The group was formed by Leandro Iwai, Sinead Foley and Siobhan McBride. Leandro works for Worldnet, a fintech company based in Dublin. His primary focus is designing, testing and developing prototypes before moving new features into production. Sinead is a Senior Multimedia Designer and works for TV3. She manages a team of designers and generates concepts across a wide range of media. Siobhan is a UX/UI designer working for Pramerica. Her focus is to conduct research, create meaningful information architecture, user flows and prototypes for enterprise applications.
As Siobhan is based in another part of the country, the group will have to work from different locations and explore tools that allow collaboration without compromising the research. The group is on a mission to save physical Post-its.
Project Goals
The team decided to work on one of the health & fitness apps available in the market. At the start of the project, the goal was to make it as broad as possible, letting the users guide the research to find which app/site is the most popular and what problems the users using this tool are facing. Therefore, the initial goal became to remove the hurdles that users of health & fitness apps face while executing their tasks, encouraging them to reach their goals. The idea was to make this project a consultancy piece.
Domain
The domain chosen was health & fitness as everybody in the group could relate to past frustrations using different apps. There are various options for apps and sites in the market (Fig. 1). The most popular health and fitness applications are MyFitnessPal, Garmin Connect, Samsung Health, Fitbit, Lose It!, Google Fit and Apple Health. Each app has a different approach: some are tied to a fitness tracker; some concentrate solely on exercises and others on nutrition. While the most popular apps have a holistic approach regarding health & fitness, other are exclusively focused on either nutrition or exercising. This diverse ecosystem broadens the initial research. The goal was to find users’ favourite app and what motivates them to use it.
After the initial discussions, the team wanted to find out more information about the users. A few assumptions were made:
Users have different goals (e.g. weight loss, muscle gain, healthy lifestyle).
Some users have to work around dietary restrictions (e.g. diabetics, coeliacs, allergic users, vegetarians, vegans, etc.)
Health and Fitness apps require the user to input data for them to work.
Different challenges were foreseen while gathering user information. People can be sensitive to talk about their weight; it’s essential to build a trust relationship with the interviewees. Another consideration is that users might have different behaviour from their attitudes, making triangulation of the pieces of information crucial to this project.
The information void
A series of questions were put together to remove the obstacles that users of health & fitness apps encounter in their interactions. What are the apps that they are using and what are the challenges they are facing? Who is the new design for, where and when will it be used? What are the users’ goals? What motivates them to use these apps? The information gathered during this process will help construct the Persona later in this project.
To get answers, a questionnaire was created using a tool called Typeform. The goal was to gather data from at least hundred users that use health & fitness apps. The questionnaire (Annex 1) was sent through social networks. Because the questionnaires were shared within team member’s circles, the data gathered can be skewed. Eventually, 180 questionnaires were collected, 132 of them being from people who are currently using health & fitness apps.
From the 180 participants in this questionnaire, 56% were female (Fig. 1). The most significant age group was situated between 35 – 44 years old with 45 people (Fig. 2). Even considering only participants using some health & fitness apps at some stage, the largest age group is still the same.
Figure 1. Participant’s gender graph.Figure 2. Participant’s age groups.
Nearly 74% of the participants used some health & fitness apps or sites at some stage (Fig. 3) with a higher percentage of women using these tools, 60.3% against 39.7% for the male counterpart.
Figure 3. Participant’s use of health & fitness apps.
The most popular app (Fig. 4) is MyFitnessPal with 45.5%. A variety of apps showed up that we did not identify at first. An in-depth analysis of the competition will be done in a later post.
Figure 4. Most popular health & fitness apps among the participants.
The participants use health & fitness apps at home (68.2%), gym (38.6%) and work (33.3%) (Fig. 5). Other users responded they use it during training. These individuals use apps more focused on tracking progress and performance (e.g. MapMyRun, Garmin Connect, Runtastic and Strava).
Figure 5. The preferred environment of use of health & fitness apps.
The questionnaire responses showed that users have different goals (Fig. 6): tracking progress (45.3%), weight management (28.2%), performance records (15.4%) and nutrition management (10.3%). Meanwhile, the goals of MyFitnessPal’s users are weight management (30%), track progress (30%) and nutrition management (11.6%). When asked about frequency of use (Fig. 7), 37.6% of the participants replied that they use the app multiple times a day.
Figure 6. The participant’s goals when using health & fitness apps.Figure 7. The frequency of use of health & fitness apps.
When asked about what the users dislike about the apps they use (Fig. 8), they were unhappy with the frequency they need to input data (26.7%) and that they felt that apps are impersonal (18.3%). People also responded that they forgot they had installed them (17.5%) and that they don’t see any improvements using them (16.7%).
Figure 8. The pain points of users of health and fitness apps.
The participants were asked what they like in the apps they use with an open question. After grouping the themes that emerged (Fig. 9), we discovered that the participants wanted ease of use, with simple and nice visuals. They also liked tracking information like calories burned, sleep tracking and distance walked without much interaction with the app. Users of apps focused on running and exercises liked features related to them: GPS tracking, distance measurement and timers.
Figure 9. Emerging patterns from the questionnaire.
The features they would like to have on the apps varied a lot; there was no consensus, but some desired features appeared more frequently:
chat feature / AI bot / chatbot
easier input options
keep users motivated
copying meals from one day to another
food displayed based on user’s location
MyFitnessPal’s users rated their experience 3.8 (Fig. 10) on a scale where 1 would be a bad experience, and 5 would be considered a very good experience.
Figure 10. Rating of the overall experiences (all apps). MyFitnessPal’s users gave it a score of 3.8.
To help build the personas, the users were questioned about some habits, preferences and products that are part of their search for a healthy and fit lifestyle. It appears that 41.2% of the users of health & fitness apps do not use fitness trackers (Fig. 11) and that 68.2% don’t use social media to keep themselves motivated (Fig. 12). When asked if they use other methods to keep track of their progress, 62.6% use only the app of their choice (Fig. 13).
Figure 11. Participant’s use of fitness trackers.Figure 12. The use of social media to keep users motivated.Figure 13. The alternative tracking methods.
To find new exercises and diets, friends are the biggest source of information for 47.3% of the users together with Google (Fig. 14). When asked if they have long-term or short-term goals, 75.8% of the participants responded that they have long-term goals (Fig. 15).
Figure 14. How users find new exercises and diets.Figure 15. User’s long-term vs short-term goals.
Finally, running was the most popular sports practised by the participants with 57.7%, following by weight training with 41.5% and cycling with 34.1%. Football, GAA and rugby came at the bottom (Fig. 16).
Figure 16. Sports practised by the participants.
A total of 26.3% of the participants do not use any health and fitness apps. They were asked three open questions about their reasons: it appears the majority of the participants who do not use health & fitness apps have no interest or feel no need to use it. When asked if there were any feature they would like in the apps, a recurring answer was to have something easy to use, and that could also educate them about macronutrients. Finally, when asked about why did they delete apps that they previously installed, the majority had never installed any health and fitness apps.
The quantitative research gave indications as to who were the users necessary for the qualitative study and also indicated that MyFitnessPal is the application the team was going to focus.
Before starting the qualitative research, a Perception Test (Annex 3) was engineered. The goal of the test was to verify the user’s awareness about the calorie content and weight of food items and to find if this has an impact on the lack of progress that users mentioned in the quantitative research.
Three different tests were performed. A food item was placed in front of the participants, and they had to guess its weight and calorie content.
The tests were made with a block of cheese (Fig. 1), a plate of mashed potato (Fig. 1) and an apple (Fig. 1). Before the tests, it was established that any answer between 10% more or 10% less from the actual answer would be accepted as correct. In total, 71 people participated in this exercise.
Block of cheese
Mashed potato
Apple
Figure 1. Items used during the Perception Test.
Results
The results (Fig. 2) showed that 22.53% of the calorie guesses stayed within the established accuracy margin while 15.49% of the weight guesses remained inside that margin.
Figure 2. Participants’ accuracy.
Block of Cheese
Mashed Potato
Apple
Touching Allowed
Yes
No
Yes
Multiple Choice
No
No
Yes
Number of Participants
21
30
20
Weight
180 grams
285 grams
133 grams
Calories
702 kcal
233 kcal
70 kcal
Weight (± 10%)
4.75%
15%
35%
Calories (± 10%)
9.52%
23.33%
35%
Figure 3. Perception Test data.
In conclusion, participants were not able to have an accurate or an approximate accepted guess when comes to weight and calorie contents of food products, but when having a visual aid together with a multiple choice, their accuracy increases substantially.
