Moderator One
Enriching quantitative surveys with AI-driven qualitative depth.
An AI voice interface designed to capture deeper insights at the end of traditional surveys. By engaging users in short, natural follow-up interviews, we bridged the gap between data and meaning without increasing friction.
Context
Moderator One was designed to add a qualitative layer to quantitative data. The goal was not to replace surveys but to enhance them by asking AI-driven follow-up questions based on previous answers (e.g., expanding on a rating). The challenge was to gather meaningful voice feedback in a separate post-survey experience without causing user drop-off, all while delivering a functional MVP under tight constraints to validate market interest.
Approach
Working in a small, agile team required covering multiple domains simultaneously. My design approach focused on three pillars: ensuring a low-friction experience to maintain conversion, mastering voice interface principles for natural interaction, and balancing depth with simplicity to prevent user fatigue. I collaborated closely with the team to define MVP scope, making strategic trade-offs to meet budget and delivery timelines.
Solution
I designed a minimal, voice-first interface that guided users through AI-generated questions, allowing them to respond naturally. Visual elements were kept simple to support the audio flow rather than compete with it. Beyond the core experience, I designed a web-based admin panel for researchers to configure probing depth and emphasis, as well as the marketing website (built in Webflow) and visuals to communicate the value proposition. The solution was fully responsive, ensuring accessibility across web and mobile contexts.
Outcome
The project delivered a functional MVP that successfully augmented traditional surveys with qualitative insights, proving that deeper feedback could be collected without significant abandonment. The MVP served as a tangible asset for client conversations and partnership opportunities. Personally, it expanded my expertise into voice UX, multi-platform design, and lean product validation.
Key Learnings
“This project highlighted the nuances of designing for emerging interaction models like voice, where pacing and clarity are essential for user comfort. It reinforced the value of solving specific problems with a targeted MVP rather than a universal solution, allowing for faster learning. Finally, the multidisciplinary nature of the work emphasized the importance of versatility and close collaboration in early-stage product development.”