AI user research for automotive
From browsing to test drive to order, AI interviews find the step where buyers drop off. You also hear how owners really feel after each OTA update.
Common challenges in automotive user research
The long path from browsing to test drive to order hides where and why prospects drop off
Owners live all over the country, so in-person interviews are hard to schedule and slow to run
In-car software gets frequent OTA updates, and traditional research can't keep up with the release cycle
Dealer feedback is passed along secondhand, so the brand rarely hears customers' own words
What automotive teams research with heari
Why prospects don't place an order
Where buyers stall after browsing, the test drive, and the quote. Interview prospects who didn't order to find what made them hesitate or switch to a competitor.
Test drive and dealership experience
How the visit felt, from greeting and test route to price negotiation. Pinpoint the moments that win customers over or turn them away.
Concept tests for new models and trims
Which features buyers value and will pay for. Show new models and trim packages to target customers and compare the trade-offs each group makes.
Owner driving and infotainment feedback
Everyday driving and life after each OTA update. Hear which features owners use or ignore, and what got better or worse after an update.
After-sales service and repair experience
Booking, check-in, repair, or pickup: which step frustrates owners. Start from their last service visit and find specific steps to fix.
Charging and refueling experience
What EV owners experience at the charger. Learn their charging habits, pain points around finding stations and waiting in line, and how charging affects repeat purchases.
Automotive research example
A typical study you can run right away. The research assistant adapts the plan and interview guide to your business.
Study plan
Sample interview guide
The AI interviewer follows the guide and asks follow-up questionsWhat they need a car for
Core questionWho will mainly drive this car, and for what?
Follow-upHousehold size and where they usually go
The test drive
Core questionWhat moment during the test drive gave you pause?
Follow-upSpecific road conditions or seating comfort
Alternatives
Core questionWhich other cars are you looking at?
Follow-upWhat draws them to the other option
What would close the deal
Core questionWhat would get you to place an order?
Follow-upPrice, features, or service
Data shows what owners did. heari finds out why.
Connect ThinkingAI Agentic Engine to select customers by test-drive and driving behavior. Bring that context into interviews, and write findings back as customer tags.
What the behavior data shows
After the OTA update, voice assistant usage dropped ~70%, and drivers switched to phone mirroring for navigation.
What the heari interview found
"Since the update, voice keeps getting addresses wrong. Fixing it while I'm driving is too dangerous, so I just use my phone."
What the behavior data shows
Visited the dealership twice in the 14 days after the test drive without ordering.
What the heari interview found
"Once the car seat's in, nobody else fits in the back. I'm holding off to see if there's a seven-seater."
Data security and compliance in automotive
No vehicle data collected
Owners' personal data and vehicle data stay out of interviews.
Separate permissions
Brand and dealer data permissions are kept strictly separate.
Never while driving
heari never starts an interview while an owner is driving.
Your data stays yours
Interview data is used only for your study, never to train AI models.
Test drive but no order? Ask your prospects
Bring a list of prospects. We'll help you run a study in heari to see what else they're considering and what's holding them back.
