DC Trails
User research and iOS app UX design
About
With over a million satisfied passengers and over 4.5 million safe miles annually, DC Trails is the premier tour bus company serving the Washington, DC, area. Their hop on, hop off city tours allow passengers to explore DC’s most popular tourist destinations at their own pace. They simply get on the bus at any of its stops, take it to the stop where they want to go, hop off to explore some destinations, and then hop back on when they are ready.
However, the passengers commonly encountered several key pain points. They didn’t know where to catch the next bus. Or they would go to a stop, not knowing when the bus would get there. They would have to call the dispatcher, in frustration, to find out. Then they would mention their frustrations in negative reviews on TripAdvisor and, especially, Yelp.
My task
- Conducted user surveys of existing and potential DC Trails customers.
- Created personas from the user survey data.
- Recommended a target audience and a first platform to use for launch (iOS).
- Created user flows and wireframes showing proposed features for the app.
Project team
- I was a subcontractor for Sweetpea Mobile, a mobile development studio based in Northern Virginia.
- My role included user research and UX design.
- Other project team members included two developers, a visual designer, a product manager, and a QA engineer.
- My main point of contact was the owner of Sweetpea Mobile.
Process
User surveys
I began this project by reviewing the DC Trails website, watching videos of their tours, and reviewing what consumers had said about them. This gave me a sense of the business objectives that they needed to achieve with this project and the strong points and weak points of the services they offer. To understand their competitors better, I watched several of their competitors’ commercials.
Next, I drafted a list of survey questions. Our survey respondents came from three sources: recent customers of DC Trails, people who had liked the DC Trails Facebook page, and respondents from Amazon Mechanical Turk (MTurk).
For the MTurk respondents, I ran the survey in two rounds. The first round served as a qualifier for several hundred participants. I sent the main survey to only the most qualified respondents. I also created a list of qualifier rules for each respondent, but these are not public.
Some of my initial assumptions were correct. I found that existing DC Trails customers were more likely than MTurk respondents to speak languages other than English, that a small percentage of hop on, hop off tour customers do these tours frequently, and that business travelers tend to be less price-conscious than personal travelers. Similarly, travelers who ran on a tight schedule tended more to travel with family and had a stronger interest in history. Lastly, people who would never take a hop on, hop off tour displayed a very distinct difference from everyone else.
Some of my other assumptions didn’t hold. For example, I found that people who visited DC spontaneously didn’t have a stronger tendency to tell friends about their trip on social media.
I also hypothesized that international travelers would have different needs from local and regional travelers, but this was inconclusive due to sample size.
Personas
I mapped all 85 survey respondents onto a list of the 20 most important behavioral variables from the survey.
Through 5 iterations of cluster analysis, I found that the users fit into 10 groupings. These became our personas. One was an outlier (a tour group leader) who was out of scope for this app. Two were clearly not part of our audience because they didn’t travel to major cities or they had no interest in a hop on, hop off tour. That left the other 7 groups.
The next several screenshots show how the personas evolved into their final version.
Ideation and user flows
I generated a list of design ideas, and our team worked to select ideas that were right for our users, good for DC Trails’ business, and technically feasible.
Next, I created user flows that contained the ideas we selected. These particular ones were part of the planning feature for Sarah, which we ultimately removed from our first release.
Iteration 1: Sketching
Iteration 1: Wireframes
Iteration 2: Wireframing
Changes in scope
During development, I revised the wireframes to reduce scope and improve maintenance. This destinations list shows key changes to our sorting and the ways that we present attractions’ prices.
New filtering logic
This introduced our new filtering flow, which explained how destination filtering would work when users apply multiple criteria.
Feature tour
We replaced our initial onboarding flow with a brief tour of key features, explained in terms of our personas’ goals.
New annotations
Our annotations for stops, buses, and destinations became much simpler, and we added a button for re-centering the map on the user’s current location.
This simplified cycling through buses and stops, while also letting people see more of the rest of the map.
By anticipating other information that users would likely need, like bus stop information for a destination, I was able to use links to reduce trial and error in users’ navigation during their tour.
New layout for destinations
I also created a tab layout for the destination view, as an alternative to the accordion above. Further down the first tab, there is a Further Reading section with books and articles for those who want to learn more about a destination..
Visual design
Live app
Results
19%
increase in DC Trails' average rating on Yelp from April 2017 to November 2017
Although I do not have access to analytics data for this app, DC Trails guests have often mentioned the app in their reviews on Yelp and TripAdvisor.