Google Maps
Role: UX Researcher, UX/UI Designer
Tools: Notion, Figma, Amazon Mechanical Turk
Team: 2 Designers/Researchers
Timeline: June 2022 - August 2022
Keywords: Quantitative User Research, UX/UI Design
Overview
Google Maps is one of the most powerful and efficient tools for travelers around the world and residents in metropolitan areas to explore nearby restaurants, utilities, shops, and more. This project aims to learn about Google Maps users behaviors associated with different pages and features, define problem space and design space for possible improvements, and design a more appealing and optimized Google Maps system that can foster a smoother user tasks flow and using habit in Google Maps. After several rounds of qualitative and quantitative user research, the team decided to focus on current Google Maps "Save" system and optimized current interactions to better integrate "Save" feature with the main interface.
Execution
1.1 Quantitative User Research
1.
User Research
Tool: Amazon Mechanical Turk, Qualtrics
Sample Size: 60 participants
How often do you use THIS page?
Number of users who chose "Very frequently" to the question
Results show that Google Maps users interact with "Explore" and "Save" page more frequently than other pages.
How useful do you think THIS page is? (0-10)
The average score of the "Explore" and "Save" page is close to the highest score ("Go"), which shows the core value of Google Maps.
1.2 Qualitative User Research
Tool: Zoom Interview
Sample Size: 10 interviewees
Summary of Insights
Lack of interactivity between pages
There is not enough user engagement and interaction between the Saved function and Go page. Functions remained isolated for many users.
Users focus more on the “Explore” page
Some Google Maps users have a pain point that they sometimes fail to use those less salient but potentially helpful features as consistently and frequently
Fragmented use attempts make it hard to develop system in Google Maps
Users have not developed a systematic use habit that can integrate Google Maps into more aspects of their lives.
1.3 Hypothesis and Problem Definition
"People tend to use Google Maps on a fragmented basis because it would cost more time and effort for them to complete tasks they usually fulfill with other applications. The current system is not connected enough for users to adopt beyond navigation and review purposes. Therefore, there is a need for a more visually effective design for interaction between the “Saved” and "Explore" page so that users can have a more engaging and consistent user experience in Google Maps."
2.
Prototype Design Iterations
The question is: how might we provide users with a more engaging and structured user experience in Google Map?
2.1 Low-fidelity & mid-fidelity prototypes
User Task Flow
Low-fi prototype
Mid-fi prototype
2.2 A/B Testing
Tool: Amazon Mechanical Turk, Qualtrics
Sample Size: 60 participants
Test B
Test A
Test B
Test A
Test B
Test A
Test A
Test B
We designed an A/B Testing survey to validate our design hypothesis.
Participants who receive test A will answer all the scenario questions, evaluate the design efficiency, and indicate their preference with the original design of Google Maps. Another group of participants will be given the B version of design, which is the mid-fidelity design from above.
The survey result indicates that the average efficiency of design A is 6.45, and the average usefulness of design A is 7.10, whereas the efficiency of design B is 7.62 and its usefulness 7.76.
The data from the tests is encouraging to us and our design. Therefore, we moved on to refine the high-fidelity prototype.
2.3 High-fidelity prototype
Recommendation Algorithm Based on Saved Items
Task Flow: Time-saving Autosave
Structured and Intuitive Saved Lists
2.4 Video Demo: 3 User Task Flows
Algorithm Recommendation
Filter Saved Restaurants
Autosave
The above videos illustrated how users will be able to have a customized, intelligent, and integrated user experience with an algorithm + visual design + interaction optimized "Explore" and "Saved" system.
Reflection
It is critical for UX designers to look at an existing digital product or competitors from a holistic perspective that combines user experience, design goals, business needs in order to balance between minor cosmetics changes and underlying features improvement. During the initial research process, I found that conducting more in-depth qualitative user interviews is helpful when facing limited resources or lacking representative data. Although platforms like Amazon MTurk allows the researchers to apply filters and sending out UX surveys based on certain user portraits and demographics, there can be some valuable details that a simple survey can not discover. The ability to ask follow-up questions immediately provides UX researchers and designers more opportunities to extract truthful and useful data in a single interview session.
From the design aspect of this case study, we are trying to design an improved and more cohesive user journey and workflow by connecting scattered features together smoothly. However, when we actually started to redesign the features, we found that designing a service is more important than designing an interface with fancy interactions if the basic logistics of the features is not reflected to the users clearly. The final results of this case study might be at a cosmetic design level since we are trying to rework the transitions among different pages and features instead of designing a brand-new features, so the next step of this project would be to evaluate the efficiency of the redesign and try to explore more variety of feature designs.