MP3, WAV, or M4A in. Timestamped transcript, speaker labels, AI insights, and theme tags out. With InsightsHub audio analysis, your qualitative team can turn hours of raw interview files into structured, searchable research in minutes.
Why recorded interviews and calls stay unanalyzed
InsightsHub Audio Analysis is built for one situation: you have the recordings and no time to relisten to them.
Say you ran 25 customer interviews, each 45 minutes long. That’s nearly 19 hours of audio. Someone has to transcribe it, someone has to find the quotes, and someone has to tag the themes. Most teams skim a few files and work from memory.
The rest sit in a shared drive, unsearchable and unused. Research, customer success, sales, and call center teams all have this pile.
Learn More: InsightsHub Audio Analysis help documentation
What is InsightsHub audio analysis?
Audio Analysis processes audio files you upload to an InsightsHub repository. It works on in-depth interviews, focus groups, customer calls, and meeting recordings.
Each file gets a timestamped transcript with speaker labels, an AI summary, AI-suggested insights, and theme and sentiment tags. The system detects the language automatically, so you aren’t limited to English.
It replaces the transcription vendor, the folder of MP3s, and the spreadsheet of hand-pasted quotes. Everything sits next to your other research. Here’s what you can upload:
- Formats: MP3, WAV, and M4A
- Length: at least 30 seconds, with no maximum duration currently
- Size: up to 500 MB per file
- Batch: up to 50 files per manual upload
- Sources: your device or a cloud connector such as Google Drive or SharePoint
For the launch details, read the launch announcement. This guide covers the day-to-day workflow.
How to analyze audio in InsightsHub, step by step
1. Upload your recordings
Open a repository and go to the folder where the audio should live. Click Import Files, or choose a cloud connector. Processing runs in the background. You get an in-app notification when transcription and AI analysis finish.
Open a file early, and a progress bar shows messages like “Analyzing content.” The Summary, Insights, and Tags tabs stay locked until processing ends.
2. Read the transcript
The File Analysis view puts the audio player on the left. The transcript shows detected speaker labels and clickable timestamps. Click one and playback jumps to that exact moment.
3. Skim the AI summary
The summary generates automatically. The recap covers the main topics and findings. The actions list includes takeaways and next steps drawn from participant dialogue. You can copy it for stakeholders and rate its accuracy to help refine future AI performance.
4. Pull out insights
Open the Insights tab and select Suggest Insights. The AI proposes significant moments and quotes. Each shows a timestamp, a quote segment, and a speaker. Accept or reject them one by one, or select several and commit them together. Accepted insights record their source (AI or User), commit date, and speaker.
The Tags tab shows AI-generated theme and sentiment tags, plus manual tags you add from the transcript menu. Tag counts show how often each one appears across your repository insights. Click a tag to see every related insight, quote, timestamp, and speaker.
6. Ask questions across recordings
Use QuestionPro AI Chat at the repository level. Ask in plain language and get source-backed responses about your audio.
A worked example: 25 interviews, one repository
A regional retailer has 25 loyalty-app interviews. Before, the team split the files, each person listened to a handful, and they argued the findings from memory. Now the team uploads all 25 in one batch, within the 50-file limit. Every call gets the same treatment: transcript, summary, suggested insights, and tags. The team runs suggested insights on each call and accepts the quotes about redeeming points.
The tags tab shows how often redemption comes up across the accepted insights. Clicking the tag lists every related quote with its timestamp and speaker. Then someone asks AI Chat which parts of the app confused participants. The answer points back to the source recordings.
The finding that reaches the readout is a real quote with a timestamp and a speaker attached. It isn’t a paraphrase from someone’s notes.
The advantages of InsightsHub audio analysis for research teams
Here’s what you gain once recordings live in the repository.
- Exact quotes, not paraphrases. Every suggested insight carries a timestamp, a quote segment, and a speaker.
- One click from transcript to audio. Any timestamp takes you to that moment in the recording.
- Human review built in. AI suggestions only join your project when you accept them.
- Themes you can count. Tag counts and tag filters work across your repository insights.
- Search and Q&A in one place. Transcripts sit beside your other research, and AI Chat answers from them with sources.
Running in-depth interviews, or feeding a voice of the customer program with sales and support calls? This is where those recordings finally become searchable.
When to use it, and when not to
Use it when you have recorded interviews, focus groups, or customer calls. You get transcripts, quotes, and themes in one repository.
Skip it for purely quantitative survey analysis. It works on files you upload, so it won’t translate a live stream. Files under 30 seconds, over 500 MB, or in formats other than MP3, WAV, and M4A aren’t supported. Very noisy audio gives weaker transcripts.
Get started with InsightsHub audio analysis
Your recordings already hold the evidence. Give them a transcript, a speaker, and a timestamp, and your team can find it.
Create a free account and upload your first recording.
Frequently asked questions
InsightsHub audio analysis turns uploaded audio into searchable research inside an InsightsHub repository. It transcribes recordings, detects speakers, writes an AI summary, suggests insights with timestamps, and applies theme and sentiment tags. It works on interviews, focus groups, customer calls, and meeting recordings.
It supports MP3, WAV, and M4A files. Each recording must be at least 30 seconds long and no larger than 500 MB. There is currently no maximum duration limit, and you can upload up to 50 files in a single manual batch.
Yes. InsightsHub automatically detects the audio language during transcription, so processing isn’t limited to English. Upload the recording the same way you would any other file. The transcript, summary, and AI insights then come out of the same automated processing.
Yes. InsightsHub automatically detects and distinguishes speakers in a recording. The transcript is organized by speaker, with clickable timestamps that jump to that moment in the audio. AI-suggested insights are attributed to the speaker who made the statement, so every quote traces back to its source.
A standalone tool gives you a text file. Audio analysis keeps the transcript inside your InsightsHub repository, next to your other research. Summaries, insights, tags, and AI Chat sit on top. Your recordings become searchable alongside past and present projects instead of sitting in a separate folder.
