LEAD GENERATION // FREE LIVE DEMO
Social Listening Agent
Brand mentions scatter across Instagram comments, tagged posts and DMs faster than anyone can manually track, so a brewing complaint or a viral compliment both go unnoticed.
WHAT IS SOCIAL LISTENING AGENT?
An AI social listening agent reads a batch of recent brand mentions and returns a positive-vs-negative sentiment breakdown, a metrics grid, a table of the specific mentions worth a direct response, and one trend worth acting on before it repeats — coverage a founder scrolling Instagram manually can't sustain past a handful of posts.
HOW IT WORKS
The agent scores every mention individually for sentiment and priority rather than eyeballing a general vibe, because the mentions that matter most are usually the extremes — a specific complaint that could become a pattern, or a strong compliment worth amplifying — not the median mention. It's prompted to separate 'worth amplifying' from 'needs a response' explicitly, since treating both the same way either buries a real complaint under noise or wastes a response on a mention that needed none.
The trend-flagging step is the highest-leverage part: three separate complaints about the same cancelled class, individually, look like isolated incidents — clustered together by the agent, they're a pattern worth fixing before the fourth complaint becomes a public thread.
You are a social listening analyst for a Dubai-based growth agency. Given a brand name and a batch of recent mentions, produce: a positive-vs-negative mention chart, a metrics grid, a table of the top mentions worth a response, and identify one trend worth acting on. Output ONLY a JSON array of typed blocks matching the OutputBlock union — no prose outside the JSON.USE CASES
Weekly brand health check
Run the week's mentions through the agent every Monday instead of scrolling comments hoping to catch a pattern by memory.
Crisis-catching before it escalates
Cluster three quiet complaints about the same issue into one flagged trend before they become a single loud public post.
Community management prioritisation
Hand a community manager a ranked 'respond to these six' list instead of an unsorted feed of sixty mentions.
Campaign reaction tracking
After a launch or campaign, measure the real sentiment split instead of relying on like counts alone.
RESULTS & BENCHMARKS
Mention triage time
projected (modeled)
Coverage vs. manual spot-checking
projected (modeled)
LIVE DEMO
Try it right now
FAQ
Common questions
What makes a mention 'worth a response' versus just noise?
The agent scores sentiment and priority per mention, separating specific, actionable complaints (worth a direct response) from general positive chatter (worth amplifying, not replying to individually).
Can it catch a brewing problem before it goes viral?
That's the trend-flagging step's specific job — clustering several individually-quiet complaints about the same issue into one flagged pattern before it becomes a single loud public post.
Does the demo monitor my real social accounts?
No — the live demo works from mentions you paste or summarise. A production version would connect to real platform APIs, but nothing here requires account access.
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Built by Hammad Yousuf — AI Marketing Automation Engineer, 540K+ YouTube subscribers.
See the production missions these agent patterns run in, or hire the whole system.