Research: Creating a User’s profile
An online survey was conducted to 104 people, which tossed results about the target audience and potential users of the interactive system for bus routes. The purpose of this survey was to narrow the scope and support the creation of a persona and the possible scenario related to the problem.
The participants taking the survey, 50% are 27–40 years old and 36.6% are 18–27 years old.
Only a 10.6% answered that they don’t use public transportation, while 63.5% answered that they use it three or more days a week. It is an opportunity in terms of the time spent planning to go out, added to the time waiting on stops and, finally, the time spent traveling.
From these users, the 93.5% use mobile phone while they travel in the bus, mainly for tasks like messaging, social media, and music or movies; some of them answered to use it for looking at the transit information. This somehow helps to understand behaviors that, according to Norman, are “the home of learned skills” and these are actioned by situations that match patterns. Most interviewees have skills for sharing and reading handy information online (50).
When they were asked about the problems they may find, these are usually related to the time and schedule of the bus arriving to the stops and overcrowded buses, as shown in the next chart. One of the participants answered “I have to stop the bus and ask the driver where it’s headed.” It seems it is part of the social exchange in this context, where people engage with the community to solve little problems like finding out what bus they need to take.
When it comes to the reasons people choose to use this service, a 62.4% use it because they don’t own a car, 19.4% own a car but prefer to use the bus, and 41.9% selected environmental reasons. Other reasons mentioned are to avoid traffic jams or parking fees.
Most of the people taking the survey use public transportation for traveling to their workplace (62.4%) or attending college (20.4%).
Some of the ideas that came from analyzing this data are possible interaction patterns for the app, such as real time tracking of units, announcement boards, issues about schedules and stops, private location sharing, recent activity, map/feed view, notes or reminders to myself, ask users to help community, integration with other social networks like twitter with hashtags, and using SMS to share information about the service.