You've installed the Zammo product and are now wondering: What’s the best way forward? How do you effectively test the chatbot? What questions should you ask? What defines a correct response? And when is it ready to go live?

Follow these best practices to ensure a smooth and effective implementation.

1. Assemble a Small, Focused Team

Start with a small team where each member has clear roles and responsibilities. Assign individuals to key areas such as:

• Project planning – Outlining goals, milestones, and expectations.
• Content development – Determining what information the chatbot should access.
• Workflow design - Crafting customized conversations and API integrations (optional).
• Testing and refinement – Ensuring accuracy and improving responses.
• Publishing and monitoring – Overseeing the chatbot’s launch and performance.

2. Establish or Identify an AI Policy

An AI policy serves as a framework outlining the guidelines for developing and using AI within an organization. Some organizations require a formal policy before initiating a bot project. It’s important to determine whether such a requirement exists within your organization and, if necessary, create a policy to ensure responsible AI implementation.

3. Determine What Content to Index

Apply the 80/20 rule: Focus on indexing the top 80% of requests that take up the most staff time. Prioritizing high-impact content ensures the chatbot is solving the most common user needs efficiently.

4. Define Key Questions for Testing

Since Zammo’s AI understands natural language instead of relying on keyword search, it’s important to consider the different ways users may phrase their questions.

• Work with subject matter experts (SMEs) to identify common queries.
• Create a spreadsheet listing expected user questions for testing. A spreadsheet template is provided below.

5. Establish Expected Responses

In your testing spreadsheet, include a column for expected responses. If the chatbot’s answer differs from what you expect, ask: