CapMetro Transit Plan 2035
UX Research & Reporting
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Timeline - Tools - Role
Timeline
Pre-comment period (Summer–Fall 2024)
Comment Period
(Fall 2024)
Reporting
(Winter 2024/25)
Tools
Miro, PublicInput, Google Forms, ChatGPT, Claude, Monday.com, Microsoft Excel
Role
UX Researcher
Community Engagement Lead
Focus Group Facilitator
About
Situation
Pet Activity & Health Tracking App
This multi-month project centered on designing, executing, and synthesizing a large-scale, mixed-method research program to shape CapMetro’s 10-year transit vision.
CapMetro needed to ensure that the Transit Plan 2035 reflected the lived experiences and mental models of Austin’s diverse communities. With rapid population growth and historic inequities in transit access, traditional planning processes risked missing key user needs. That is where we stepped in!
Our team knew we needed to conduct human-centered, equity-driven UX research to yeild actionable feedback. The insights had to go beyond demographics and capture behaviors, motivations, and pain points to best shape the transit plan and research was needed to prioritize representativeness, accessibility, and bias reduction.
The goal was to design and execute mixed-method research, combining qualitative depth from focus groups with quantitative validation from surveys to uncover these needs, values, and behavioral patterns that would inform long-term transit strategy.
Task
Research Objectives
The objective of this project was to design and execute a human-centered research program that could capture the needs, values, and behaviors of Austin’s diverse communities and translate them into actionable insights for CapMetro’s long-term transit planning.
📍 Conduct inclusive focus groups, surveys, and pop-up events
→ Engage a wide range of participants across age, income, geography, and language to ensure representation.
📍 Methodological Triangulation
→ Applied qualitative generative methods (focus groups) alongside quantitative evaluative methods (structured surveys) to capture both attitudinal and behavioral data.
📍 Data Synthesis & Insight Generation
→ Integrate qualitative themes with quantitative evidence into a 73-page report, providing clear, actionable recommendations for transit planning.
📍 Inclusive Research Operations (ResOps)
→ Reduced bias and improved validity through accessible facilitation practices (bilingual moderation, ADA-compliant materials, hybrid participation options), ensuring research was equitable, representative, and replicable.
My task was to lead my team to deliver a rigorous, bias-aware UX research program that could generate trustworthy insights and translate them into evidence-based design recommendations for an improved public service ecosystem.
Action
Once we had a clear picture of the problem, it was time to roll up our sleeves and start building toward solutions. We broke the process down into focused steps that connected research to design decisions:
1) Focus Groups (Qualitative Discovery)
My team and I designed discussion guides with open-ended and scenario-based prompts, facilitating 16 moderated sessions (8–30 participants each) across Austin. Methods included participatory design exercises that uncovered hidden motivations, unmet needs, and behavioral barriers. I created inclusive conditions with bilingual facilitation, ADA-compliant materials, and hybrid options to reduce research bias and cognitive load.
It was important to me that I treated facilitation as experience design for research itself — reducing barriers so participants could contribute authentically and with psychological safety.
Key actions included:
📊 Moderating 16 sessions across diverse cohorts (youth, seniors, Spanish-speaking, riders with disabilities).
📊 Applying generative research techniques to surface latent needs.
📊 Enabling co-creation by guiding meaningful group discussions in real-world transit contexts.
📊 Lead a cross-functional team (moderators, note-takers, stakeholders) through bias-aware facilitation best practices.
2) Surveys (Quantitative Validation)
To complement qualitative findings, I distributed and assited in the design of a multi-question survey instrument on PublicInput and ran intercept surveys at pop-up events, focus groups, and at an open house to maximize reach and inclustivity. Our team produced 500+ responses across demographic segments, capturing behavioral metrics, attitudinal data, and satisfaction scores. I applied quantitative UX methods including frequency distributions, cross-tab analysis, and segmentation to validate qualitative themes.
By implementing surveying, our team:
💡 Reached 500+ respondents across diverse geographies and demographics.
💡 Applied methodological triangulation to strengthen reliability.
💡 Combined behavioral analytics with attitudinal sentiment mapping.
💡 Used survey data to statistically validate and prioritize focus group themes.
Analysis & Reporting (Mixed-Methods Synthesis)
After gathering data from both focus groups and surveys, the next step was to make sense of it all. I designed a mixed-methods synthesis process that integrated qualitative themes with quantitative evidence to ensure insights were both reliable and actionable.
Our team conducted thematic coding of focus group transcripts to identify recurring sentiment around safety, affordability, and accessibility. In parallel, I applied quantitative segmentation to identify priority groups by income, geography, and usage. Findings were triangulated into a unified insights framework, ensuring consistency across data sources.
Key steps included:
📍Applying affinity mapping and thematic analysis to code transcripts and cluster qualitative data into sentiment themes like safety, affordability, and accessibility.
📍Conducting sentiment analysis, cross-tabs, and segmentation on survey responses to validate focus group findings at scale and highlight demographic variations.
📍Delivering a 73-page insights report that translated research into design recommendations directly tied to user evidence.
Action
Results
Findings
After synthesizing insights from focus groups, surveys, and pop-up events, we identified recurring patterns that revealed both riders’ pain points and opportunities for improvement in CapMetro’s future transit design.
📊 Connectivity
→ Demand for seamless transfers, direct routes, and expanded coverage.
📊 Service Frequency
→ Long wait times were the biggest usability barrier.
📊 Desired Destinations
→ UT Austin, Downtown, East Austin, airport, and Zilker Park were high-priority nodes.
📊 Safety & Security
→ Reliability and reduced wait times are linked directly to perceptions of safety.
📊 Service Span
→ Strong demand for earlier/later service for nontraditional work schedules.
📊 Accessibility
→ Barriers for non-English speakers, riders with disabilities, and low-income communities.
📊 Affordability & Equity
→ Cost seen as critical, especially with over half of respondents earning <$75k.
📊 Engagement Reach
→ Hybrid approach engaged 14k+ people across surveys, focus groups, pop-ups, and digital outreach.
After translating these insights into actionable recommendations, the research directly informed CapMetro’s Transit Plan 2035, shaping priorities around equity, accessibility, and long-term usability.
Reflection
Front-to-End Project Reflection
This project strengthened my expertise in mixed-method UX research, combining qualitative (focus groups, thematic analysis) and quantitative (surveys, segmentation) approaches to generate actionable insights. I gained experience in research operations, from inclusive recruitment and facilitation to large-scale synthesis and reporting. Most importantly, I learned how rigorous, accessibility and human-first research can amplify community voices and translate them into evidence-based design recommendations that guide complex service ecosystems like public transit.
In addition to my research responsibilities, I also stepped into a leadership role, guiding our cross-functional team through planning, facilitation, and synthesis. I aligned moderators, note-takers, and stakeholders around consistent, bias-aware methods, ensuring our process was collaborative.
