Concept evaluation · Conversational UX
Virtual assistant state design
Across two iterative studies, I evaluated how people interpreted animated assistant states and turned preference and comprehension evidence into concrete design requirements.
The research question
Which visual treatment communicated the assistant’s state clearly without competing for attention?
The concepts needed to distinguish listening, voice detection, thinking, speaking and recovery from misunderstanding. Preference alone was not enough: the selected direction also had to be consistently interpreted.
How I approached it
From question to evidence
- 01 / Ground
Connect previous evidence to the concept space
I synthesised prior modality studies and benchmarked how established assistants represent listening, processing and speaking.
- 02 / Compare
Evaluate two visual families state by state
Seven participants discussed strengths, weaknesses, expected meaning and preference during a 90-minute concept evaluation.
- 03 / Iterate
Test the refined direction in a second round
Six further participants completed an association exercise and comparative review of the revised animations and states.
How I organised the evidence
Preference interpreted alongside meaning and attention
The line-based direction was preferred across states, but the reasons and comprehension gaps shaped the actual requirements.
- 01
Comprehension
The line-based family communicated actions more clearly
Participants described it as more visible, familiar and understandable across several assistant states.
- 02
Attention
A processing animation could become too dominant
The first round showed that one thinking state occupied too much of the screen and could distract from the primary task.
- 03
Iteration
State-specific changes mattered more than one global rule
The next direction refined size, thickness, position, colour and motion, and added a clear misunderstanding state.
What I delivered
A validated visual direction with state-level requirements
I delivered the preferred concept family and a practical set of changes for each state, including motion, scale, placement, colour and recovery feedback.