name: pm-feature-intel
description: Go beyond sentiment - get specific feature recommendations with quantified demand and competitive context
metadata: {"pmkit":{"emoji":"🔬","category":"feature-intelligence","schedule":"0 9 * * 1"}}

Feature Intelligence

Go beyond sentiment. Get specific feature recommendations with quantified demand, competitive context, and internal alignment signals.

Overview

Cluster customer feedback into actionable themes with representative quotes, impact assessment, and product implications.

Tools

generate_feature_intelligence

Analyze all feedback sources and generate clustered themes.

Input:

{
  "lookbackDays": 30,
  "includeSources": ["support", "gong", "community", "nps"]
}

Output: Markdown report with:
- Executive summary (top 3-5 themes with impact assessment)
- Theme analysis (for each theme):
- Theme name and description
- Number of mentions and sources
- Representative quotes (3-5)
- Affected customer segments
- Product implications
- Trend analysis (what's changing vs. last period)
- Recommendations (prioritized actions based on themes)

get_support_feedback

Fetch support ticket themes and feedback.

Input:

{
  "sinceDate": "2026-01-01",
  "groupBy": "theme"
}

get_gong_insights

Fetch aggregated insights from sales calls.

Input:

{
  "sinceDate": "2026-01-01",
  "insightTypes": ["pain_points", "feature_requests", "competitors"]
}

get_community_feedback

Fetch community forum posts and feature requests.

Input:

{
  "sinceDate": "2026-01-01",
  "minVotes": 5
}

get_nps_verbatims

Fetch NPS survey responses and verbatim feedback.

Input:

{
  "sinceDate": "2026-01-01",
  "scoreRange": [0, 10]
}

Schedule

Default: Weekly on Monday at 9:00 AM (0 9 * * 1)

Output

Markdown file saved to: pmkit/feature-intel/{timestamp}/report.md

SIEM telemetry saved to: pmkit/feature-intel/{timestamp}/telemetry.json