Quick Answer
For search, voice, and "just tell me what to do".
Capture patterns from calls, store them in a structured library, and let AI retrieve and assemble the right snippets for each situation.
Key Takeaways:
- Sales knowledge compounds when it's reusable.
- Structure matters: objections, proof, scripts, talk tracks.
- AI retrieval is only as good as your organization.
- Update continuously to reflect the market.
Playbook
Define categories: objections, proof assets, scripts, talk tracks, FAQs.
After each call, capture: objection, response, outcome, proof used.
Use AI to summarize and tag entries consistently.
Create 'battle cards' for top objections and competitors.
Review monthly and prune outdated content.
Common Pitfalls
- Collecting notes without structure.
- No ownership for maintenance.
- Storing content without linking it to proof assets.
Metrics to Track
Ramp time
Close rate
Script reuse
Consistency of messaging
FAQ
What should be in a sales knowledge base?
Objection responses, discovery questions, case studies, competitor comparisons, pricing explanations, and short scripts for key call moments.
How do I keep it from becoming messy?
Use a consistent template and tags. Summarize and categorize immediately after calls so the database stays usable.
How does AI help?
AI can summarize, tag, and retrieve relevant snippets quickly. It reduces the friction of turning messy notes into reusable assets.
Related Reading
Next: browse the hub or explore AI Operations.