Gallery
Experiment overview
A conversational research bot designed and developed to transform formal data collection into natural dialogue through strategic personality design and trust-building mechanisms.
The initiative reimagined research interactions by creating a digital entity that balanced scientific rigor with conversational warmth, resulting in more authentic participant responses.
Main objectives
The project enhanced research data quality by designing a conversation system that felt refreshingly human - mapping out natural dialogue paths, adopting a casual tone that put participants at ease, building trust through personality before probing for insights, and deliberately subverting the sterile research environments that typically trigger performative responses.
Achieved results
By creating an interaction environment that more closely resembled everyday conversations, the system collected data that better reflected participants’ genuine perspectives rather than what they believed researchers wanted to hear.
Participant feedback confirmed that the approach significantly improved their experience compared to traditional research methods.
Main reflection
This experiment demonstrated that research quality depends as much on relationship dynamics as methodological rigor.
By deliberately designing a digital entity that had a sense of humor, the project collected data that more accurately reflected authentic perspectives.
The project proved that by making research interactions feel less like formal studies and more like natural conversations, we can access insights that remain hidden in more traditional approaches.