Member Insights

Use to analyze loyalty member behavior, segmentation, and experiment results.

Published by @gtmagents·from gtmagents/gtm-agents·0 agent reads / 30d·0 saves·Updated June 14, 2026

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

Data Sources – transaction systems, product telemetry, MAP/CRM, support, survey tools.
Segmentation – tier, lifecycle stage, engagement score, risk/comeback cohorts.
Metrics – enrollment funnel, active members, point velocity, redemption, incremental revenue.
Experimentation – define guardrail metrics, success criteria, and monitoring cadence.
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.

More on the bench

Email Sequence

When the user wants to create or optimize an email sequence, drip campaign, automated email flow, or lifecycle email program. Also use when the user mentions "email sequence," "drip campaign," "nurture sequence," "onboarding emails," "welcome sequence," "re-engagement emails," "email automation," or "lifecycle emails." For in-app onboarding, see onboarding-cro.

Alireza Rezvani

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Launch Brand Kit

Packages updated brand guidelines, assets, and enablement resources for GTM teams.

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Registration Ops

Use when configuring registration flows, reminders, and data sync for webinars.

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Sharebench · Public bench

Connect via MCP.

Add the public bench to any AI tool. Your agents read every artifact you see — no signup needed.

1Pick your tool

# Add the public bench as an MCP server
claude mcp add --transport http sharebench-public https://mcp-public.sharebench.ai

# Settings → MCP → Add new MCP server
{
  "mcpServers": {
    "sharebench-public": {
      "url": "https://mcp-public.sharebench.ai"
    }
  }
}

# Custom GPT or Developer Mode
# Add a remote MCP connector with this URL:
https://mcp-public.sharebench.ai

# Append to ~/.codex/config.toml
[mcp_servers.sharebench_public]
url = "https://mcp-public.sharebench.ai"

2Ask your agent for an artifact

Once connected, just ask in plain language — your agent searches the bench and pulls in what it needs.“Pull the brand voice from sharebench and rewrite this draft.”