It’s time for transit agencies to (actually) double down on rider focus

Transit is losing to Uber and Lyft, but this isn’t inevitable. 

It’s been hard to ignore the deluge of news stories about the enormous growth of Uber and Lyft, both of which went public this year. Most articles talk about the companies’ success in growing both their customer base and total ridership over time.

There’s a lesson here for public transit agencies that want to reverse their own ridership declines. The “secret sauce” of Uber and Lyft’s wild growth is an unflinching devotion to the customer experience. From their applications’ user experience, to their arrival predictions’ accuracy, Uber and Lyft maintain a laser-focus on driving customer satisfaction.

This rider focus isn’t unique to Uber or Lyft, but it has differentiated them from their public transit competitors and, indirectly, bred higher expectations of service quality for many transit riders.

In order to grow ridership, public transit agencies need to give their riders the same treatment. After all, many transit riders are also Uber and Lyft customers, and they gauge their transit experiences against what they experience elsewhere.

In order to compete with Lyft and Uber, customer experience needs to be in the very DNA of everything agencies do. By focusing on what riders care about —minimizing wait times, finding ways to keep buses moving through traffic, making both riding and waiting more comfortable—ridership will follow.

Of course, every transit professional wants to offer the best service possible for their riders, but to deliver meaningful change for riders, that desire must be reflected explicitly in each agency's goals and performance measurement frameworks. Like any shift in policy, true rider focus requires goals that are actionable, data-driven, and prioritized consistently throughout the agency.

Transit agencies that take customer focus seriously have reaped the benefits. Take, for example, Transport for London (TfL), which has become an industry leader in implementing rider-focused changes to their transit network. In the early 2000s, TfL dramatically reoriented their agency ,placing its riders' needs at the top of its priority list. The results have been staggering: between 2000 and 2015, public transportation use in London increased from 24 percent to 36 percent of all trips, while private car trips decreased from 50 percent to 37 percent. An important but underappreciated aspect of TfL’s reforms was setting headway consistency as a true indicator of service reliability for their high-frequency service.

This works because most riders on high-frequency routes usually ignore the schedule and care only about wait times. Is my bus late? I don’t know, and I don’t care. But have I been waiting more than 12 minutes? Maybe I should have just taken an Uber.

Recognizing the importance of keeping the time between buses -- also known as ‘headways’ -- consistent, TfL introduced the concept of excess wait time to measure service reliability for frequent buses. Excess wait time measures how much time the average passenger has to wait beyond the time they would've waited if buses arrived at evenly spaced intervals.

Excess wait time and other headway consistency metrics are quickly becoming a best practice in the field, and the list of US-based applications in the US is growing. MTA in New York, MBTA in Boston, and WMATA in Washington all measure and report on headway reliability metrics, reorienting their metrics around what riders actually value.

Technologically, it’s more than possible for transit to compete with Uber and Lyft. Real-time GPS data is available for almost every bus in almost every transit system in the US, and this data is well documented as a tool to improve internal management practices, rider experience, and, increasingly, headway management.

That’s why we at Swiftly developed tools to make it easier for transit agency staff to analyze the real-time and historical performance of their headways, to tie planning and operations decisions back to what riders truly care about for high-frequency routes. Our Headways module is part of a growing software ecosystem that makes these abstract concepts concrete at the click of a button. Is the 38-Geary always getting caught at red light at 7th Avenue? Is this delay hurting rider wait times farther down the line? It’s now much simpler to quickly identify these kinds of issues, allowing transit agencies to prioritize “micro capital projects” like Transit Signal Priority where they have the largest impact on rider satisfaction and ridership.

Rider satisfaction in the public transit world has lagged behind the private sector. Companies like Uber and Lyft have taken advantage of this fact, rushing in to fill a vacuum in customer experience for people who would otherwise take public transit. Evidence continues to mount that Uber and Lyft are drawing riders from transit at an alarming pace. They’ve taken market share because they provide an experience that people perceive to be more rider-focused than public transit.

It doesn’t have to be this way. Transit agencies have more data at their disposal than ever before to help them understand what customers need, how to deliver it, and where they’re falling short. The next step in transit operations is to double down on what works: managing headways and measuring reliability in a way that reflects how riders use transit service.

Rider focus is more important now than ever amidst an extended, nationwide ridership decline. People have a growing list of choices to get from point A to point B, and aligning agency metrics with what riders actually care about is a powerful way to get riders to choose transit.

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Matt Fleck is a product marketing specialist and transit wonk based in San Francisco.