A UX Case Study
Case Study Overview
Design Challenge Design a route selection feature for a navigation app to encourage tourists to take more walking routes in cities.
Team Members: Saurav, Ritika and Kuntal
Tools: Miro, Survey Monkey, Zoom, Figma
Duration: 7 days
Our Design Process
We began with some secondary research to further understand the problem and consider the things that need to be addressed for user research. The secondary research was split into 2 parts: how cities and organizations are working towards a more sustainable future for transport, and how organizations directly emphasize walking tourism. This helped us identify potential factors that may impact the users’ behaviours while travelling.
To better understand the needs and behaviours of our users, we conducted a user survey with 34 participants and 2 rounds of user interviews.
User Surveys As a team, we started off by understanding the problem and defining the target audience. We wanted to learn about users’ navigation trends, as well as personal travel habits to further define our target audience.
We crafted a survey facing various travel-related questions to obtain both qualitative and quantitative data. Our questions focused on 2 aspects: how do travellers navigate through an unfamiliar place and what are some reasons they choose to (or not to) walk to a destination.
- Most people plan their trips beforehand while only a small number explore a place on their will
- To our surprise, tourists actually walk a lot instead of using public transportation or cars when travelling
- Weather, good scenery, and attractions on-the-way are 3 of the common factors that motivates people to walk
- Google Maps is the dominant navigation tool people use
User Interviews In order to efficiently derive insights and user needs, we carried out 2 semi-structured interviews in order to discover further insights into the issues at hand. Both our interviewees are regular travellers but with distinct needs. We asked how often they travel each year and for what purposes, any issues related to travel in general, and their motivations regarding walking. We focused on these questions to understand how we can encourage travellers to walk more, and their needs while travelling.
- Similar to our assumptions and survey data, travellers’ main motivations for walking are budget-related and driven by exploration
- They are willing to walk more if they can find routes dedicated to sightseeing and understanding the local culture
- They are not specifically motivated to reduce carbon footprint when they choose to walk
We identified which companies are working towards a similar goal of simplifying users’ navigations and how their product impacts the behaviours users make. We did a competitive analysis among Google Maps, Apple Maps, and CityMapper to identify their own business model and what makes them stand out in the market.
This stage helped us identify the approach that these companies make towards more sustainable methods of travel such as walking, and how our product can help emphasize this further.
As we already learned through the user survey that Google Maps is the dominator in the market, we decided to do a redesign for Google Maps for these reasons:
- It dominates the market, which indicates users are less willing to see change within the app.
- Google’s business model generates billions of revenue through ads. When users search a location, different local businesses will come up along with advertisements. Our exploration feature (which will be explained later in the case study) will rank different listings similar to a Google search model, where ads will get a higher listing and better chance to appear in system-generated routes.
We gathered all the data collected from user surveys and user interviews and grouped them into 3 types of feedback, along with the category they fall into.
- From the Pain Points category, we learn that people don’t find enough time to explore new places and can’t rely on local people to always help them around
- From the Behaviours category, we learn that factors such as time and budget can be an issue when planning for travels and that walking helps to discover new local places
- From the Needs category, we learn that people want to discover new places during their route and need a cost-friendly way to do so
We created 2 personas to better understand the different approaches our user may take. The first persona reflects those users that have a destination in mind but are looking to explore further. The second persona reflects those users that have not made any travel plans beforehand and are looking for ways to discover the best routes for exploring.
How can we encourage tourists to explore cities through more walking?
After figuring out the needs of our personas, we set out to brainstorm ideas and sort it out using a prioritization matrix. This helped us identify the high and low impact features that we could potentially consider when building out our product.
Once we prioritized the functionalities our feature should offer, we made a user flow to illustrate the journey our user could take when interacting with our product.
Based off the user flow, we set out to create the IA of the app. We focused on ease of findability and usability, and used our 2 personas to guide the flow of the interaction.
Prior to creating the wireframes of our app, each team member made some sketches illustrating the different ways the user can interact with the product. We maintained a user interface similar to Google Maps for our screens and later decided as a team which screens worked best to move forth with.
Following our information architecture and user flows, we built our first low-fidelity wireframes, targeting issues and personas that were addressed.
From the user research, we learned that our target audience wants to walk so they can discover more of the city. They either have a destination in mind or want to explore along the way. Right now, Google Maps has 2 screens related to this purpose: explore, and the screen after searching a particular location. Both show the users’ nearby attractions. However, neither of these features targeted a core need: discovery along the way.
Taking the above into consideration, we decided to focus on an upgraded experience in those 2 screens and created our low-fidelity prototype based on existing functions and structures in Google Maps.
User Testing As we had a one-week timeframe to complete this challenge, we did not have enough time to test after completing our high-fidelity prototype, and it’s still not perfect at this stage. Under this constraint, our user testing session focused on discovery experiences. We focused on their visceral reactions and tried to find out if there is anything that could be improved within the usability or user interface. We used Figma’s own prototyping tool to test with users.
- Initially, our radius feature might be confusing because our prototype does not allow actual zooming in or out
- The user flow is clear and our users love to play around with each route to see what could be different
- Some other issues included the routes on map not being distinct enough
We built our high-fidelity designs based on user feedback. Here are our final designs explained.
Find Routes Explore nearby attractions from the explore tab.
Explore your Radius Users can adjust the walking radius based on the desired walking time or distance. The user can see selected routes beneath the radius.
Google Maps will generate different routes according to the walking radius and the destination the user had inputted. Locations included in each route is depending on the user’s preference, reviews from other users, and advertisements.
Customize your Route Users can select attractions in the previously indicated radius and add to their own custom routes. It’s similar to the saved lists functionality in terms of adding specific locations. However, this function also forms a curated walking route with optimized walking distances and sightseeing options along the route.
Problems we Faced:
- Time constraints We began this challenge a week before the deadline and were short on time in some areas of the design process.
- Time zones All members on the team were in differing timezones which affected some communication and collaboration.
- Skill levels Not all members of the team had a design-related background or significant experience in the field, which may have resulted in minimum collaboration around some parts of the process.
Further Steps Due to the small time constraints, we weren’t able to conduct formal usability testing and there are definitely some more questions we hope to answer.
- Does the transplanted mental model of “route cart” for customized routes make sense to the user?
- Are the customization and generated routes the best method for encouraging exploration?
In addition, we would love to develop a plan to measure our success based on usability matrix and business objectives.