What Are Synthetic Users?
Synthetic users are AI-generated simulations of human behavior. Rather than recruiting real people and scheduling sessions, synthetic user tools use language models and behavioral data to simulate how different types of users would interact with a product, website, or design. Tools like Racoonn use this approach to simulate thousands of diverse personas on a landing page simultaneously.
The technology has matured rapidly. Modern synthetic user tools don't just flag accessibility issues — they simulate the reasoning, decision-making, and emotional responses of specific user types.
Where Synthetic Users Win
Speed: synthetic tests run in minutes vs days for real user testing. Scale: 5,000 synthetic personas can be run simultaneously; recruiting 5,000 real users is prohibitively expensive. Cost: 90%+ cheaper than real user research. Diversity: synthetic tools can represent rare or hard-to-recruit user types (specific professional roles, geographic regions, accessibility needs).
Synthetic users excel at: identifying messaging clarity problems, surfacing objections from diverse audience segments, testing landing page conversion readiness, and catching obvious UX friction that any user type would encounter.
Where Real Users Win
Emotional authenticity: real users express genuine surprise, frustration, delight, and confusion in ways AI can't fully replicate. Complex interaction design: multi-step workflows with visual dependencies are better evaluated by real users. Edge cases: real users do unexpected things that AI doesn't simulate. Novel concepts: for genuinely new product categories, real user reactions reveal mismatches between mental models and product design.
Real user testing is irreplaceable for: first-time evaluation of a novel product concept, deep qualitative emotional research, testing physical products or hardware interactions, and validating that AI test findings hold in practice.
The Hybrid Research Approach
The most effective research combines both: use synthetic users for fast, frequent testing of landing pages and conversion flows (weekly or with every significant change), and use real user research for deeper investigation of specific issues identified by synthetic testing or for new concept validation (monthly or quarterly).
This approach gets the best of both: the speed and scale of AI testing for continuous optimization, and the depth and authenticity of real user research for strategic decisions.
Choosing Based on Research Question
Use synthetic users when: 'Why aren't different user types converting on our landing page?' Use real users when: 'How do users feel when they first encounter our onboarding flow?' Use both when: 'We're launching a new feature and want to understand both conversion readiness and the emotional experience of new users.'