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Generalgtmagents

member-insights

Use to analyze loyalty member behavior, segmentation, and experiment

Stars
259
Source
gtmagents/gtm-agents
Updated
2026-04-03
Slug
gtmagents--gtm-agents--member-insights
View on GitHubRaw SKILL.md

// install — copy + paste into any project

mkdir -p .claude/skills && curl -fsSL https://raw.githubusercontent.com/gtmagents/gtm-agents/HEAD/plugins/loyalty-lifecycle-orchestration/skills/member-insights/SKILL.md -o .claude/skills/member-insights.md

Drops the SKILL.md into .claude/skills/member-insights.md. Works with Claude Code, Cursor, and any agent that loads SKILL.md files from .claude/skills/.

Member Insights Skill

When to Use

  • Monitoring program health across tiers or regions.
  • Designing personalization campaigns based on loyalty data.
  • Reporting experiment outcomes to stakeholders.

Framework

  1. Data Sources – transaction systems, product telemetry, MAP/CRM, support, survey tools.
  2. Segmentation – tier, lifecycle stage, engagement score, risk/comeback cohorts.
  3. Metrics – enrollment funnel, active members, point velocity, redemption, incremental revenue.
  4. Experimentation – define guardrail metrics, success criteria, and monitoring cadence.
  5. Insight Distribution – dashboards, alerts, and story-driven memos for GTM teams.

Templates

  • KPI scorecard (metric → target → actual → variance → owner).
  • Segment heatmap (cohort → engagement → action recommendation).
  • Experiment readout template (hypothesis, lift, guardrails, next steps).

Tips

  • Blend quantitative metrics with VOC snippets for context.
  • Tag insights with urgency so ops/marketing can prioritize quickly.
  • Pair with monitor-loyalty command to ensure consistent reporting structure.