Updating a Search Form
In only one year
The Challenge
Three issues had emerged:
Simplify the search form (UX and Product)
Over the years, the form had accumulated too many fields (from basic search inputs to highly specialized modifiers) overwhelming both new and experienced users.Modernize outdated components (UX)
The form was built on deprecated UI patterns and needed to be rebuilt using current design system components.Maintain feature parity with legacy tools (Product)
Leadership and commercial teams requested that legacy modifiers be supported to ensure parity with older systems that handled niche search needs.
Goal: Simplify the form while retaining flexibility for expert users and complex edge cases.
Ambiguity in the Brief
The initial requirements were vague: “Make search easier, add more modifiers, and update the UI.”
However, there was no agreement on what “easier” meant. For some stakeholders, it meant fewer fields and simpler workflows. For others, it meant more visible access to advanced legacy power features. The brief was ambiguous, and the use cases ranged from novice agents to seasoned experts with 20+ years of experience.
Discovery & Framing
I began by mapping the entire search ecosystem:
Which workflows depended on it
The purpose and history of each modifier
How and why legacy modifiers were used
Differences in usage between agent personas
I studied legacy advanced search forms, API modifiers and interviewed internal trainers, subject matter experts, and both novice and expert agents. I also observed live booking sessions using FullStory to understand real-world interaction patterns.
With a solid understanding of the problem space I then started wireframing the workflow.
Definition
I framed the problem as:
“How might we reduce cognitive load while preserving expert power?”
This became our guiding principle: Progressive Disclosure: show only what’s needed upfront, but allow deeper control when required.
Design & Prototyping
In Figma, I designed a modular layout that could flex for different user types:
Basic Search: Clean, minimal layout with only the most-used fields.
Advanced Drawer: Expandable section revealing advanced filters for experts.
Saved Search forms: either as persistent fields, saved templates, agent credentials, or context driven AI
Validation
We conducted remote usability tests with five agents, comparing the legacy and redesigned forms.
Results:
Every participant preferred the simplified layout.
Expert users appreciated that advanced options weren’t removed, noting that they were simply better organized and easier to find.
Delivery & Collaboration
The epic was divided into smaller feature tickets. I collaborated closely with developers to define component behavior in Figma, shared interaction specs via Storybook, and aligned on how preferences should persist across sessions (a key feature for advanced travel agents).
However, implementation slowed as other priorities took precedence. This stretched the timeline considerably, leading to partial adoption: some fields used updated components, while others retained the old design, creating a visible UI mismatch. To mitigate this, I broke the remaining updates into smaller chunks and aligned them with related development work whenever possible.
Unexpected Technical Challenge
During testing, agents expressed a strong desire to search by flight number (a common need for frequent travelers). While the design accounted for this, development stalled when the lead engineer noted that the API required both a flight number and departure time - data agents typically do not have.
I reached out to the API team to confirm and explore workarounds, but they verified that the limitation was inherent to the data model. Ultimately, the feature had to be abandoned until future API updates could address it.
Outcome
After extensive research, design iteration, and phased implementation over the course of a year, the redesigned search form was fully (almost) released and well received by agents. The modular layout and progressive disclosure pattern balanced simplicity with expert flexibility delivering a more intuitive, modern experience while laying the foundation for future enhancements.
Potential futures: Persistence, templates and adaptive content (AI generative UX)