mcpField
C
conversion-diagnostic-kit

conversion-diagnostic-kit

github.com/gtmagentsMarketing & growth42875 installsUpdated 30w ago
Repository

About conversion-diagnostic-kit

conversion-diagnostic-kit is a skill for diagnosing conversion and checkout problems and turning findings into prioritized actions. It combines analytics signals, customer feedback, segmentation, and impact-based scoring for teams preparing experiments or remediation plans.

Key features

  1. 01Combines analytics and customer feedback
  2. 02Segments issues by audience and context
  3. 03Classifies UX, merchandising, and technical issues
  4. 04Prioritizes by impact, confidence, effort, and risk
  5. 05Provides diagnostic and experiment templates

Use cases

  1. 01Investigate a sudden checkout completion decline
  2. 02Create experiments from funnel pain points
  3. 03Coordinate remediation across engineering, UX, and marketing

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/gtmagents/gtm-agents --skill conversion-diagnostic-kit

After installing, type/conversion-diagnostic-kitin Claude Code to confirm it loaded.

Details

From the project README

Conversion Diagnostic Kit Skill

When to Use

  • Sudden drops in conversion, AOV, or checkout completion.
  • Preparing experiment backlogs tied to funnel pain points.
  • Aligning engineering, UX, and marketing on remediation priorities.

Framework

  1. Signal Stack – analytics, heatmaps, session replay, VOC, performance metrics.
  2. Segmentation Grid – device, channel, geography, campaign, customer type.
  3. Issue Taxonomy – UX friction, merchandising mismatch, technical/performance, policy/payment.
  4. Prioritization Model – score by impact, confidence, effort, and guardrail risk.
  5. Action Tracker – link issues to owners, experiments, or engineering tickets.

Templates

  • Conversion diagnostic workbook (data inputs, findings, recommended tests).
  • Standup agenda for cross-functional conversion war rooms.
  • Experiment brief template with hypothesis, KPIs, guardrails.

Tips

  • Pair quant data with VOC clips for stakeholder alignment.
  • Keep diagnostics lightweight (48-hour turnaround) for high-velocity campaigns.
  • Use alongside diagnose-conversion-drop command for automated reporting.

Comments

Markdown supported