Can Qual-at-scale replicate, or perhaps improve upon, quantitative scales as an input into segmentation? Most segmentations run on a long attitudinal battery written before anyone speaks to a customer. We are testing whether a handful of open-ended questions, converted to embeddings, can build a better one. Same respondents, both instruments, three competing solutions, scored on holdout prediction, typing accuracy, reproducibility, interpretability, and interview length. The result tells the industry what segmentation inputs should be made of, and how much questionnaire we can give back to respondents.