LEAD GENERATION // FREE LIVE DEMO
Social Listening Agent
THE PROBLEM
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.
~1h/day → ~2 min
Mention triage time
Part of the Reputation Squad →
No pitch — just a plan.
Give me your brand and this week's mentions — I'll score every one, flag the six that need a reply, and catch the trend before it goes public.
Execution trace — recorded run (this agent's real pipeline)
Reading the mention batch
ok
Scoring sentiment per mention
ok
Ranking mentions worth a response
ok
Flagging the trend worth acting on
ok
Mention triage time
~1h/day → ~2 min
projected
Coverage vs. manual spot-checking
every mention scored, not sampled
projected
Positive vs. negative mentions, last 3 weeks
| "Best trainers in the Marina, hands down" | Positive | Low — amplify |
| "Third class cancelled this month, no notice" | Negative | High — respond |
| "Loved the new HIIT class format" | Positive | Low — amplify |
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. Every mention referenced must come from the batch actually supplied — never invent a comment, a commenter, or a complaint that isn't in the input; if the batch is too thin to support a confident trend, say so instead of manufacturing one.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)
GET THIS RUNNING ON YOUR BUSINESS
Want Social Listening Agent solving this for you?
This runs in production today, not a mockup. Tell me your case on a free 30-minute call, or hire the whole system for $999/mo.
No pitch — just a plan.
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.
RELATED AGENTS
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.