Today, AI agents and chatbots are not just answering one question at a time. They are handling full conversations with users. A customer may start with a greeting, then ask multiple questions, change their request, or ask for clarification.
Because of this, testing a chatbot is no longer just about checking one question and one answer. We must test how the agent behaves during the entire conversation. This is called multi-turn conversation testing.
Salesforce Agentforce now supports this type of testing using conversation history, which makes agent testing smarter, more reliable, and closer to real-life usage.
Let’s understand this step by step in easy words.
Why Single-Question Testing Is Not Enough
Earlier, developers usually tested agents like this:
- Ask one question
- Check one reply
- Mark the test as pass or fail
But real users don’t talk like this. A real user may say:
- “Hello”
- “My name is Rahul”
- “Can I bring my pet?”
- “What is the check-in time?”
Now the agent must:
- Remember the user’s name
- Understand that the pet question is about hotel policy
- Answer check-in time correctly
If the agent forgets earlier information or gives wrong context-based answers, the customer experience becomes poor.
That’s why testing with full conversation history is necessary.
What Is Conversation History Testing in Agentforce?
Conversation history testing means:
- The agent is tested using all previous messages in the chat
- Every new reply is checked based on what was already said
- The agent behaves just like it would in a real customer chat
Instead of testing one line at a time, you test the entire conversation flow.
What Is Agentforce Testing Center?
Agentforce Testing Center is a Salesforce tool that helps you:
- Create automated tests for AI agents
- Test real chat conversations
- Verify each response step-by-step
- Automatically detect errors when the agent behavior changes
With conversation history support, the Testing Center becomes even more powerful.
Step 1: Collect a Sample Conversation
First, you need a real or sample conversation. You can get this from:
- Agent Builder
- Past user chats
- Demo conversations
Example conversation:
User: Hi
Agent: Hello! How can I help you today?
User: My name is Rahul
Agent: Nice to meet you, Rahul!
User: Are pets allowed?
Agent: Yes, pets are allowed with some conditions.
User: What time is check-in?
Agent: Check-in starts at 3 PM.
This full chat becomes your test conversation.
Step 2: Use Conversation History During Testing
Now instead of testing only one message, the Testing Center does this:
- It sends the full chat history to the agent
- Then it asks the agent to generate the next reply
- The system checks if the reply matches your expected output
So every time:
- The agent sees everything said earlier
- It must reply correctly based on the full context
This is exactly how real customers interact.
Step 3: Convert It Into Batch Tests
Once your full conversation is ready, you can convert it into a batch test file.
Each row in the batch test contains:
- Conversation history so far
- Current user message
- Expected agent response
Important best practice:
Each test row should end with the agent’s reply, not the user’s message.
This keeps the flow correct for the next test step.
Step 4: Automated Turn-By-Turn Validation
Now the automated system runs the entire chat step by step:
- Checks greeting quality
- Confirms if the name is remembered
- Verifies policy answers (like pets allowed or not)
- Tests time-based responses like check-in
Each step is automatically marked as:
- Pass
- Fail
You get a full report of what worked and what failed.
Why Conversation Testing Is Very Important
Here’s why this feature is a big improvement:
1. Real-Life Testing
You are testing the agent exactly how users talk in real life, not in artificial one-line tests.
2. Better Accuracy
The agent must remember names, preferences, and past questions correctly.
3. Easy Regression Testing
If you update:
- Knowledge articles
- Business logic
- Prompts
You can re-run the same tests and instantly see if anything broke.
4. Saves Time
Manual testing of full conversations takes hours. Automated tests finish in minutes.
5. Improves Customer Satisfaction
Fewer mistakes = happier users = better trust in AI.
Example Use Case
Let’s say your AI agent handles hotel bookings.
A customer might ask:
- About room availability
- Then pet rules
- Then late check-out
- Then cancellation policy
With conversation testing:
- You can verify that the agent handles all these questions correctly in one flow
- Not just as isolated answers
Final Summary
Multi-turn conversation testing in Agentforce allows you to:
- Test the full user journey
- Validate context awareness
- Catch errors early
- Maintain consistent high-quality agent behavior
Instead of only testing what the agent says, you now test how the agent behaves across an entire conversation.
This makes AI agents smarter, safer, and production-ready.
Have any questions? Feel free to drop an email to support@astreait.com or visit astreait.com to schedule a consultation.