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sentiment-analysis skill

/plugins/community-orchestration/skills/sentiment-analysis

This skill analyzes community feedback to identify sentiment, trends, and risks, enabling prioritized actions and executive updates.

npx playbooks add skill gtmagents/gtm-agents --skill sentiment-analysis

Review the files below or copy the command above to add this skill to your agents.

Files (1)
SKILL.md
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---
name: sentiment-analysis
description: Use to interpret qualitative feedback, trends, and risks across community
  channels.
---

# Community Sentiment Analysis Skill

## When to Use
- Monitoring community tone during launches, incidents, or roadmap changes.
- Preparing executive updates that require member sentiment context.
- Prioritizing response or enablement efforts based on emerging themes.

## Framework
1. **Signal Sources** – forums, chat transcripts, surveys, social listening, support tickets.
2. **Tagging Schema** – categorize by emotion, topic, product area, persona, and severity.
3. **Trend Analysis** – track frequency over time, correlate with launches or incidents.
4. **Risk Scoring** – define thresholds for escalation (negative volume, influencer involvement, compliance).
5. **Action Loop** – translate findings into comms responses, content updates, or product feedback tasks.

## Templates
- Sentiment tagging sheet (message → tags → severity → owner).
- Trend report layout with charts + narrative.
- Escalation matrix referencing response SLAs.

## Tips
- Combine manual review with NLP dashboards to balance accuracy + scale.
- Capture representative quotes for exec storytelling.
- Pair with `measure-engagement` command to provide recommendations alongside metrics.

---

Overview

This skill interprets qualitative feedback, trends, and risks across community channels to surface actionable insights for GTM teams. I built it to combine tag-based analysis, trend detection, and risk scoring so teams can act quickly on member sentiment. It supports executive summaries, escalation, and prioritization of responses.

How this skill works

The skill ingests signals from forums, chat transcripts, surveys, social listening, and support tickets and applies a consistent tagging schema for emotion, topic, product area, persona, and severity. It computes trend lines and risk scores, flags influencer involvement or policy risk, and generates templated reports and escalation recommendations. Outputs include a sentiment-tagged dataset, visual trend summaries, and owner-assigned action items.

When to use it

  • Monitor community tone during product launches, incidents, or roadmap announcements.
  • Prepare executive updates that require representative member sentiment and trends.
  • Prioritize support, enablement, or product fixes based on emerging negative themes.
  • Escalate potential compliance or reputation risks driven by high-severity feedback.
  • Validate the effect of communications or product changes on member sentiment.

Best practices

  • Combine automated NLP tagging with periodic manual review to maintain accuracy and reduce drift.
  • Use a standardized tagging schema (emotion, topic, persona, severity) across channels for consistent analysis.
  • Define clear risk thresholds and SLAs for escalation (negative volume, influencer signals, compliance flags).
  • Capture representative quotes to humanize reports for executives and stakeholders.
  • Correlate sentiment trends with launches, incidents, or marketing activities to identify root causes.

Example use cases

  • Daily monitoring dashboard during a major product launch to detect early negative trends and assign owners.
  • Weekly executive sentiment brief with top themes, severity, and recommended comms actions.
  • Triage workflow after a support incident: identify affected personas, prioritize fixes, and draft customer messages.
  • Social listening follow-up to detect influencer-driven spikes and recommend outreach or public responses.
  • Product planning input: surface recurring negative themes tied to a feature for backlog prioritization.

FAQ

What sources should I feed into the skill?

Include forums, chat transcripts, survey responses, social listening streams, and support tickets for a holistic view.

How do you handle tagging accuracy?

I recommend hybrid validation: automated NLP for scale plus regular human audits and schema updates to prevent drift.

When should sentiment trigger escalation?

Escalate when negative volume crosses a predefined threshold, influencers are involved, or messages indicate compliance/reputation risk.