A structured approach to KM content
Essentials of content optimization for paying users:
- Modular Architecture Design: Break down the body of knowledge into three levels, "Basic-Advanced-Case", and create a correspondence:
- Concept note document (PDF format)
- Methodology guide (Markdown text)
- Real-world case studies (web links + screenshots)
- Predefined Question and Answer (Q&A) Bank: Uploading a Q&A document containing the answers to 50-100 frequently asked questions ensures that the robot prioritizes the answers to these well-crafted questions.
- Version Control Tips: Create monthly iterations of content (e.g., v1.0/v2.0), explaining new knowledge points in the changelog and prompting regular users to subscribe on an ongoing basis.
- Multimedia supplementation: Converting video scripts and podcast subtitles to text for uploading. Although Chatwise does not support direct parsing of audio and video, the text version still improves knowledge coverage.
It is recommended to use the golden ratio of "90% structured content + 10% real-time updates".
This answer comes from the articleChatwise: the AI chatbot that shares knowledge into revenueThe
May not be reproduced without permission:AI productivity tools " How to optimize the content structure of a Chatwise bot in a pay-for-knowledge scenario?
