👩‍🔬Written by: Daniel Mitev

📢 Hosted by: UX Collective

🌐 Read on Medium: Article Link

⏱️ Full Article Length: ~12 minutes

⏱️ Summary Reading Time: ~4 minutes

🧠 Key Concepts

1. Understanding Synthetic Users

• Definition: Synthetic users are AI-generated profiles designed to mimic real user behaviours, providing artificial research findings without involving actual users.
• Creation: Developed using AI models trained on extensive datasets of real user interactions, behavioural patterns, and decision-making processes.
• Purpose: Used in UX research to test interfaces, workflows, and design elements efficiently and cost-effectively.

2. Advantages of Using Synthetic Users

• Cost Efficiency: Organisations can significantly reduce UX research budgets by relying on synthetic users, with some reports indicating up to a 30% reduction.
• Speed: Accelerates testing processes, allowing for rapid iteration and development cycles.
• Scalability: Enables testing across diverse user scenarios and global markets without the logistical challenges of recruiting real participants.

3. Limitations and Risks

• Lack of Emotional Depth: Synthetic users cannot replicate the emotional responses and unpredictability of real human users, potentially leading to overlooked usability issues.
• Over-Reliance on AI: Dependence on synthetic data may result in designs that perform well in simulations but fail in real-world applications, leading to decreased user engagement and costly redesigns.
• Ethical Considerations: Raises questions about the accuracy and effectiveness of research findings derived solely from AI-generated data.

4. Balancing Synthetic and Real Users in UX Research