Customer Insights

Use when consolidating product usage, health, and sentiment signals for lifecycle programs.

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

Customer Insights & Telemetry Skill

When to Use

Building segment-specific lifecycle journeys.
Prioritizing accounts for adoption help, expansion offers, or advocacy invites.
Diagnosing churn/retention risks and surfacing insights to CS + product.

Framework

Signals Stack – product usage, engagement, sentiment, commercial, health composite.
Data Plumbing – define sources (warehouse, product analytics, CS tools) and refresh cadence.
Normalization – align account/user IDs, tag personas/verticals.
Insight Delivery – dashboards + alerts to lifecycle, CS, product teams.
Closed Loop – track outcomes (expansion booked, churn prevented, advocacy activated).

Templates

Health score schema (dimensions, weight, threshold, owner).
Insight brief (observation, impact, recommended play, owner, due date).
Data dictionary for lifecycle dashboards.

Tips

Keep manual notes from CSMs in sync with telemetry to avoid blind spots.
Tag signals by persona/vertical for more precise plays.
Automate distribution via Slack/email alerts tied to triggers.

More on the bench

Vendor Management

Evaluate, compare, and manage vendor relationships. Trigger with "evaluate this vendor", "compare vendors", "vendor review", "should we renew", "RFP", or when the user is making procurement or vendor decisions.

sales-gtm-revops+1

Qbr Builder

Create Quarterly Business Reviews with account health scores, usage analytics, ROI analysis, expansion opportunities, and risk mitigation

customer-success+1

Escalation

Structure and package support escalations for engineering, product, or leadership with full context, reproduction steps, and business impact. Use when an issue needs to go beyond support, when writing an escalation brief, or when assessing whether an issue warrants escalation.

customer-success+2

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.”