Role: Senior / Lead User Researcher
Timeline: ~8–10 weeks
Partners: Product, Design, Analytics, Airport Operations
Airports were 20% of Lyft’s business, and the one place where it had parity with Uber. Given that, the Airports team decided to invest in a new Rider experience to make ordering airport rideshare easier, to improve Lyft brand preference, and market share.
Rideshare riders are unclear about where and when to order a ride upon landing at the airport to minimize wait time. This leads many riders to order too early or too late, which impacts the Rider, Driver, and marketplace efficiency.
The team created a pre-order product to enhance the Rider ordering experience and improve demand signals for the marketplace.
Rapidly evaluate early concepts and flows to identify usability issues and validate whether proposed solutions reduced perceived risk for Riders.
I designed a 2-phase study which
included a foundational study to get signal around the problem space.
Iterative RITE concept testing with airport-active riders, partnering closely with Product and Design to make real-time improvements across multiple design rounds.
Participants provided strong signal around the problem space. However, they were confused by several aspects of the experience (rules, status, consequences) which increased rider anxiety and decreased confidence that the preorder system would work.
Iterative testing greatly increased comprehension of the product through improved education and simplified design.
Improved concept clarity and usability before engineering investment
Helped teams converge on fewer, higher-confidence solutions
Accelerated decision-making in a fast-moving problem space
Lyft | Airport Driver Foundational UXR
Facing low conversion among airport drivers, this foundational study examined how drivers evaluate trips from the airport and experience each step of the airport journey, from arrival to pickup. The insights directly shaped product direction to reduce friction and improve adoption.
myStrength | Small Change, Big Impact
Evaluative research surfaced a subtle interaction pattern in clinical assessment questions that led users to answer incorrectly. Addressing this small UI detail helped protect the integrity of myStrength’s diagnosis and recommendation system and was prioritized into production within weeks.