to determine which trips need more cars or wagons.


Data analytics allows us to understand and improve the public transport user experience. This increases both passenger satisfaction and improves the overall efficiency and effectiveness of public transport systems.


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