Recently we conducted a set of focus groups for Trapeze, a company that specializes in app development for transit agencies. Many of us here in the office are transit enthusiasts (yes, we’re geeks) so this was an exciting project for Usability Matters. The groups, which were run in 3 different locations (two in Canada and one in the U.S.), were composed of frequent transit riders who use web-based planning tools or mobile apps to support their transit use.
Our group explorations and rich discussions led to some valuable findings to help Trapeze with their ongoing work. We also helped the participating transit agencies gain a deeper understanding of their ridership. Also, and somewhat unexpectedly, this study helped me reflect on and validate three key insights to carry forward in my service design work. Perhaps you’ll find it helpful to be reminded of these also:
1. Don’t forget about constraints in your users’ technology context and their effect on how your products are used.
Sometimes our connectedness makes it seem like our technology ecosystems are universally shared, but there are still key differences that are geographically specific. For example, in our two Canadian locations, every group featured some notable discussion about mobile data usage, and people’s desire to limit it (to avoid added costs). This concern led to an increased interest in those markets for more publicly accessible solutions, like signage or kiosks. However, in our U.S. location, data usage was not raised as a particular concern. Those who had smart phones (most of our participants) reported using them liberally, without attention to limits or additional costs, despite the fact that most of our U.S. participants were using transit to commute (rather than for leisure), sometimes from one job to another, and they did express concerns about the costs of transit and commuting overall. It’s not that money was no object for them — far from it — but that their data plans were generally more affordable and accessible than they were for our Canadian participants. This finding was a useful reminder to our Trapeze, whose suite of products includes mobile apps, to account for those kinds of regional differences.
2. Establishing new “normal” ways of doing things will require some room for a learning curve.
In this case, we observed that riders in the U.S. location, who were already using their smart-phones to physically get into the transit system (screen-scanners at the turnstiles serve as one option for fare payment), responded more favourably and more openly to ideas that involved some kind of phone-scanning or other physical device integration. Of our other participants, only those (few) who reported experience with using their phone with an in-store or point-of-entry scanner were able to imagine how they might adopt some of the proposed features that would require that kind of interaction. We were careful in structuring our discussion questions to avoid describing technologies in any restrictive ways, or to ask our participants too directly to design solutions, so we were prepared for the variations in their responses. Those who hadn’t encountered any similar technologies were sceptical about how those features could work. They would need to see it in action before agreeing to try it.
3. People adopt contextually specific biases and personality traits — attitudes that may or may not persist in a different situation — and adjust their behaviours to those contexts.
This was perhaps the most memorable finding from our various group discussions. When presented with features or options that might help them optimize their own individual transit experiences or goals (getting somewhere on time, fastest routes, easy transfers, etc.) our participants universally rejected solutions that they perceived as lessening or worsening the experience of other riders.
Almost unanimously, participants in all three locations had the same response to ideas for communications that might guarantee a transfer connection. “I would hate to get on that vehicle, with everyone waiting for me…” Quickly, the discussions raised concerns that this feature could be ‘abused’ by individuals, but many conceded that the decision to hold or not hold the waiting vehicle could be better made at the system level (“If there were more of us, and the driver had some rules about how long to wait, that might be okay.”)
At first, we were somewhat surprised by this apparent altruism. So many of our participants had had stressful, angering encounters with transit gone awry, and they relied on their systems to get them to work or school on time. Why wouldn’t they use whatever tools they could to ensure the success of those trips? But of course, we realized that users of a public transit system are acutely attuned to the fact that they are using a shared service, and their behaviour reflects that awareness. I was reminded of the popularity of social media campaigns targeted at shaming transit riders who misbehave (just search for ‘manspreading’ on Twitter or Instagram if you don’t know what I’m talking about). Regardless of their political views outside of the subway car, transit riders are pretty much all vigilant socialists in the moment: “A smooth ride for everyone means a smooth ride for me, too.” Features that are at odds with the kinds of behaviours that the system supports or sustains are likely to be rejected (at least, in a room of one’s fellow transit riders).
Our work is founded on understanding users and making sure business goals are aligned to help serve their needs. This study, in addition to being a fun and interesting exploration, helped remind me of a few important facets of any user’s experience with a product or service, and has added some new angles to my design perspective.