Project Overview
As part of the Human-Computer Interaction curriculum in the Masters of Information Management program at the University of Maryland, our research team conducted a comprehensive usability evaluation comparing Google Maps and Apple Maps on iOS devices. Conducted in 2014 when mobile mapping applications were rapidly evolving, the study examined how users across different age groups and experience levels interacted with each platform's interface and feature set.
The research employed Norman's Four Principles of design as our evaluation framework, assessing functional visibility, conceptual models, user-centered design, and error handling across both applications. Our participant pool included family and friends representing a broad spectrum of ages and technical proficiency levels, providing diverse perspectives on interface intuitiveness and task completion effectiveness.
The study revealed unexpected findings: while Apple Maps demonstrated faster task completion times and higher success rates, Google Maps received higher satisfaction ratings from users — particularly younger demographics — despite taking longer to complete identical tasks. This disconnect between performance metrics and user preference provided valuable insights into the complex relationship between familiarity, aesthetics, and perceived usability.
Evaluation Framework & Scope
Role
I served as a research team member, collaborating with classmates to design the study methodology, recruit participants, conduct testing sessions, and analyze results. My responsibilities rotated across sessions and included asking scripted questions, timing task completion, observing user behaviors, recording data, and contributing to findings analysis and report synthesis. Each team member recruited three participants from their own personal networks to ensure age and background diversity across the participant pool.
Research Hypotheses
Task Scenarios & Timing
Tasks were selected to represent real-world navigation scenarios of increasing complexity. Participants alternated which app they started with to control for order effects. Average task completion times (in seconds):
| # | Task Description | Apple Maps | Google Maps | Winner |
|---|---|---|---|---|
| 1 | Find a Starbucks — basic business search used as a baseline; most participants had no difficulty with either app. | 27s | 32s | Apple Maps |
| 2 | Get directions from the Empire State Building to the Washington Monument — tested intuitiveness without using current location. The largest performance gap of any task. | 68s | 158s | Apple Maps |
| 3 | Get directions from current location to the nearest Starbucks. Both apps defaulted to the Empire State Building (last location from Task 2), tripping many participants. | 58s | 51s | Google Maps |
| 4 | Share current location via message or email without typing an address. Only 3 participants completed this independently on Google Maps — the feature path was non-obvious. | 45s | 103s | Apple Maps |
| 5 | Use voice to find directions to the nearest CVS. Participants unfamiliar with iPhones didn't know to press the home button to activate Siri, inflating Apple's time. | 73s | 27s | Google Maps |
Key Findings
Apple Maps achieved 43/45 completed tasks (95.6%) vs. Google Maps 40/45 (88.9%). Participants starting with Apple Maps completed tasks faster, and order effects showed initial exposure created momentum advantages.
Google Maps SUS mean: 65.28 vs. Apple Maps 63.06. Users expressed preference for Google Maps even when they took longer or completed fewer tasks — driven by brand familiarity, aesthetic appeal, and feature richness perception.
Apple Maps performed better with users over 40. Google Maps resonated more strongly with users under 40. A 74-year-old participant rated Apple significantly higher than any other demographic — suggesting generational design preference differences.
The most striking finding: objective task data supported Apple Maps superiority, yet SUS results and expressed preference favored Google Maps. Aesthetic appeal, brand familiarity, and feature richness perception all contributed to the disconnect.
Three additional dynamics shaped the results: participants least familiar with either app often performed tasks most intuitively, suggesting that experience with one platform creates cognitive barriers when switching to another. Platform integration gave Apple measurable structural advantages — Siri and system-level location services aren't accessible to third-party apps. And first impressions persisted — users carried mental models from whichever app they started with, affecting how readily they discovered alternative interaction patterns in the second.
Observed Behaviors
- Voice commands were preferred by users unfamiliar with search box interfaces — particularly in Google Maps, where the microphone affordance was more discoverable.
- Word choice significantly impacted search success rates; small phrasing differences caused task failures even when participants knew exactly where they wanted to go.
- Map location history didn't reset between tasks — both apps remembered the Empire State Building from Task 2, unexpectedly tripping participants on Task 3 when searching for current location.
- A halo effect was observed: one participant's positive experience with a single feature colored their entire SUS rating of that application.
- Users projected emotion through voice tone when interacting with navigation — frustration was audible before participants verbalized any difficulty.
- Participants who didn't regularly use map apps struggled most with Task 5; non-iPhone users had no frame of reference for pressing the home button to activate Siri.
Research Challenges
Many participants had strong muscle memory from their primary mapping app, creating inherent bias when testing the alternative. Isolating genuine usability differences from learned behavior required careful analysis of first-time responses.
Testing exclusively on iOS gave Apple Maps structural advantages through Siri and system-level location services — making it difficult to determine whether Apple's performance edge reflected better design or platform-level integration.
Recruiting through personal networks provided wide age diversity but introduced potential homogeneity in technology adoption patterns. Conclusions required cautious interpretation given the non-randomized selection.
Future Improvements
Study Artifacts
