AI user research for consumer electronics
Validate selling points before launch. After launch, find out why people skip a feature or leave a bad review, with quote-backed findings in hours.
Common challenges in consumer electronics user research
Products ship fast, and there's no time for weeks of traditional interviews before launch
As features pile up, data alone can't tell you why people skip a particular one
Product reviews and comments are mostly venting, rarely explaining what actually went wrong
Users are spread across countries and regions, making multilingual interviews expensive
What consumer electronics teams research with heari
Concept and messaging tests for new products
Check that your selling points land with target users before launch. Show different versions of the copy and follow up on real use cases and what people care about.
Unboxing and first-use experience
Walk through day one, from unboxing and pairing to first use. Find where new users get confused or stuck.
Feature usage and abandonment
Find out why people skip a feature and what would make them use it. Follow up on specifics: did they miss it, find it awkward, or just not need it?
Companion app experience
See what gets in the way during pairing, everyday adjustments, and firmware updates. Find where people most often give up or ask for help in the companion app.
Reasons for returns and bad reviews
Get the full story behind vague one-star reviews. Interview people who returned the product or left a low rating, and trace each issue to the hardware, product listing, or support.
Support, warranty, and repair experience
Uncover what frustrates people about repairs, replacements, and support. Walk through their last service interaction to find the moments that hurt word of mouth most.
Consumer electronics 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 questionsUsage habits
Core questionWhen do you usually wear headphones?
Follow-upMost recent use
First reaction
Core questionLooking at these two selling points, which one do you notice first?
Follow-upWhy that one
Real needs
Core questionNoise cancellation or comfort: which matters more to you?
Follow-upA specific experience
Buying decision
Core questionWhat would make you buy new headphones?
Follow-upBudget and timing
Behavior data shows what users did. heari finds out why.
Connect ThinkingAI Agentic Engine to target participants by device usage. Pull behavior data into interviews and sync findings back as user tags.
What the behavior data shows
Used noise cancelling for only 12 minutes total in the 30 days after activation, under 2 minutes each time.
What the heari interview found
"Noise cancelling makes my ears feel kind of stuffy, and it gets uncomfortable after a while, so I only turn it on for a bit on the subway."
What the behavior data shows
Saw the firmware update prompt 5 times and never installed it.
What the heari interview found
"Last time I updated, I had to pair it all over again. Such a pain. Now when it pops up I just close it."
Confidentiality and compliance in consumer electronics
Unreleased product confidentiality
Participants can sign NDAs, and interview guides leave out unreleased details.
Cross-border data
Data from cross-border interviews is transferred according to your compliance requirements.
Anonymous by default
Insight reports cite participants by ID only.
Your data stays yours
Interview data is used only for your study, never to train AI models.
Test your selling points with target users before launch
Bring a new product concept or an unused feature, and we'll run user interviews with you in heari.
