customer-success
Customer Success equips you with patterns for support infrastructure: ticketing system integration, hybrid-search knowledge bases, AI-driven ticket triage, and escalation automation. It covers self-service portal design, SLA tracking, and feedback loops that surface product signals from support interactions.
Customer Success supports building support ticketing, knowledge bases, and triage automation for customer support operations.
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Install
travisjneuman/.claude/customer-success · repository language: JavaScript
git clone https://github.com/travisjneuman/.claude
cp -r .claude/skills/customer-success ~/.claude/skills/customer-successnpx skillfed install travisjneuman/.claude/customer-successFrequently asked questions
AI-generated answers based on this skill's SKILL.md and metadata
How to build a support ticketing system with customer-success?
Customer-success provides patterns for integrating support ticketing and triage systems into your infrastructure. It covers ticketing system integration, ticket routing automation, and escalation workflow design to help you build or connect existing platforms like Zendesk or Intercom. The skill emphasizes triage automation to route tickets efficiently based on priority and agent expertise.
What does customer-success offer for knowledge base design?
Customer-success equips you with patterns for designing searchable knowledge bases and self-service portals. It covers hybrid-search implementation, help center architecture, and in-app help widget development. These patterns enable customers to find answers independently, reducing support volume while improving satisfaction through effective self-service help center setup.
How can customer-success help with SLA tracking and monitoring?
Customer-success provides guidance on setting up SLA policies and monitoring support metrics like first response time and resolution time. It includes patterns for tracking SLA compliance, measuring CSAT and NPS metrics, and implementing dashboards to monitor support team performance against defined service level agreements.
Does customer-success support customer health scoring?
Yes, customer-success implements patterns for customer health scoring and churn detection. It helps you build models that surface product signals from support interactions, enabling you to identify at-risk customers early. This includes feedback collection systems and metrics that predict customer churn based on support behavior and engagement signals.
What AI capabilities does customer-success include?
Customer-success covers conversational AI and chatbot support flows for automating routine customer interactions. It includes patterns for AI-driven ticket triage, escalation automation, and in-app chatbot development. These capabilities help reduce manual triage overhead while ensuring complex issues reach the right human agents quickly.
How does customer-success optimize support team workflows?
Customer-success provides patterns for support team workflow optimization through ticket routing systems, escalation automation, and feedback loops. It integrates customer satisfaction measurement with operational metrics, helping teams prioritize high-impact issues and continuously improve response times and resolution quality.
SKILL.md
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Customer Success Engineering
Overview
This skill covers building technical systems that power customer support and success operations. It addresses support ticket system integration (Zendesk, Intercom, Freshdesk), knowledge base architecture, conversational AI chatbot design, customer feedback collection and routing, SLA management and enforcement, escalation workflow automation, self-service portal implementation, and customer health scoring models.
Use this skill when building or integrating support systems, designing chatbot flows, creating self-service documentation portals, implementing SLA tracking, building customer health dashboards, or automating support workflows.
Core Principles
- Self-service first - The best support interaction is the one that never happens. Invest in searchable knowledge bases, in-app help, and contextual guidance before scaling human support.
- **Automate
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