gh-gtmagents-gtm-agents-plugins-customer-feedback-orchestration/commands/synthesize-feedback.md

name, description, usage

name	description	usage
synthesize-feedback	Consolidates quantitative and qualitative signals into prioritized themes with opportunity sizing.	/customer-feedback-orchestration:synthesize-feedback --window 60d --personas "admins,execs" --detail workshop

Command: synthesize-feedback

Inputs

• window – analysis horizon (30d, 60d, quarter) pulling data from surveys, support, usage, community.
• personas – optional filter for personas or segments to highlight.
• detail – summary | workshop controls depth of deliverables.
• include-voice – true/false to embed verbatim quotes.
• impact-lens – arr | adoption | satisfaction to drive prioritization lens.

GTM Agents Pattern & Plan Checklist

Mirrors GTM Agents orchestrator blueprint @puerto/plugins/orchestrator/README.md#112-325.

• Pattern selection: Feedback synthesis typically runs pipeline (aggregation → tagging → impact modeling → opportunity framing → narrative). If tagging + modeling can run in parallel, record a diamond block with merge gate in the plan header.
• Plan schema: Save .claude/plans/plan-<timestamp>.json capturing window, data feeds, dependency graph (CS, product, research, analytics), error handling, and success metrics (theme confidence, coverage %, time-to-synthesize).
• Tool hooks: Reference docs/gtm-essentials.md stack—Serena for taxonomy updates, Context7 for historic studies, Sequential Thinking for workshop prep, Playwright for dashboard QA when embedding outputs.
• Guardrails: Default retry limit = 2 for data pulls/tagging jobs; escalation ladder = Research Lead → CX Leadership → Exec sponsor.
• Review: Run docs/usage-guide.md#orchestration-best-practices-puerto-parity before workshops to confirm dependencies + deliverables.

Workflow

1. Data Aggregation – collect structured/unstructured feedback from connected systems.
2. Tagging & Clustering – apply taxonomy, detect emerging topics, score severity + frequency.
3. Impact Modeling – quantify ARR, usage, or sentiment impact with supporting metrics.
4. Opportunity Framing – craft problem statements, desired outcomes, and proposed motions.
5. Narrative Packaging – produce decks/notes for PM, CS, marketing, and exec consumption.

Outputs

• Theme matrix with impact, personas, confidence, and owner recommendations.
• Quote bank + evidence appendix tied to each theme.
• Action backlog seeds for route-insights command.
• Plan JSON entry stored/updated in .claude/plans for audit trail.

Agent/Skill Invocations

• cs-analyst – leads data prep + scoring.
• research-lead – ensures insights align with study goals.
• insight-synthesis skill – provides framing templates and storytelling patterns.
• survey-design skill – highlights methodology caveats.

GTM Agents Safeguards

• Fallback agents: document substitutes (e.g., CS Analyst covering Research Lead) when leads unavailable.
• Escalation triggers: if data completeness or confidence metrics miss thresholds twice, escalate via GTM Agents rip-cord and log remediation in plan JSON.
• Plan maintenance: update plan JSON/change log when data sources, personas, or impact lenses change to preserve audit history.

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