Introduction
Design Brief: Research and develop a design a solution that will help people to get around the city with public transportation.
Client: Hyper Island school project
Role: UX Research, UX Design
Team: Sean Stuart, Yiyuan Xu, Cristina Coll Cartiel
Duration: 4 weeks
Date: October-November 2021
Programs used: Figma, FigJam, Miro, Google Forms
For this project we used the Double Diamond model.
Desk Research
We started with going through the reviews for SL app (since this is the official public transportation app in Stockholm) on Google Play Store, App Store and on Trustpilot in order to understand the main pain points of the users.
We also compared SL with other similar apps in big cities (“MY Transit NYC” in New York, “Bonjour RATP” in Paris, “Deutsche Bahn Navigator” in Germany) in order to understand where SL app stands in comparison to other similar services.
During this analyses we looked at both features that the apps offered as well as reviews from the users.
Desk Research
As the next step, I’ve created a survey on Google Forms.
At that particular point we were still learning about the user behavior and therefore questions in the survey were relatively broad and did not focus on any public transportation app in particular. Instead we were open to learn what apps people were using, why they were using them and what were their main pain points.
I’ve also included 2 questions about the features that users thought they were missing in the app.
The survey was answered by 31 users.
Once we gathered the feedback from the survey, we combined them with the insights from the desk research.
Based on that information we created 2 archetypes, an Empathy Map and a User Journey Map.
In the Empathy Map we summarized all the insights from the research, including the feedback that we received in the survey and from reading the reviews online
The survey included 3 quantitative and 1 qualitative (open ended) questions.
With it we wanted to test our hypothesis that we got as a result of desk research + brainstorming.
How often do you use public transport?
Which app do you use when planning a trip/travelling by public transport?
When asked about pain points with public transportation apps and what improvements the users would like to see, we got a lot of feedback (30 users out of 31 total answered that question).
Below are some of the answers:
Maybe add an extra feature to show exit roots from different stations, for example if a train station has several exits, App should help the commuter to know where they can exit to reach their destination
Too poor information when the train/bus are late. Sometimes the app are not very clever, like suggest a way too long route when you only have to walk maybe 300 meters and take another bus
When I need to change from like bus to train then it usually shows a big time gap between the changes when there are actually trains going before what it shows in the app - it would be good if I could see all the trains/ transport going from the locations around the time of my arrival
The autofill in the trip planner isn’t to my taste, it wants to know where i am are going but I want to say where I am starting
SL app gets stuck very often and doesn’t find the route or address I need. Would be convenient if it explained where exactly the bus stops are, since sometimes it’s not very clear.
It does not always show all possible routes. For instance, if I want to go from A to B and would prefer train instead of bus + tube even though train takes few minutes longes. It does not always show all routes so you have to search your self how to get to the train and then from train to where you want to go. So I guess, what would be nice is the function
"add a stop" that already exist for car journeys
Synchronisation between current position of the transport and the schedule
It would be great with a summary of all trips made / all tickets you bought in a month. To know how much money you spent on public transportation
What we learnt about the users
46.7% of respondents used SL app when traveling with public transportation.
43.3% were using public transportation several times a week.
At the same time around a third of the respondents used a combination of apps when planning a trip, considering they were not in a rush.
Narrowing down and defining the problem
Since we needed to narrow down the target audience and create a feasible solution, we chose to focus on an “everyday user”, i.e. people who were using public transportation on regular basis.
We have also narrowed down all the potential features to just the following two:
Get notified if there are delays in the "favourite" commute route, i.e. set the time when you want to get notifications (e.g. before going to/from work)
Knowing how crowded specific transport is at a given time
From there we chose to focus on 1 of those features but still explore potential needs a bit further and created one more scenario where the user was a tourist, instead of being a local regular commuter.
At his stage we have tried to phrase a HMW statement together with answering some of the core questions for understanding our users:
What are the users needs?
What are their challenges?
What are the insights we can use from interviews?
Tourist
We created a User Persona and a User Journey Map for each of those users in order to:
1. understand their actions and goals better
2. identify issues users might experience while using SL app
Local
Based on a HMW statement we developed a hypothesis which we used for creating a solution
We believe that the users want to see the live crowds information when chosing a public transportation route, so that they can feel at ease when traveling and in control of their journey
In the beginning of our ideation phase we created a Task Flow as we wanted to understand what the users will go through when they will want to view how crowded specific public transportation is at a time when they want to travel.
In the User Flow we mapped users path from when the user opened the app to when they viewed “live crowds” feature and acted on it.
There we tried to consider various ways of interacting with the app:
- how the user will be looking up/planning the journey
- whether the journey will be taking place at that particular time or scheduled for later
This was the last step in our process. Each of us created several low fidelity paper prototypes which we then put together in FigJam. We then combined some of the ideas and created a low fidelity prototype that you can find below.
It was important to us to be able to use both text and visusal cues in order to be able to indicate how crowded a bus or a subway was.
This way we wanted to make the feature accessible for a wider range of users.
