Synthetic respondents are artificial personas generated by machine learning models to mimic human responses. When informed by diverse datasets, these “stand-in consumers” can be used to quickly evaluate new product concepts. The overnight rush to launch synthetic feedback tools has posed a dilemma for the market research industry, primarily due to AI’s ability to produce convincing—but sometimes unsubstantiated—output. In this article, we share three characteristics of best-in-class synthetic models—and why a “fake it ‘til you make it” approach won’t suffice. [Ray's note: Imagine synthetic students to stimulate class discussions and to engage self-paced learners]
