Can I use this for segment-specific marketing?

Yes, it includes normalization patterns to tag signals by persona and vertical, enabling highly precise lifecycle journeys and messaging.

What data sources does this skill support?

The skill provides guidance for integrating data from warehouses, product analytics platforms, and CS tools into a unified signal stack.

Does it provide templates for health scoring?

Yes, it includes schemas for health score dimensions, weightings, and thresholds to help define what a 'healthy' customer looks like for your business.

How does this skill help with customer churn?

It provides a diagnostic framework to identify negative usage patterns and declining sentiment signals, allowing teams to intervene with targeted plays before a customer cancels.

Customer Insights & Telemetry

Name: Customer Insights & Telemetry
Author: gtmagents

bygtmagents

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マーケティングオートメーション

Analyzes product usage, health, and sentiment signals to drive customer lifecycle programs and retention strategies.

概要

This skill empowers Claude to act as a bridge between raw product telemetry and actionable Go-To-Market (GTM) strategies. It provides a structured framework for consolidating disparate data points—including product usage, engagement metrics, and customer sentiment—into comprehensive health scores. By automating the identification of churn risks and expansion opportunities, it helps teams build precise, segment-specific lifecycle journeys and prioritize high-impact customer success interventions.

主な機能

Automated lifecycle journey mapping for specific segments
Data normalization across account IDs, personas, and verticals
Standardized health score schema and weighting
Churn and retention risk diagnosis frameworks
29 GitHub stars
Multi-source signal consolidation (usage, sentiment, commercial)

ユースケース

Creating insight briefs for CS and Product teams to address adoption gaps.
Building automated onboarding journeys based on real-time usage signals.
Identifying high-value accounts for advocacy programs or expansion offers.

概要

主な機能

Automated lifecycle journey mapping for specific segments
Data normalization across account IDs, personas, and verticals
Standardized health score schema and weighting
Churn and retention risk diagnosis frameworks
29 GitHub stars
Multi-source signal consolidation (usage, sentiment, commercial)

ユースケース

Creating insight briefs for CS and Product teams to address adoption gaps.
Building automated onboarding journeys based on real-time usage signals.
Identifying high-value accounts for advocacy programs or expansion offers.