Synthetic Personas

Synthetic Personas explained

A team can examine an idea from different assumed perspectives: what might someone with limited prior knowledge ask, and which information might be missing? A synthetic persona can prompt that discussion. Label what comes from actual research and what was added or invented. Not every model profile is based on current first-party customer data; even a detailed prompt initially remains an instruction to a model.

Asking the persona to react to copy produces a model output. It is neither an observed purchase decision nor an independent voice from the audience. AAPOR explicitly distinguishes human respondents from AI-generated responses. More runs or differently named personas do not automatically create a larger real sample. The proportion of approving model answers is not measured market demand.

Quality depends on the task, data, assumptions, model and evaluation, not simply model size. A plausible result may reproduce stereotypes or smooth away important differences. If a simulation is intended to make a particular prediction, test that prediction against suitable independent observations for that exact use. A previous correct result does not validate every new campaign, region or product category.

Creative Engineering uses these perspective exercises to prepare concepts and sharpen real research questions. We take responsibility for the concept and quality. Record the model version, assumptions and checked sources, and protect any source data used. Assess useful new questions and the effort needed to reach substantiated findings. Simulation costs are not comparable to an equivalent human study unless equivalent evidential value has been demonstrated.