Re-designing Maps for Navigation and Tracking

The digitalisation of maps has influenced humans to heavily rely upon them. One doesn't need to be familiar with the place to reach their destination or roam around a city (in the case of tourists) anymore. Traveling and connecting from point to point has been broadly simplified with the emergence of Google Maps as well as inbuilt maps in ride hailing and food delivering applications in India (Ola, Uber, Swiggy, Zomato, Dunzo to name a few). The reasons for the usage of these digitalised maps in the past few years have been different for each user. Some users use it to navigate their way through to reach their destination while some use it for getting around a new place for tourism, some use it to track where the food they ordered is while some others use it to know how far their given taxi is.
In this study, along with three of my peers, I tried to understand the user experiences and usability issues while using maps for two of the aforementioned reasons - navigation and tracking. This was done as part of our course - Human Computer Interaction - and we applied our learnings into this project.
Research
Since we were still in the middle of a lockdown subject to the COVID-19 pandemic, research was largely done remotely. We conducted in-depth qualitative interviews via Zoom as well as a survey interpreted through Likert Scales using Google Forms. We developed separate questionnaires and interview plans for navigation maps and tracking maps and the research was taking place simultaneously.
In the case of the navigation maps, the interviews aimed to uncover not just the unique aspects of each user’s experience but also the larger frame of travelling and how navigation is tied into that. What sort of traveler you are, or what your needs are as a traveler - long distance vs short distance, business or leisure, within a known or unknown city or place - were taken as the key determinants of users' navigation experience.
For the food tracking maps, the larger frame of experience was also affected by how ordering became mostly a joint exercise, in the pandemic times, with family members weighing in on the restaurants to order from and the food items too. The interviews, hence, also focused on the effect of the pandemic and how it influenced the user experiences from the customers' perspective.
Nine semi-structured qualitative interviews were conducted in all - four for navigation maps and five for food tracking maps. Twenty nine responses were collected from the survey through google forms - fifteen for navigation maps and fourteen for food tracking maps. Beyond this, relevant literature based on the topic was studied to foster our understanding.
Affinity Diagrams and Mind Maps
The data collected from the research phase revealed a diverse range of user experiences. We used the help of Google Sheets to form a data set from the interview notes (field notes were taken while the interviews were conducted, we also recorded the online meetings with the consent of the participants). From this data set, we were able to form themes by identifying common pain points and issues, and some that were very specific to the kinds of experiences that the users had on particular instances. To simplify these themes, we made affinity diagrams for both the categories. These affinity diagrams were further simplified into mind maps which are shown below:
Personas and Scenarios
After forming themes and affinity diagrams, it was perfectly set up for us to use our creativity and imagination to form user personas which could lead us to understanding the design problem that requires solution. We formed three personas - Shreya, Rohit, SK Bansal. Shreya and Rohit are involved in food ordering while SK Bansal is involved in navigating to reach his desired destinations. We elaborated Shreya's persona a little more and formed a scenario from her imagined life. The three personas are as follows:



SCENARIO
Shreya is looking forward to a long weekend, and decides to treat herself to her favourite donuts from a nearby place. She goes onto the app Swiggy to place an order, and finds herself ordering a few more things - a pizza and a plate of starters as well - as her brother also wants to order something. Her estimated time of delivery is 35 mins, and it is evening around 5:20 pm. This is a period of rush and traffic on some roads, but since the place she is ordering from is nearby, she anticipates that traffic won’t be too much of an issue. So she places the order, makes her payment, and puts aside her phone. 15 minutes in, she senses her phone vibrating, and picks it up to see missed calls from the delivery person. She calls him from the button on the map and sees that he is stuck in the lane opposite from hers. She explains to him to come to the exact location. When he still doesn’t understand, she shares the location using Whatsapp share a location feature. He confirms that he has understood and reaches. He then tells her that due to a blockade on the usual route he had to take some other route, and hence he reached the opposite lane, from where he didn’t know how to proceed, and the app’s map wasn’t helping. Shreya takes her delivery and thanks him.
Design Concept
With the personas and scenarios done, we understood the broad usability and design issues that we wanted to address. We landed to a design concept which was to modify some features in both Google Maps and the inbuilt maps in Swiggy. We designed a rough wireframe of the prototype by hand for Google Maps and on Miro for Swiggy.
Design issues addressed by us is shown in the table below:
The design concept (for Swiggy only at that point of time) is pitched by us in the video below:


Final Prototype
The final prototyped version included a few new features proposed as design solutions addressing the usability issues identified from our user study. We used Figma to prototype our solutions for both Tracking in Swiggy's Map and Navigation in Google Maps. After completing a first iteration of the prototypes, we took the design under evaluation which in turn helped us improve our prototype and incorporate more thoughts and opinions of users. The features of the second and final iteration of the prototypes are shown below:
SWIGGY's MAP FOR FOOD TRACKING
GOOGLE MAPS FOR NAVIGATION
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