CrowdListen aggregates comments and discussions from major social platforms—including TikTok, YouTube, Instagram, Reddit, X/Twitter, Hacker News, Discord, and Slack—and uses AI to rank them by engagement signals such as likes, upvotes, and replies. The weighted comments are automatically clustered into thematic groups, delivering structured audience sentiment that can be accessed via free instant analyzers or integrated through API and AI‑agent workflows. This enables product, marketing, and research teams to monitor public opinion and feed actionable insights into their decision‑making pipelines.
Funding
Funding not disclosed
Founders
Product
Problem
Customer feedback is scattered across numerous social media, forum, and community platforms, making it difficult for teams to capture the full context of audience opinions. Without a unified view, insights become fragmented, handoffs lose detail, and translating feedback into actionable decisions is inefficient.
Solution
CrowdListen aggregates comments, threads, and discussions from over eight major platforms—including TikTok, YouTube, Instagram, Reddit, X/Twitter, Hacker News, Discord, and Slack—into a single analysis pipeline. Its AI engine extracts the full text of posts and associated comments, then ranks each comment by engagement signals such as likes, upvotes, and replies. By weighting higher‑engagement comments more heavily, the system surfaces the consensus view of the audience. The ranked comments are clustered into coherent themes, producing structured insights that can be consumed directly or fed into downstream workflows. Users can access these insights through free instant analyzers or through paid workspaces that support ongoing monitoring, API access, and integration with AI agents via the Model Context Protocol (MCP).
Target Audience
Primary customers are product, marketing, and research teams that need to monitor public sentiment across social channels, as well as developers building AI agents that require automated audience intelligence.
Features
- Cross‑platform data collection covering TikTok, YouTube, Instagram, Reddit, X/Twitter, Hacker News, Discord, and Slack
- AI‑driven extraction of transcripts and comments with engagement‑weighted ranking (likes, upvotes, replies)
- Automatic clustering of comments into thematic groups to reveal audience consensus
- Free instant analyzer tools for any URL, providing transcript, ranked comments, and theme summaries without login
- Workspace environment with multi‑analysis limits, API access, and support for AI agent integration (MCP Harness)
- Customizable search depth and context retention for deep dive investigations
- Exportable insights and API endpoints for integration with internal dashboards or research pipelines