If you work in customer experience at a transit agency, you know that riders don't experience your agency as a collection of departments and systems. They experience one service.
When the train is delayed, the transfer doesn't work, or a bus never shows up, they don't care which system failed. They just know the information they were given was wrong.
And when a rider is standing in the cold waiting for a bus that has disappeared from the app, they don't call the IT department. They call customer service. They post on social media. They file a complaint. They ask, "Where is my bus?"
This is why I think transit data is a customer experience issue, not just a technology issue.
We often talk about GTFS and GTFS-Realtime as technical standards for moving information between systems. But that data increasingly shapes what riders see, what they expect, and how they make decisions about their trips.
When the data is wrong, the customer experience is wrong. And when riders can't trust the information we give them, they can't fully trust the service itself.
What Is Structured Data?
Transit agencies have a lot of information about their service. The problem is that it often lives in different places and in different formats.
A schedule might live in one system. Vehicle locations in another. Service alerts somewhere else. Customer service may have a completely different view of what is happening.
That makes it difficult to create a consistent picture of the service, both for riders and for the people trying to help them.
Structured data gives all of these systems a common language. GTFS describes the scheduled service: routes, stops, trips, and times. GTFS-Realtime adds what is happening right now, such as vehicle locations, delays, and service changes.
That information powers much more than a trip planner. It feeds agency websites, Google Maps and Apple Maps, customer service tools, digital signage, and other systems riders rely on to understand the service.
For CX leaders, this matters because the data is part of the experience. The question isn't just whether the data is technically or structurally correct. It's whether the information a rider receives reflects the service they are actually going to experience.
1. When the Bus on the Screen Doesn't Show Up
Few things erode trust faster than watching a bus get closer on your screen, only to have it disappear before it arrives.
From the rider's perspective, this isn't a data problem. It's a broken promise. The app said the bus was coming, so they planned around that information. When it disappears, they don't know whether the bus is late, canceled, stuck somewhere, or whether the information was simply wrong.
There are several reasons this can happen, but one common problem is that scheduled service and real-time vehicle data aren't properly connected. The systems need to know which vehicle is serving which trip so that a rider sees the right bus, at the right stop, at the right time.
When that connection works, real-time information can do what riders actually need it to do. It can help them make a decision about whether to wait, walk to another stop, change their route, or leave later.
That is the real value of reliable transit data. It isn't just showing a countdown on a screen. It is giving riders information they can use to make decisions.
2. Giving Customer Service the Same View of the Service
When something goes wrong, riders turn to customer service for answers.
But too often, the person answering the phone or responding to a message has no more information than the rider. They may know that a bus is late, but not why. They may see that a trip is scheduled, but not whether the vehicle is actually running. They may know there is a disruption, but not what it means for the rider's trip.
That puts customer service in an impossible position. They are being asked to explain a service they can't see.
Connecting operational data with the information customer service uses can change that. When agents can see the same real-time information that powers rider-facing tools, they can give people a much clearer picture of what is happening and what they can do next.
The goal isn't for customer service to have more data. It's for them to have the right data, at the right time, so they can help a rider make a decision.
3. Connecting What Riders Say to What Operations Can Change
Customer feedback can tell us where riders are struggling, but a complaint by itself rarely tells us why.
A rider might say, "Route 47 is always late." That's important information, but it's difficult for an operations team to act on without knowing when the problem happens, how often it happens, or what is happening in the service at that time.
This is where structured data can help. When rider feedback can be connected to routes, trips, stops, and time of day, CX teams can start to see patterns that would otherwise be difficult to find.
Instead of simply saying that riders are frustrated with Route 47, you might be able to see that complaints consistently occur during a particular time of day or around a particular part of the route.
That creates a much more useful conversation between CX and operations. The question moves from "Why are riders complaining?" to "What is happening in the service that is creating this experience?"
And that is where customer feedback becomes useful for improving the service, not just responding to it.
Data Is Part of the Customer Experience
Transit agencies are often organized around functions. Scheduling owns the schedule. Operations runs the service. IT manages the systems. Customer experience listens to riders. But riders don't experience those boundaries. They experience one transit service.
That means CX leaders have a stake in the data that describes and communicates that service. Not because CX needs to own GTFS or become experts in data pipelines, but because the quality of that data directly affects what riders see, what they expect, and the decisions they make.
Reliable transit data isn't just a technical requirement. It is part of delivering a service that riders can understand and trust.
If we want to improve the customer experience, we need to pay attention to the systems that create it.