MOBILE APP
GoFar is a startup company that has developed a data-tracking device that provides a driver with real-time information to encourage smarter and safer driving.
The challenge
To research and deliver a UX solution that met the rapidly changing needs of key stakeholders who were at various stages of development within a small evolving startup. The initial meeting illustrated that there were various opinions on how much data and what type of features the app should utilise.
Approach
Daily standup meetings and two week sprints were adopted to fit with the client’s agile processes. This proved to be a great way to manage client expectations while maintaining flexibility during the various stages of research, analysis, design, testing and delivery of the app’s navigation, features and functions.
My role
I was responsible for UX research including contextual inquiry, behavioural studies, competitive analysis and other areas of research, evaluation of findings, creative development of the apps’ features and functions which included feature prioritisation, sketching, usability testing and wireframes.
My UX activities
• Business and competitive analysis
• Client/stakeholder management
• Contextual research
• Feature prioritisation
• Ideation, sketching and iteration
• Information architecture
• Persona development
• Site maps
• Task analysis
• Qualitative/quantitative surveying
• Usability testing
• Wireframes
Tools
• Adobe Illustrator
• Adobe Photoshop
• Keynote
• Paper, Post-it Notes and Sharpies
• Sketch 3
• SurveyGizmo
Outcomes
GoFar integrated the iOS navigation and Information Architecture in the first release of the app
UX findings were integrated into GoFar’s existing UX research and data
Interview guides along with other UX artifacts were used for continued contextual and survey research – consumer and enterprise sectors
Buckle up and lets get underway
Prototype demo and trail
The discovery process began by trialling GoFar's data-tracking prototype. This provided contextual understanding of how the product performed and provided instant driver feedback through a light display. The initial driving experience began to shape hypothesis and queries for the next stage of contextual inquiries.
Contextual inquiries
Multiple interviews were conducted across a range of drivers including individuals required to drive as part of their career. This helped formalise questions that were included in the next stage of surveying additional drivers and begin to provide qualitative and quantitative data.
Key insights gained
• Driver behaviour can be directly related and influenced by passengers in the vehicle
• The value of becoming a better driver would have to outweigh the cost of $150, disruption of the interior aesthetics and other various reasons for individuals to purchase
• Time spent using new technologies (data-tracking wearable devices such as a FitBit) can be short lived as users can quickly get disenchanted if expectations are not met
Recognising opportunities and challenges
Competitive analysis
A product review of the competitive landscape was completed to identify any possible gaps and opportunities.
Key insights gained
• Majority of cheaper products have poor User Experience (UX) and User Interface (UI)
• Majority of cheaper products offer a minimum range of driver tracking data
• GoFar is the only product that provides instant feedback via light display
Research and more scrutiny
Survey results and analysis
A 20 question survey was developed and distributed online with a return of 56 respondents – from babysitters to software engineers.
The qualitative and quantitative data provided specific insights and validated hypothesis. One hunch was that a high number of drivers already use vehicle specific data via factory equipped built-in instrumentation. This was confirmed as over 50% (29 drivers) use built-in fuel trackers to monitor their fuel economy and of those 73% (19 drivers) found it very useful. Encouraging data to indicate good market potential.
Creating a licence to empathise
Identification of core user groups
Over a week of contextual inquiries and surveying provided many insights and informed the various archetypes to be identified.
Personas were developed to contextualise the various user groups and their associated traits, needs and behaviours. These personas provided a foundation of empathy and informed my many design considerations and choices. Additionally, they were provided to stakeholders in the form of driver’s licences so they could keep the users 'front of mind' while making informed choices during the continued development of their data-tracking device.
Focusing on driver tasks and needs
Development of the app’s features and notifications
Contextual inquires and competitive analysis indicated that there were opportunities to differentiate, create shelf appeal and promote product longevity after purchase with a ’data-rich’ app that provided a broad range of information and features for the diverse range of drivers. There was a continued focus during ideation and development to only include functions, features and notifications that were relevant to the specific needs of the defined user groups.
Understanding the context of the vehicle was important to observe and gain insights of driver habits and behaviours
Rapid sketching and lo-fi concept testing
In the context of multiple driver task and habits, the app navigation was simplified to minimise driver distractions and maximise usability.
Usability testing and final wireframes
Additional testing was completed again in various environments including the context of the vehicle. Various users confirmed that the latest iterations worked well and the wireframes were ready for the next stage of sensory design.
Utilisation of various data streams for applicable notifications
With access to vehicle and driver performance along with location, there are many opportunities to utilise this data and prompt the user at appropriate moments – such as recognising low full and providing the user with the nearest options for petrol stations, and once there, asking the user if they would like to record the data to calculate their fuel mileage. (shown below)
Gamification – education through engagement
A small amount of time was spent researching the use of gamification. Use of quizzes, avatars and other ideas were generated. It was determined that quizzes were are a good opportunity to educate the driver in areas of low performance.
