Research results can be highlighted more effectively using statistical multivariate methods that significantly enhance the usability of the results.

For example, reviewing customer satisfaction results based only on questions with the highest or lowest scores does not provide a solid basis for defining which operations or services require improvement. Nor does an interpretation of results on this basis provide a well-rounded picture of satisfaction in target groups. If an individual feature or characteristic receives poor scores, but the importance of such a feature or characteristic to respondents or its impact on overall satisfaction is low or perhaps even insignificant, a poor score does not necessarily indicate something to be changed or improved. Analysing data with multivariate methods, we can pinpoint the factors (functions and/or services) that have the greatest impact on customer satisfaction and concentrate more on these areas as focus areas or strengths.

Statistical multivariate methods pose various requirements to research material. This means that methods can be selected based on the requirements of different research materials. Each analysis method also offers different capabilities or goals. Naturally, we select the method or methods that will produce the best results for your particular project.