Personas are useful when they help a business understand how people think, decide and act. They are less useful when they simply create a polished version of what a customer might say. That distinction is becoming more important as artificial intelligence makes it easier to generate convincing customer profiles at speed.
Synthetic personas can appear highly realistic. They can answer questions, react to messages and simulate preferences. This makes them useful for quick testing, creative development and early exploration. The risk is that they may reflect what a model assumes a person would say rather than what real people are likely to do.
Evidence-based personas take a different approach. They are built from real-life data and behavioural signals, with synthetic data used to improve and optimise the model. This matters because commercial decisions need more than plausible language. They need insight into behaviour, timing, barriers, motivations and likely action.
Synthetic personas focus mainly on what people say. Evidence-based personas focus on what people do. That makes them more relevant when decisions carry greater risk, when audiences are complex, or when timing matters. In sectors such as healthcare and life sciences, where customer behaviour can be shaped by regulation, professional context and patient need, a stronger evidence base can improve the quality of decision-making.
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