Use Case • Research & insights
Research & Insights: Treat Transcripts as a Corpus
When you’re studying an industry, brand, or creator, video conversations hold fresh signals. Pull transcripts at scale, keep them structured, and run clustering, sentiment, or trend models on top.
Consulting & research Market intelligence Enterprise insights
Challenges teams mention
- • Downloading captions one-by-one doesn’t scale to dozens of videos.
- • No consistent format makes it hard to feed BI or NLP pipelines.
- • You need recurring refreshes but lack an automated way to collect data.
How this playbook helps
- • Ingest by channel, playlist, or individual link so coverage stays complete.
- • Export TXT / CSV with video IDs, timestamps, and metadata intact.
- • Hook into APIs / webhooks (coming soon) to schedule pulls and analyses.
Analysis Flow
Four steps from collection to insight
- Compile the watchlist (channels, playlists, or single URLs).
- Batch-fetch transcripts and log metadata like title, publish date, and language.
- Push the text into your warehouse or scripts for topic / sentiment / keyword modeling.
- Sync insights back to BI dashboards, weekly reads, or client deliverables.
Feature highlights
- • Clean plain-text output ready for any NLP stack.
- • Timestamps for slicing clips or training audio models.
- • Planned API and batch modes to automate recurring crawls.
Build your transcript data pipe
Start with one video, then scale to channel-wide trend tracking.