Synthetic users are AI-generated profiles that simulate user interactions, allowing UX researchers to gain insights and test designs without human involvement. Their use has surged, with technology enterprises utilizing synthetic data in workflows rising from 23% in 2019 to 67% today. Synthetic users are built on vast datasets of real interactions, offering a scalable, cost-effective alternative to traditional personas, which require manual research. However, this method raises ethical concerns and limitations, particularly in capturing the emotional nuances of human behavior, essential for comprehensive UX studies.
Synthetic users have emerged as a prominent tool in UX research, allowing companies to simulate user behaviors and test designs without traditional human involvement.
67% of technology companies utilize synthetic data in their workflows, a significant increase from 23% in 2019, underscoring a trend towards AI-driven research.
While synthetic users can save time and costs and adjust dynamically using AI insights, they still fall short of capturing the depth of real human emotions.
The creation of synthetic users involves AI models trained on extensive datasets, contrasting sharply with traditional personas, which require considerable manual input and market validation.
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