Building a voice-based ordering experience that's safe to use while driving
A discovery and evaluative research project to define user requirements and test a new conversational UI for Telenav's In-Car Commerce OEM product.
RoleLead UX Researcher
MethodsInterviews · Surveys · Wizard of Oz · Personas
Timeline2020
PlatformIn-car voice UI (OEM)
The problem
How do you build a voice ordering system that's safe, intuitive, and usable while driving?
The outcome
Insights informed design changes and established a new approved remote testing protocol for voice products at Telenav.
6usability sessions
3key insights
✓protocol approved
Background
Voice ordering in the car is a hard problem.
Telenav was building a voice-based ordering system for OEM clients — letting drivers order food, coffee, and parking without looking away from the road. The challenge was designing an experience that was safe and low cognitive load, while COVID made in-person testing impossible.
Research question
How can we build a voice-based ordering system that is safe and easy to use while driving?
Research approach
Discovery first, then evaluation
Two phases: understand who the users are and what they need, then test early designs for safety and usability.
01
User interviews & persona creation
Interviewed OEM drivers who frequently order while driving. Synthesized findings into personas to guide design direction.
02
Literature review
Reviewed research on voice testing, cognitive load, and conversational UI to build a heuristics framework for evaluation.
03
Survey (N=100)
Captured voice assistant usage patterns and collected natural language phrase samples to train the voice engine on command variants.
04
Remote Wizard of Oz usability testing
Designed and ran a new remote WoZ protocol using Zoom and Adobe XD. 6 sessions with real users testing voice ordering tasks and conversation flows.
Testing protocol
A new way to test voice remotely
With in-person testing off the table, I designed a remote Wizard of Oz protocol that let us simulate a voice experience over Zoom. The researcher controls the prototype responses in real time while the participant speaks naturally, creating the illusion of a live voice system.
Participant
Speaks naturally via Zoom
Screen share
Prototype visible to participant
Researcher keyboard
Controls prototype responses in real time
Adobe XD prototype
Simulates live voice responses
Tool
Zoom for remote session, screen sharing, and recording
Prototype
Adobe XD conversational flow, keyboard-controlled by researcher
Sessions
6 remote sessions with real OEM users
Outcome
Protocol approved for future voice testing at Telenav
Key insights
Three usability problems emerged consistently
Due to NDA restrictions, specifics are redacted. These are high-level findings.
Insight 01
Users forget what they ordered
A voice-only order summary increases cognitive load. Users need a quick visual reference to recall items without being distracted from the road.
Insight 02
Visual system status cues don't work while driving
Users can't look at the screen to know when the system is listening. Without clear audio cues, they talk over the system or miss their window to speak.
Insight 03
Unfamiliar menus make voice ordering unusable
A heavily voice-driven UI assumes users know the menu. For infrequent customers, not knowing item names makes the system impossible to use without visual support.
Impact
Research informed design and unlocked a new testing approach
New protocol
Remote Wizard of Oz testing approved
The remote testing protocol developed for this study was formally approved, enabling lean iterative voice testing for future conversational flow work.
Design changes
Findings directly informed the next design sprint
Insights on cognitive load, audio cues, and menu familiarity shaped changes to the conversation flow and visual display strategy.
A note
I left Telenav before the product reached full build-out. The work captured here reflects the research phase and its direct outputs. Future planned work included driving usability testing and distraction and cognitive load assessment using NHTSA recommended methods.
