Surveys are a commonly used method in UX research to quickly gather quantifiable data. However, surveys can reach their limits when it comes to gaining deeper insights into user experiences. In contrast, qualitative interviews provide deeper insights while requiring more time effort in both data collection and analysis. This paper presents three practice-tested approaches as an exploration of the question how to efficiently combine depth and quantification of insights: a) AI-generated formula for keyword detection with Airtable, b) AI-detected clusters with Miro, and c) AI-moderated interviews and AI generated analysis report with ListenLabs. The content is relevant for UX professionals who wish to make their research processes scalable and efficient.