This week the research phase began. This project is still in its infancy and my goal this week was to define the problem I was setting out to solve more clearly, formulate my research plan and begin putting it into action.
For this case study I decided to tackle a topic of which I have first hand experience: adopting a healthier and more active lifestyle. I wanted to jump straight to interviews but before I could recruit participants I felt I needed to do a bit of background research in order to try to begin to understand what problems people have in this area and any potential opportunities that may exist for digital products to fill in this space.
As the fitness apps arena is quite a saturated market, I narrowed down a list of the current biggest competitors and who their target audiences are. I conducted research in online communities, read through Facebook groups, visited online discussion forums, spoke to a couple of friends and also reflected on my own experience with trying to become more active and implement healthy habits. This initial research helped me to get a better understanding as to why some people currently use fitness and health apps, their perceived benefits from using them and in what contexts/ scenarios they are using them.
I began by writing a proposal brief, an initial problem statement and hypothesis - all of which were based on assumptions I had prior to speaking to real users one-on-one and which I hoped to either prove or disprove through my research.
Too many people worldwide lead inactive and unhealthy lifestyles. This has negative consequences on both their physical and mental health. Predictions indicated that the COVID-19 pandemic had potential to negatively affect people’s lifestyle, decreasing levels of physical activity and increasing sedentary behaviour and leading to detrimental effects on health (Bentlage et al, 2020). These predications proved to be correct, as the pandemic has led to increasingly sedentary lifestyles worldwide and this has significantly correlated to worsened global mental health (Runacres et al, 2021). How can we get people moving? Research suggests that feeling intimidated, lack of support and lack of confidence are common barriers that prevent people from engaging more in physical activity (Withall, Jago & Fox, 2011). We need ways to encourage people to adopt healthier and more active lifestyles and acquire better habits. However, we want these changes to be habitual and permanent.
How might we encourage users to make healthy lifestyle changes and engage in less sedentary behaviour patterns through digital products?
Encouraging progress above results/ performance statistics may lead to higher long-term retention rates in the digital fitness and health space. People who are unfit and want to change their lifestyle can feel intimidated by the way most leading health and fitness apps are currently marketed and positioned. Fitness newbies tend to fall back on old habits after a while and this often leaves them feeling worse than they did before, because they assume fitness isn’t for them.
My research goals were to better understand the motivations, desires, beliefs and frustrations of potential users regarding their own health and fitness journeys.
The methodology for my user research was to conduct user interviews remotely. They were to take the form of informal one-on-one discussions, where I would ask participants to walk me through their personal attitudes to fitness and healthy habits. Each interview was scheduled to take between 15-20 minutes and I wrote up a discussion guide with lots of extra questions to allow for flexibility and room to improvise if the discussion took on an interesting and unforeseen turn.
Before I began recruiting for and conducting my foundational user interviews I wanted to outline my participant criteria. Looking at my research goals, I knew that I wanted to interview users who desired to be healthier. I also realised there was value in interviewing people at different stages of their fitness journey and life. I also wanted to get a variety of lifestyles, ages and professions so I could be more assured that I was getting a representative sample of data. I decided to create a screener survey to filter potential participants. On top of that, I designed the survey in order to gather some extra general data about people’s perceptions and attitudes towards health and fitness. I used Google forms to create the survey. I was careful in how I structured my questions, since surveys are an unmoderated piece of research (Garg, 2021). Survey length is a key factor in determining response rates, especially when surveying the general public (Hall, 2017), so I purposefully kept it below 10 questions. I struggled to get a large size sample of respondents since this is a personal project and I didn’t have a research budget. I imagine that if I was offering some form of compensation/ incentive to my participants this would have been much easier. In the end I managed to survey 110 people from all over the world. Some key findings included:
Since the timeframe within which I planned to complete this research was one week, I found I had to move fast to have enough time to recruit participants, hold interviews and synthesise all the insights, findings and data. Some of the people I reached out to interview did not have availability at the beginning of the week, and this was a big hurdle because it delayed the synthesising stage until the weekend.
I found that the initial problem statement and hypothesis really helped to generate interview questions. The interviews were very relaxed and conversational and revealed a lot of rich and targeted insights. Unfortunately some of them ran over time which meant that I had even more minutes of audio to transcribe manually than I had planned, which ended up being rather time-consuming. My colleague recommended using Otter next time to avoid this problem; Otter is an AI-powered assistant that generates real-time notes from voice meetings and allows you to edit and highlight transcriptions.
Once I had finally typed up the transcriptions from my interviews I was ready to begin synthesising the research.
I used affinity mapping, with lots of notes containing either one insight, observation, quote or behaviour, to comb out and identify underlying themes/ categories from the huge amount of qualitative data the interviews had generated. A couple of notes wouldn’t fit in any of the categories I had already established, so I had to create a new grouping and some categories I observed began to have too many notes, so I broke them down into subcategories of related themes (Pernice, 2018).
Insights:
After affinity mapping, I created a user journey map based on the insights gathered in the interviews. I felt there were a few different user types and viewpoints I could have mapped, but I stuck to one point of view per map in order to construct a strong and clear narrative (Gibbons, 2018). I decided to explore the actions, mindsets and emotions of a sedentary individual trying to add more activity to their day. I was able to use real user verbatim thoughts, motivations and questions from my interviews to fill out the user’s mindset in different stages of their journey (Gibbons, 2018).
The journey map helped me to visualise the experience of a provisional persona called ‘Natalie’ downloading, using and then abandoning an existing fitness app in an attempt to be more active.
I found journey mapping proved to be extremely helpful in pinpointing moments of frustration and delight and allowed me to identify opportunities that speak to existing user pain points.
Following the synthesis of my research and taking all the insights gained into account, I revised my problem statement to better reflect findings gathered up until this point.
How might we encourage people to exercise more, make it a habit and help them avoid falling back into their old ways by focusing on their journey, rewarding their behaviour and providing them with ongoing motivation?
Bentlage, E., Ammar, A., How, D., Ahmed, M., Trabelsi, K., Chtourou, H., & Brach, M. (2020). Practical Recommendations for Maintaining Active Lifestyle during the COVID-19 Pandemic: A Systematic Literature Review. International Journal of Environmental Research and Public Health, 17(17), 6265.
Garg, D. (2021) “Research UX: Surveys NOT as McD Burgers,” Medium. Available at: https://uxplanet.org/research-ux-surveys-not-as-mcd-burgers-be96d7599c20 (Accessed: February 2, 2022).
Gibbons, S. (2018b) “Journey Mapping 101,” Nielsen Norman Group. Available at: https://www.nngroup.com/articles/journey-mapping-101/ (Accessed: February 2, 2022).
Hall, T. (2017) “How to Create Effective User Surveys,” Medium. Available at: https://uxplanet.org/how-to-create-effective-user-surveys-1cea4b06ff76 (Accessed: February 3, 2022).
Otter (2022) Otter.ai, Otter.ai. Available at: https://otter.ai/ (Accessed: February 3, 2022).
Pernice, K. (2018) “Affinity Diagramming for Collaboratively Sorting UX Findings and Design Ideas,” Nielsen Norman Group. Available at: https://www.nngroup.com/articles/affinity-diagram/ (Accessed: February 2, 2022).
Runacres, A., Mackintosh, K., Knight, R., Sheeran, L., Thatcher, R., Shelley, J., & McNarry, M. (2021). Impact of the COVID-19 Pandemic on Sedentary Time and Behaviour in Children and Adults: A Systematic Review and Meta-Analysis. International Journal of Environmental Research and Public Health, 18(21), 11286.
Withall, J., Jago, R., & Fox, K. (2011). Why some do but most don’t. Barriers and enablers to engaging low-income groups in physical activity programmes: a mixed methods study. BMC Public Health, 11, 507.
