/social-listening

name: social-listening
description: Use when you need to turn a supplied set of comments, DMs, reviews, community posts, or call notes into an evidence-backed picture of what people ask, resist, and repeat. Trigger phrases include "what are people saying about this?", "mine these comments", "what language should we use?", "find recurring objections", and "summarise this community feedback". Do not use this to scrape platforms, infer demographics, or write positioning from a handful of anecdotes; use agent-reach to collect public evidence first, audience-personas to group people, and positioning-audit to decide the message.

Social Listening

Turn evidence the operator already has into a usable demand map without pretending that a small sample represents the whole market.

1. Set the evidence boundary

Ask for the source material, where it came from, its date range, and the decision it should inform. Keep comments, DMs, reviews, support tickets, and interview notes labelled by source. If the user has only a claim about what people say, ask for the underlying text before analysing it.

2. Extract the signal without flattening it

For each item, capture the speaker's own wording, the situation they describe, the job they are trying to do, the obstacle, and any stated outcome. Keep a short supporting excerpt beside every finding so a reader can check it. Separate direct customer language from the operator's interpretation.

3. Cluster by decision-relevant theme

Group repeated evidence into questions, desired outcomes, objections, alternatives, proof requests, and vocabulary. Count only the supplied evidence. Mark a theme as isolated when it appears once, recurring when it appears across independent items, and unresolved when the context is too thin to tell.

4. Produce a demand map

Return a compact table with: theme, evidence count, representative wording, likely stage of the journey, confidence, and the next action. Next actions can be a research question, an FAQ update, an input for audience-personas, or a test for positioning-audit. Call out contradictions instead of averaging them away.

Hard rules

• Do not infer age, location, income, intent, or sentiment beyond what the evidence says.
• Never present supplied comments as a representative market sample without a sampling basis.
• Preserve anonymisation: do not expose names, handles, private messages, or customer details unnecessarily.
• Do not manufacture quotes or improve a speaker's wording inside quotation marks.
• Treat volume as a clue, not proof of importance; a repeated complaint from one thread is not independent corroboration.

Failure modes

| Failure | Do this instead | | --- | --- | | A loud minority becomes "the audience" | State the sample and test the theme with a wider, independently collected set. | | Themes mix people at different stages | Split the cluster by situation or journey stage before recommending an action. | | The result is a pile of quotes | Convert each cluster into a decision, uncertainty, and next move. | | The user wants public-platform research | Use agent-reach to gather allowed public sources, then return here to analyse them. |

Where it sits

Use agent-reach before this skill when evidence must be collected. Use audience-personas after this skill to turn recurring patterns into grounded audience groups. Use positioning-audit after that when those groups need a message and social-proof-mining when the evidence should become approved proof.