Deepa

AudioForms - AI-Powered Voice Surveys

Boost engagement with voice surveys and audio forms. Easily add audio to survey forms, capture voice-of-customer (VOC) feedback, gather deeper insights. Ideal for product managers, marketers, researchers, and support teams seeking powerful user research tools.

Add a comment

Replies

Best
Deepa

Hey! I’m Deepa, a UX Researcher / Designer and a Product Builder. In my past life as a UX researcher, I've spent too many hours spent transcribing user interviews and sorting through messy notes, so I decided to build something to make my job easier.

It’s called AudioForms — a simple way to collect voice responses instead of written ones. Great for getting quick and async feedback without needing to schedule calls or do full interviews.

Why voice surveys?
- People talk more naturally than they write
- You still get tone, context, emotion
- Responses are auto-transcribed and come with sentiment analysis — so you know not just what they said, but how they felt about it.

It’s been super useful for async interviews, idea validation, and feedback collection — perfect for UX Researchers, Product Managers, Marketing and CS teams or anyone looking to get voice-of-customer feedback.

Here’s a quick demo 👇
https://youtu.be/uBgnynVcTFU

Samantha Spiro

Awesome stuff! I conduct so many interviews – this will be a game-changer.

Yifan Wang

I've been looking long for the product for ux design, so lucky to discover the voice survey tool. Will defintely use this in the upcoming research!

Shreyans Bhansali

This is such a smart shift—voice captures nuance text just can’t. How are you handling background noise or accents in transcription? That can make or break insights in real-world usage.

Deepa

@shreyans_assistiv Hey Shreyans - Thanks so much! Totally agree with you, voice captures so much nuance that text sometimes just misses. Right now, the API that we are using does a great job handling background noise and different accents- so that takes a big chunk of the heavy lifting off our plate. In the future, there is a plan to add a feature where users can flag any parts of the transcription that seems off or inconsistent - that will help us in improving and spotting patterns over time.

Thanks for bringing that up - always curious how others are thinking about this too. Let me know if you have more questions.