City Fit — A modern solution to outdoor fitness (A UX Case Study)

As the connection between metropolitan and rural regions is changing, moving around the city had additionally seen change over the previous years by overpopulation.

Different alternatives have recently appeared in the transportation field. Simultaneously, Simultaneously, the streets have become a great area for work out.

City Fit is an app that is designed to help users stay active and find work out areas while still living in a populated city. By providing users the ability to find optimal routes to exercise in the city, it may help citizens to navigate the streets in a more efficient way.

The Goal

Our team focused on the following key question to start the research:

“How Might WE organize the variety of people navigation the streets to provide a more efficient and cleaner city?”

City Fit’s mission is to help the citizens living in overpopulated cities to be able to find places to exercise among the chaos that cities are generally known for.

Research Phase

First, our team had to conduct a research to lead to some initial data to determine the heading of the app that we’re developing.

► User research: Quantitative Data

First, we used a Survey Canvas to elaborate our survey and determine which questions would be helpful for our project.

After finalizing our survey canvas, we created a survey with 10 questions to collect some initial responses to questions that we made. We we’re able to obtain 32 responses from the survey and the results provide our team very important information about our audience:

Some survey results

The biggest frustration among the people living in cities that took the survey was the absence of areas/routes to go workout in the city.

► User research: Qualitative Data

After seeing the results of our survey, we conducted 4 interviews with people that mos likely would use our app based on the survey questions.

We also made an Interview Guide to conduct the interview efficiently and get to ask more specific questions!

Interview Guide

The interviews provided us more insight into our users, and help us determine in what direction the project is going to go and what are the issues that we need to focus on.

Here are the most important insights that we learned from our user interviews:

• The people that we interviewed don’t feel to comfortable working out in the gym.
• People want to feel motivated while working out.
• Most people prefer working out outside, but they also want to feel safe.

Define Phase

► Affinity Diagram

After concluding our research, our team developed an affinity diagram using miro to brainstorm ideas based on the data that we gathered from our interviews. The affinity map allow us to identify patterns among the insights that we collected to determine three main pain points that people working out in cities are experiencing.

► Empathy Map

We used empathy maps to comprehend the scenario of our users and understand their personality: to understand how they feel, what do they do, what do they hear, what are their dreams and what are their fears.

The empathy map was really useful for our project, it help us to empathize with our users and understand how they feel about exercising in the city, what are their emotions towards seeing large crowds, pollution, and homelessness and how do they affect their working out experience in the city.

► User Persona

Based on our empathy and affinity map, we created a Alice, our user persona to reflect our primary user’s characteristics (Our target group), frustrations and needs.

Primary User Persona

► User Journey Map

Alice’s User Journey provide us insight into a whole day in the life of our user, and also provide opportunities for us to ideate solutions to solve our user’s frustrations.

• Alice is Irritated by the large crowds of people while working out.
• She feels demotivated the rest of the day, after a frustrating day of workout.

Ideation Phase

► How Might We? Statements

After learning about our User struggles and needs, we created three problem statements based on our user’s experience while trying to exercise outside in the city.

How might we make our users feel safe while exercising outside?

How might we make our users avoid large crowds of people in the city?

How might we make our users explore new areas/routes around the city to workout?

We ideated possible solutions for these three problem statements and each member came up with different results.

► MoSCoW Method

We used the HMW Statements to create the solutions to solve the main struggles that people living in the city are facing. The MoSCoW method was used to prioritize the “Must Have” features for our app in order to solver our user’s frustrations.

► The MVPs

The main three problems that we we’re focusing to solve were: make our users feel safer while working out in the city, make our user avoid crowds of people, and facilitate routes/areas for our user to workout in the city!

Based on these three problems, we designed three solutions:

• Provide the user with safer routes around the city.
• A feature that allows users to see how crowded an area/route is in real time.
• A feature that grant the user routes/places around city to workout.

► Metrics:

How do we know our app is being successful? and How do we know our app is unsuccessful?

Conclusion

• Some surprises that we found out while working on this project were that a large amount of people don’t use any type of fitness apps
• Some people find gyms too competitive and that’s why they don’t go to them
• Key learnings that we learned in this project were
• To prioritize our features, based on what our audience is looking for
• And one key learning that I would keep in mind for the next project is to make more specific questions on our survey to get better data.

Thank you for reading!