Our approach for this project was centred around the Neilson Norman group version of design thinking. The focus is to create a ‘human-centric product’. (Gibbons, n.d.)
The focus for our first week was to empathise with users.
As a group, we did a Heuristic evaluation on the Dublin Bus app itself in order to identify usability issues to solve.
Beside are the quick notes we made on each value after having used the app ourselves.
Next, we discussed the usability goals as a group to identify any usability problems.
We decided on several more apps to test using this method in order to clarify user satisfaction.
We broke up to gather qualitative and quantitative data by testing our friends and families on Dublin bus app and its competitors.
I tested a 14 year old, non-Dublin native, tech savy teen and a 26 year old, Dubliner, app developer.
The highest rated app I tested was Transit, an app which provides users with ‘real-time public transit data’.
I made the table below to best illustrate my findings for each of the usability goals.
I asked both users how they would rate each usability goal and below displays the mean of the results.
I made this chart on Sketch to illustrate my findings from the heuristic evaluations I carried out on the apps above. I focused on five heuristics values because of our initial heuristic evaluation. We found the values above, to have the lowest scores of user ratings for Dublin Bus app.
From our initial heuristic and usability goals, we decided as a group on our task analysis. With consent, I filmed my sister (14-year-old) carrying out our primary task of ‘getting from A to B’, which in this case was getting from Stillorgan to Stephens Green. We also decided upon four secondary tasks for our users.
However, as you can see from the video, my sister was far too frustrated to even attempt the other tasks. This highlighted many problems that first-time users experience when using Dublin Bus app. They are overwhelmed and frustrated by the page order and wording (Match between system and the real world) of the app. After ten minutes of attempting the task of opening the app, press route planner, enter inn address, (in search of finding nearby bus and its route) the task had come to a halt. This was due to the address of the testers actual location not aiding in the search. Rather a user has to know the exact address of the bus stop or bus number. This is information only those who frequent Dublin bus would know. The user-tested had no prior knowledge regarding Dublin bus and tried to get from one location to another with great difficulty.
The user then attempted to complete the same task using real time Ireland app. The success was greater due to the user having recalled using this application before when using Bus Eireann services. First, they opened app, selected ‘search by stop’ (realised that was not the correct button), selected hamburger menu, selected ‘search by route’ and entered in 133 which displayed the route where the user selects the bus stop nearest to them and then selected departures and real-time was displayed.
However, when given the task of getting from Stillorgan to Dublin city (Dublin bus only) the user was again dumbfounded. The efficiency of use for both applications relies heavily on a user accustoming to the app. Rather than the app replicating the user natural responses/needs. The user is not given control. This non-ease of flow/lack of guidance and user control caused great disruption for the user.
This drawing displays the task my sister did of attempting to get from Stillorgan to Stephens Green. She very rarely ventures into Dublin unless it is to meet friends or myself. As you can see, the end result is far too disappointing that of a national transport app. For someone with such tech-savviness, to just give up to call me for guidance, after spending a lengthy 12 mins with the app.
Therefore, I carried out all with Bram (26-year-old). I asked Bram to use transit to try to find out what modes of transport to use and location from BrooklynBridge to Manhattan. (The app has not been modified for Irish transport systems yet so the alternative was to use a place familiar in order to test if data given was accurate).
The app opens up with the map as its homepage. This displays the apps core function, to enable a user to view the current location as this aids them in their search for transport nearby(recognition rather than recall. ie Google Maps). This abled the user to feel more in control as the app replicated the user’s thoughts of ‘I am at Brooklyn bridge now, it is what I see physically and digitally’. This allowed the user to step into the virtual world of the map as it matched their reality.
After all the user testing, we informed each other of our findings via Whatsapp. We utilised the data obtained from the initial; heuristic evaluation, as a means for our task analysis. It gave us an insight into how the apps compared according to user satisfaction. It enabled us to categorise what is expected from the users for a ‘human-centric’ app.
We then made this table to display four apps we pooled together because they stood out because of their similar and higher ratings to that of Dublin bus. The task analysis featured here is of our primary task of getting from A (Initial location) to B (ending location) With all this data at hand, we needed a way to further analyse it to find out what our users really need, which will be discussed in the following blog.