Effortless A/B Split Testing with AI-Powered Chatbots
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Automate A/B split testing for your chatbot experiences by dynamically serving different AI responses based on user sessions. This workflow ensures you can test variations and gather data to optimize user engagement without manual intervention.
About This Workflow
This n8n workflow leverages AI and database integration to perform sophisticated A/B split testing on chatbot interactions. It begins by receiving a chat message, then checks for an existing session in Supabase to ensure consistent testing for returning users. Based on whether a session exists, it either assigns a new A/B path or continues with the existing one. The workflow dynamically defines the AI prompt to be used, drawing from pre-defined baseline and alternative values, and then utilizes an AI Agent (powered by OpenAI's GPT-4o-mini) to generate a response. Chat history is managed via a Postgres database, providing a robust solution for evaluating different conversational paths and improving user experience.
Key Features
- Automated A/B Split Testing: Dynamically assign users to different conversational paths for testing.
- AI-Powered Response Generation: Utilize advanced language models (e.g., GPT-4o-mini) for intelligent responses.
- Session Persistence: Maintain consistent A/B testing assignments for returning users using Supabase.
- Flexible Prompt Definition: Easily define and switch between baseline and alternative AI prompts.
- Chat History Management: Store and retrieve chat conversations using a robust PostgreSQL database.
How To Use
- Configure Chat Trigger: Set up the 'When chat message received' node to listen for incoming messages and capture
chatInputandsessionId. - Integrate Supabase: Connect your Supabase credentials and configure the 'Check If Session Exists' and 'Assign Path To Session' nodes to manage user session data in the
split_test_sessionstable. - Define Prompt Values: In the 'Define Path Values' node, customize the
baseline_valueandalternative_valuefor your A/B tests. - Dynamically Select Prompt: Use the 'Get Correct Prompt' node to dynamically select the prompt based on the
show_alternativeflag from session data. - AI Agent Configuration: Connect the 'AI Agent' node to your chosen language model (e.g., 'OpenAI Chat Model') and pass the dynamic
prompt. - Memory Management: Configure the 'Postgres Chat Memory' node with your PostgreSQL credentials and desired table name to store chat history for each session.
Apps Used
Workflow JSON
{
"id": "56927ad7-faed-4f79-aa80-4a3cdaadd9ea",
"name": "Effortless A/B Split Testing with AI-Powered Chatbots",
"nodes": 18,
"category": "Marketing",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
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ID: 56927ad7-faed...
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