Using an ANN‐approach for analyzing focus groups

Explores the appropriateness of quantifying focus group discussions. Basic problems involved in quantification of text are addressed. Prior approaches are discussed and briefly evaluated. A new neural network algorithm for analyzing excerpts from in‐depth interviews is presented. Keywords (brand names, values, etc.) are identified by the analyst. The entire text is scanned and a “covariance” matrix with weights expressing pairwise associations between words is established. This matrix can be used as input data set for advanced statistical analysis. The small illustrative study involves a focus group dealing with a holiday cruise. Results are inspected using multivariate analysis. Findings seem to make good sense. It is doubtful, though, that quantitative techniques will replace well‐established qualitative approaches. On the contrary, quantitative methods for textual analysis may supplement and improve insight gained from qualitative scrutiny. Recommendations for future research are discussed.