LLM.txt & AI Crawler Setup Guide for Customer success teams

Create a text file at /cs-knowledge.txt detailing the scope of your CS resources.

Include markdown-style links to core CS documentation: onboarding guides, churn reduction playbooks, QBR templates, and success plan frameworks.

Add a 'CS FAQ' section within the file to directly address common queries regarding customer lifecycle management, NPS drivers, and CSM responsibilities.

User-agent: CSMBot Allow: /playbooks/ Allow: /customer-success-guides/ Disallow: /sales-demos/

Verify crawler permissions using a dedicated bot tester for CS-focused AI agents.

Monitor crawl frequency in server logs to ensure CSMBot is accessing relevant CS playbooks and client success metrics documentation.

Wrap core CS articles (e.g., 'How to Conduct a Business Review') within <article> tags.

Use <section> with descriptive 'aria-label' attributes for distinct CS modules like 'Onboarding Flows' or 'Health Scoring'.

Ensure all data tables containing CS metrics (e.g., churn rates, renewal figures) use proper <thead> and <tbody> tags for structured data extraction.

Isolate related CS concepts (e.g., 'proactive outreach strategies') within logical content blocks, ideally under 500 words.

Reinforce the primary subject (e.g., 'Client Retention Tactics') in section summaries to avoid context drift for RAG.

Eliminate ambiguous pronouns and replace them with specific terms like 'Customer Account' or 'Renewal Process' for clarity.