Usability Testing and Redesign of Google Maps
This project focused on improving the usability of Google Maps' multi-stop route planning, location-based discovery, and public transport features. Through extensive user testing on both the smartphone app and desktop site, key pain points were identified, including inaccurate travel time estimates, inconsistent points of interest (POI) discovery, and difficulties in planning future public transport routes. The research provided critical insights to optimize Google Maps for a growing population of commuters in a post-pandemic world.
Project Details
Role
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UX Researcher
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UI Designer
Tools
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Adobe Photoshop
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CIF Usability Standards
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Figma
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Microsoft Office
Timeline
October 2023 - January 2024
Platform
Desktop Website
Mobile Application
The Problem
The Solution
Challenge:
Google Maps, despite its dominance as a navigation tool, struggles with specific usability issues related to multi-stop route planning, inconsistent POI discovery, and difficulty finding optimal public transport routes. These challenges hinder users’ ability to plan routes effectively, particularly when navigating multiple destinations or exploring nearby locations.
Why It Mattered:
With commuting on the rise post-pandemic, and as younger generations enter the workforce, ensuring that Google Maps addresses the evolving needs of commuters is crucial. Improving these key functionalities would enhance user satisfaction, efficiency, and overall navigation experience for millions of users.
To address the usability challenges identified in Google Maps, the project focused on redesigning key functionalities to enhance user experience, particularly for commuters and travelers. Due to time constraints, the redesign prioritized Location-Based POI Discovery, which had the highest frustration and error rates. The proposed solution introduces an Explore Radius Feature to improve POI visibility and a more intuitive List Creation Interface to simplify saving and sharing places.
These changes aim to resolve inconsistencies in POI discovery and streamline the user journey for mobile and desktop platforms. While improvements to Multi-Stop Route Planning and Public Transport Planning were identified as future opportunities, the initial redesign focuses on delivering immediate impact by addressing the most critical pain points, enabling Google Maps to better meet the evolving needs of its users.
Table of Contents
Research Phase
Survey & Participant Selection:
To ensure the usability testing would accurately reflect user behavior, a survey was conducted to screen participants based on their age, frequency of use, and confidence in navigating Google Maps. The target demographic for the test was users aged 25-34, which represents 28.55% of Google Maps' user base according to data from SimilarWeb. A sample size of 18-20 participants was initially desired—9 for mobile testing and 9 for desktop. However, due to time constraints and participant availability, 10 participants were selected.
Participant Profile:
Out of the 12 people who filled out the screening questionnaire, 10 participants were chosen via outreach on WhatsApp and social media platforms. Though the selected participants did not fully align with the target age group, their frequent usage of Google Maps and high confidence in using the app made them suitable for testing. The participants included:
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2 benchmark users from the 25-34 age group.
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1 participant from the 36-50 age group, providing insight into potential usability gaps for older users.
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The majority were from the 18-25 age range, offering a perspective on improving the app's appeal to younger users.
Challenges with Representativeness:
The actual sample wasn't fully representative of the intended target group (25-34 years), largely due to difficulties in reaching participants from that demographic. However, the selected participants, despite their different age ranges, offered valuable insights due to their frequent use of the app. Including both younger and older users also helped identify broader usability issues and opportunities to expand Google Maps’ appeal across different age groups.
Key Insights Gained from Participants:
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Usage Patterns: Participants across all age groups demonstrated confidence in using the app, but their pain points varied depending on the task and device.
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Benchmarking: The inclusion of the 25-34 age group, alongside other age groups, highlighted specific areas where the app could better meet the needs of its target audience.
Design Process
Usability Testing on Stock Google Maps:
Before moving forward with any redesigns, participants were tasked with completing three real-world scenarios on Google Maps. These tasks aimed to evaluate the effectiveness and usability of core features across both the mobile and desktop versions of the app.
Task 1: Multi-Stop Route Planning
“Find the best route to Church Street from Four Seasons Bangalore, picking up your friend from Lulu Global Mall in one search.”
The goal of this task was to assess how easily participants could plan a multi-stop route, a key functionality for commuters and travelers.
Task 2: Location-Based Discovery
“Find restaurants and cafes near Church Street, add them to a list, and send the list to a friend.”
This task was designed to evaluate how users find and share Points of Interest (POI). Participants encountered several usability issues:
Task 3: Public Transport Route Planning
“Find all public transport options for your friend to reach Church Street from Lulu Global Mall, arriving around 5:30 PM.”
This task evaluated the ease of using Google Maps to plan future public transport routes.
Findings from Stock Google Maps Usability Testing:
The usability testing on both the desktop and mobile versions of Google Maps revealed key insights into the effectiveness of its core functionalities across three primary tasks.
Task 1: Multi-Stop Route Planning
“Find the best route to Church Street from Four Seasons Bangalore, picking up your friend from Lulu Global Mall in one search.”
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Desktop Results:
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All participants successfully completed the task. The average completion time was 222 seconds (vs. expert time of 29 seconds), with low error and frustration rates.
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Key Issue: Participants found the lack of real-time traffic data on desktop problematic, which impacted the accuracy of travel time estimates. Despite this, they reported high confidence and satisfaction with the task overall, rating it as easy to complete.
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Mobile Results:
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On mobile, participants took an average of 301.8 seconds (vs. expert time of 33 seconds). There was an increase in frustration and difficulty compared to desktop, and participants expressed dissatisfaction with the lack of distance information for multi-stop routes.
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Key Issue: The mobile app did not display the total distance for the journey, which is a critical feature, particularly for users with electric vehicles. This led to increased task time and lower satisfaction.
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Task 2: Location-Based POI Discovery
“Find restaurants and cafes near Church Street, create a list, and share it with your friend.”
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Desktop Results:
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Participants struggled more with this task, with an average completion time of 276 seconds. Several users required assistance, and there were noticeable errors in generating shareable lists.
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Key Issue: The inconsistent display of POIs based on zoom level frustrated users, who found it difficult to see all available options. Furthermore, the list creation feature was hidden under the "Saved" tab, which was unintuitive.
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Mobile Results:
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The average task time on mobile was 338.6 seconds, with two task failures. Participants found the task significantly more difficult on mobile, reporting high frustration and low satisfaction.
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Key Issue: Creating and sharing lists was especially problematic on mobile due to the hidden and confusing list options, leading to increased user frustration.
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Task 3: Public Transport Route Planning
“Find all possible public transport options to reach Church Street from Lulu Global Mall, arriving around 5:30 PM.”
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Desktop Results:
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Participants completed the task in an average of 222 seconds. While the task was rated easier than others, the trust in public transport timings was relatively low.
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Key Issue: Although users completed the task with high satisfaction, they expressed skepticism about the accuracy of Google Maps' public transport timings based on past experiences.
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Mobile Results:
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Mobile participants took an average of 257.5 seconds to complete the task. There was a noticeable drop in trust and satisfaction compared to desktop.
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Key Issue: Participants struggled with filtering transport options for future times, and many found the interface confusing for combining different modes of public transport (e.g., bus and metro).
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Redesign Goals
Redesign Goals: Following the usability testing of the stock Google Maps, it became clear that addressing all identified pain points within the given timeframe was not feasible. As a result, the redesign effort focused specifically on Location-Based POI Discovery, which had the poorest performance in testing. The goal was to significantly improve user satisfaction and ease of use in this area.
Chosen Redesign Area:
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Location-Based POI Discovery:
Problem: Users struggled with inconsistencies in how points of interest (POIs), such as restaurants and cafes, were displayed depending on the zoom level. This confusion limited users' ability to discover nearby options, particularly on mobile. Additionally, the process of creating and sharing lists of these POIs was unintuitive and frustrating, especially due to the hidden list creation feature.Redesign Solution:
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Explore Radius Feature: Introduce an Explore Radius function, allowing users to set a search radius around their destination. This feature will display all relevant POIs within the selected radius in both list view and on the map, resolving the inconsistency caused by zoom levels.
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List Creation Interface Improvements: Make the list creation feature more visible and user-friendly. A dedicated List button will replace the current hidden location under the "Saved" tab, improving discoverability and usability on both desktop and mobile versions.
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Reason for Focusing on Location-Based POI Discovery: Due to the poor results in testing, especially on mobile, and the high frustration and error rates associated with this task, it was prioritized for redesign. Time constraints prevented addressing all identified pain points (e.g., multi-stop route planning and public transport planning), but improving the POI discovery process was deemed the most impactful change within the project's timeframe.
Other Key Redesign Areas (Deferred):
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Multi-Stop Route Planning:
Problem: Users had trouble adding multiple stops in one search, and key information (e.g., distance on mobile, real-time traffic on desktop) was missing.
Solution (Future Consideration): Add total distance display on mobile and integrate live traffic data on desktop for better decision-making. -
Public Transport Planning:
Problem: Users found it hard to filter transport options for future times, and trust in the accuracy of transport data was low.
Solution (Future Consideration): Introduce a Future Availability Indicator for public transport, showing the next available time for each option.
Additional Redesign Suggestions (Based on Post-Test Feedback):
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Preferred Route Saving: Allow users to save custom routes they prefer but that Google Maps does not suggest. This feature will make commuting more efficient for users who have routes they commonly take.
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SOS Feature: In emergencies, users should be able to send their last known location or live location to emergency contacts directly from the app.
Prototypes
Lo-fi Prototype
Mobile Prototype
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Desktop Prototype
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Hi-Fi Prototype
Mobile Prototype
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Desktop Prototype
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Discussion and Conclusion
Discussion
The usability testing of Google Maps uncovered critical insights into users' challenges while navigating the application. Tasks such as multi-stop route planning and public transport planning revealed that while users could complete these tasks, the lack of crucial information—like traffic data on desktop or trip distances on mobile—hindered the overall experience. The most significant challenges were observed in Location-Based POI Discovery, where inconsistent data display and an unintuitive list creation interface frustrated users, particularly on mobile.
Despite Google Maps' position as a market leader, the testing highlighted gaps in its ability to meet the evolving needs of its user base, especially commuters and younger travelers. The results emphasized the importance of consistent functionality across platforms, intuitive design, and better discoverability of features.
The decision to prioritize the redesign of Location-Based POI Discovery was driven by its poor performance in testing and its impact on user satisfaction. Other areas, such as multi-stop route planning and public transport planning, were acknowledged as critical but deferred for future iterations due to time constraints. The proposed changes, such as the Explore Radius Feature and improvements to the list creation interface, aim to simplify complex tasks and reduce user frustration, particularly for mobile users.
This project not only demonstrated the importance of usability testing in uncovering hidden pain points but also highlighted the need for focused redesign efforts to deliver impactful changes within limited timeframes.
Conclusion
The usability evaluation and redesign of Google Maps underscore the value of user-centered design in creating intuitive, effective, and satisfying experiences. By focusing on Location-Based POI Discovery, the project tackled one of the most pressing issues identified in testing, providing clear, actionable solutions that promise to enhance the user experience.
Future work should address other identified pain points, such as improving multi-stop route planning and public transport planning, to create a more holistic and seamless experience. This iterative approach ensures that design efforts are grounded in user feedback and prioritize the features with the most significant impact.
Overall, this project highlights how usability testing and targeted redesigns can bridge the gap between user expectations and application functionality, reaffirming the importance of continuous improvement in user experience design.