Multivariate research techniques involve the analysis of more than one statistical outcome variable at a time.
Techniques such as factor analysis, cluster analysis, multidimensional scaling, conjoint analysis, and multiple regression analysis fall under this category and are used to understand complex relationships within data sets.
These techniques help in product development by identifying patterns, segmenting markets, and predicting outcomes. Reference: Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E., & Tatham, R.L. (2006).
Multivariate Data Analysis. Pearson.