Case study: Passenger's NeTEx-based fare discovery capability

Earlier this year (Feb 2024), Passenger launched a new fares capability based on NeTEx data — ahead of a completed fares profile from the BODS team. This case study aims to give a summary of the work.


The availability of NeTEx data from operators has enabled Passenger to develop a fares calculator within our consumer-facing app products.

Without the national Bus Open Data Service (BODS) and regulation driving it, it is unlikely that operators would consistently follow a standard format for this type of data. This would inevitably result in higher costs to innovate in this area of the customer experience and, in all likelihood, slow innovation to a crawl.

In February 2024, Passenger celebrated the launch of real-time bus fare information in its white-label mobile app product, used by over 35 bus companies in the UK to sell tickets and provide travel information to riders planning their journeys.

For the first time, riders can find out how much their journey will cost before catching the bus. Brighton and Hove Buses, Metrobus in Surrey, Warrington’s Own Buses, Reading Buses, Thames Valley Buses, and Nottingham City Transport launched the new capability in Q1. Other Passenger customers have since followed.

According to Transport Focus, the independent watchdog representing the interests of Britain’s rail, bus and tram passengers in England (outside of London), 33% of non-users — people who don’t know much about their local bus services — would like to know what the bus fare is going to be before boarding.

The Passenger app update addresses this by making information available to customers about tickets that can be purchased on the bus—from the driver—and as mobile tickets directly from a smartphone. Mobile tickets are already a popular way for riders to purchase tickets instantly for immediate travel.

We believe the project is the first to use the NeTEx fares dataset, made available to the public as part of BODS. In development since 2018, the service by the Department for Transport (DfT) in England, was commissioned following the Bus Services Act in 2017. It was designed to stimulate innovation and grow passenger numbers by making local bus services easier to understand. Passenger has long supported open data standards in its software development. NeTEx, an EU (CEN) standard, was chosen as the baseline for Passenger’s new fares capability, following the DfT’s adoption of it for BODS in England.

Many bus operators invest significant resources in publishing data via the BODS platform, and the project is also a highly visible return on that investment.

The app update in February (2024) was the culmination of several Passenger software updates, including tools for operators to preview their fare data before publishing. These tools also help operators become BODS compliant by bringing the data to life. Before this project, it took significant effort for operators to see errors in their NeTEx datasets easily.

With a clear understanding of how operator teams envisaged the customer-facing aspects of the experience, much of our subsequent work focused on developing tools to check data quality in Passenger Cloud, Passenger’s data management platform.

Customer workshops underlined that data quality needed to be reviewed before it could be published and made available to customers. Whilst NeTEx data had been created and published to BODS, there was no way yet to visualise it. Operator teams weren’t confident that what they submitted to BODS would be useful data.

Helen Connolly, COO, discusses ideas with operators at a fares workshop

So, we set about designing tools that allow operators to visualise the NeTEx data before making it available to customers. The first thing we built was a point-to-point calculator for a single service. This highlighted user experience and technical issues, including bad line names, line directions, issues with stop names, duplicate lines, and shadow fares – present because of the £2 fare cap scheme. But the calculator also had no multi-leg journey pricing, which was quickly emerging as a critical objective.

Our first Passenger Cloud tool iteration enabling NeTEx data to be visualised.

This led us to build a Fare Data Management capability into Passenger Cloud, which included a way to hide fare products from the search results. The option to rename fare products to include customer-friendly titles also became an essential part of the delivery, as this isn’t currently possible in the NeTEx data creation tools available to operators.

Reviewing fare data using the calculator tool was initially time-consuming for operators, so we simplified it with an option to export fare triangles, showing stop-to-stop fares in a familiar overview format for each route. Later, we also made it possible to configure the fare triangle export to be stop-to-stop or zone-to-zone to make it easier for some operators to compare with how they input fare data into their ETM systems.

All of this culminated in the journey plan preview tool, which mimicked the results appearing in the app’s journey planner. We had test builds ready to share with both NCT and Oxford, Passenger customers leading with the data review, so they could test their fares in Passenger Cloud while being able to see what the customer would eventually be able to see on the front end.

The delivery of our fares in journey planner capability was the result of collaboration between Passenger, Ticketer and the BODS/KPMG team.

The NeTEx data available on BODS, in most cases generated by the Ticketer system (all except NCT), had yet to be tested in a customer-facing application. Without a way to visualise the data on the service itself, operators also had no real way to test whether what they had uploaded to BODS was accurate and ready to be used.

But without these early datasets, it would have been challenging for Passenger to build the capability. Working together has enabled each party to adapt its contribution to support the other.

BODS has subsequently released a draft of the NeTEx profile designed to support data suppliers to create datasets that are consistently structured, making it easier for data consumers to use them.

Ben Murray, KPMG’s Product Manager on the Department for Transport’s BODS programme, presenting to Passenger operator teams

“We haven’t seen fares data used in the wild. We feel like it can be the most disruptive type of data, the most helpful type of data for passengers to decide if this is the right way for them to travel. And there’s a lot of moving parts to pull together to make that work. And no one’s tried to do that yet. So, there’s going to be a painful journey of discovery and iterative approach to improving that experience for the passengers that you’re going through for the first time”, commented Ben Murray, KPMG’s Product Manager on the Department for Transport’s BODS programme.

He continues, “So, I think Passenger will be forging the way for other app developers, other technology firms, that are surfacing data for passengers that can learn a lot from what you’re doing and the experience that you have to make sure that they can follow in your wake, to make sure that they provide a good experience for the passengers based on the experience that you’ve taken from this process."

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Ben Murray’s comments were from an interview we recorded in January 2024, which is available here The most disruptive type of data - Passenger