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AI-Driven Infinite Loop User Interview System

This workflow utilizes an AI language model to automate user interviews, capable of generating open-ended questions and recording user responses in real-time. Users initiate the interview through a form, and the interview data is stored in a Redis database and synchronized to Google Sheets for easy data analysis and sharing. Users can end the interview at any time, and the interview records can be accessed via a Webhook, ensuring data security and efficient management. This system is suitable for market research, user experience studies, and academic surveys, greatly enhancing the flexibility and efficiency of interviews.

Workflow Diagram
AI-Driven Infinite Loop User Interview System Workflow diagram

Workflow Name

AI-Driven Infinite Loop User Interview System

Key Features and Highlights

  • Utilizes AI language models to automatically generate open-ended interview questions, enabling infinite loop questioning.
  • Initiates interviews via form triggers, facilitating effortless collection of user responses.
  • Records interview Q&A pairs in real-time, building a complete dialogue history.
  • Allows users to terminate the interview anytime by entering the “STOP” command.
  • Stores interview data in real-time within a Redis database, ensuring efficient session management and rapid response.
  • Automatically syncs interview results to Google Sheets for easy data sharing and subsequent analysis.
  • Provides access to a web-based display of the full interview record via Webhook after the interview concludes.
  • Employs Redis session management with automatic data expiration after 24 hours to ensure data security.

Core Problems Addressed

Traditional user interviews are often time-consuming, labor-intensive, and costly to prepare and execute. This workflow automates the interview process through an AI-driven interviewing agent, reducing human resource demands while enhancing flexibility and efficiency. Real-time data storage and export simplify team analysis and data sharing.

Use Cases

  • Market Research: Gather in-depth user feedback on products or services.
  • User Experience Research: Understand users’ genuine feelings and needs when using products.
  • Academic Surveys: Automate questionnaire-style interviews to collect qualitative data.
  • Remote Interviews: Enable users to participate online anytime without face-to-face interaction.
  • Product Validation: Continuously probe user pain points and improvement suggestions through ongoing questioning.

Main Process Steps

  1. Start Interview: User inputs their name via a web form, triggering the interview process and generating a unique session ID.
  2. Set Interview Topic: The system sets the interview theme (e.g., “Real Driving Test Experience in the UK”).
  3. AI Questioning: The AI interview agent automatically generates the next open-ended question based on the user’s previous answer.
  4. Collect Answers: User responds via the form or inputs “STOP” to end the interview.
  5. Record Data: Each question and answer pair is written in real-time to the Redis session list and simultaneously saved to Google Sheets.
  6. End Interview: Upon detecting the user’s end request, session data is cleared and the user is redirected to the interview completion page.
  7. Display Interview Record: Via Webhook access, users and teams can view a web-based presentation of the complete interview transcript.

Involved Systems and Services

  • n8n Form Trigger: Initiates the interview and collects user input.
  • LangChain AI Agent Node: Automatically generates interview questions and processes user answers.
  • Redis (hosted via Upstash): High-performance session storage managing interview data and states.
  • Google Sheets: Stores and shares interview results.
  • Webhook and HTML Nodes: Provide dynamic web page display after interview completion.
  • UUID Generation Node: Creates unique identifiers for each interview session.

Target Users and Value Proposition

  • Product Managers & User Researchers: Automate interview workflows, reduce manual effort, and improve data collection efficiency.
  • Market Research Teams: Rapidly gather large volumes of user feedback and accurately identify user needs.
  • Developers & Automation Engineers: Build intelligent interview bots, integrate multiple services, and enable efficient data flow.
  • Educators & Academic Researchers: Conveniently conduct qualitative interviews, enhancing research data quality and acquisition speed.
  • Any Organizations or Individuals Requiring Continuous User Interviews: Leverage AI to conduct 24/7 interviews, overcoming time and geographic constraints.

This workflow centers on AI combined with modern automation technologies to create a flexible, efficient, and scalable user interview platform. Suitable for both small teams and large enterprises, it enables automated intelligent interviewing and data management, significantly boosting interview effectiveness and user experience.