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The answer to this question is: both. We use an "advanced AI" approach (also known as “multi-modal”), which blends several types of AI (NLP, NLU, ML, GPT) with statistical approaches based on context. This allows you to get many qualitative insights on the interests of your prospects and customers, even down to a sub-category level, alongside quantitative data at the same time.
It's not magic, but a rigorous series of steps. This approach also has some limitations. For example, we can tell if ice cream matters to a segment of your target audience, but the "last mile" questions on variations, like flavor, color, etc., still require asking each member specifically.
That said, we can get directional answers to new questions in a matter of hours, we can incorporate qual and quant research too, and we can answer new questions fast, where traditional methods may need months to field qual research studies and where they can't easily go back and for clarification if there are follow ups.
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We use a multi-modal approach that combines AI techniques (NLP, NLU, ML, GPT) with statistical approaches to provide both qualitative and quantitative insights. While we can provide qualitative insights on interests, there are limitations in capturing specific variations without asking each individual. However, our approach allows for fast answers to new questions and incorporates both qual and quant research.