Best Practices

Building an effective chatbot takes more than just uploading documents and deploying. Here are proven best practices to help you create chatbots that genuinely help your business.

Knowledge Base Best Practices

Quality Over Quantity

Upload well-structured, relevant documents. Poor quality or outdated content will lead to poor chatbot responses.

Keep content current: Regularly update your knowledge base as your products, services, or information changes
Use clear formatting: Well-structured documents (with headings, lists, etc.) help the AI understand and retrieve information better
Be specific: Include detailed information rather than vague summaries. The chatbot can't infer information that isn't there

Organize Your Knowledge

Create separate knowledge bases for different topics (e.g., "Product Docs", "Support FAQs", "Sales Materials")
You can connect different knowledge bases to different chatbots depending on their purpose
This keeps responses focused and prevents the chatbot from mixing unrelated information

AI Prompt Best Practices

Define Clear Role and Behavior

Your chatbot's AI prompt sets its personality and behavior. Here's what works well:

Be specific about the role: "You are a customer support assistant for [Company]"
Set tone expectations: "Be friendly, professional, and concise"
Define boundaries: "If you don't know something, admit it and direct them to contact support"

Testing & Optimization

Test Before Deploying

Always test your chatbot thoroughly in the playground before deploying
Try various question types: simple, complex, edge cases
Test all actions to ensure they trigger correctly

Monitor and Iterate

Review conversations regularly to identify gaps
Update knowledge bases when you notice questions the chatbot can't answer
Adjust prompts based on how the chatbot is behaving
Refine action triggers based on actual usage

Continuous Improvement

Building a great chatbot is iterative:

Deploy and collect data: Let real users interact with your chatbot
Review conversations: See what questions come up most often
Update knowledge: Add missing information to your knowledge base
Refine prompts: Adjust behavior based on actual interactions
Optimize actions: Fine-tune when and how actions trigger

Common Pitfalls to Avoid

Over-optimizing too early: Deploy, gather real data, then optimize
Ignoring user feedback: Pay attention to what visitors actually ask
Setting temperature too high: Higher creativity often means lower accuracy
Neglecting knowledge base updates: Outdated information leads to wrong answers