Inspiration
YouTube creators often have hundreds of people telling them exactly what they want to watch next — inside the comments. But manually reading hundreds of comments and identifying patterns is slow and overwhelming.
That inspired CrowdMind.
What it does
CrowdMind turns real YouTube comments into actionable audience intelligence.
Paste a public YouTube video URL and CrowdMind collects the comments, analyzes audience signals using AI, and identifies recurring demands, questions, pain points, and content opportunities.
Instead of guessing what to create next, creators can use signals directly from their audience.
How we built it
CrowdMind is built as a web application using React, Vite and Tailwind CSS. It retrieves real public YouTube comments and uses Gemini AI to analyze them and transform noisy conversations into structured audience insights and content ideas.
Challenges we ran into
One major challenge was reliably analyzing hundreds of real comments while keeping AI responses structured and usable. Large comment sets could produce oversized or malformed responses, so the analysis pipeline was improved to handle larger inputs while keeping the final output concise.
Accomplishments that we're proud of
CrowdMind works with real YouTube videos and real audience comments rather than mock data. It can analyze hundreds of comments and turn them into useful signals for creators within seconds.
What we learned
We learned how to combine real-world API data with generative AI, handle large amounts of unstructured text, validate AI output, and build a usable end-to-end product.
What's next for CrowdMind
Next, CrowdMind could analyze comments across multiple videos, track audience demand over time, compare competing channels, and turn insights directly into video briefs and content strategies.
Built With
- gemini-api
- javascript
- react
- tailwind-css
- vercel
- vite
- youtube-data-api