Analyse Data

As with all research suppliers, we provide basic statistics such as means and frequencies for quantitative data and verbatim quotes from qualitative responses. However, one of the things that differentiates us from many other research suppliers is that that’s just the start of the analytical procedures we use: we also use more sophisticated analytical procedures that maximise the value of the data collected.

The exact nature of the analytical procedures used varies depending on the situation and the project objectives, but qualitative techniques we use include content analysis, cognitive mapping, repertory grid, and means-end chains. For quantitative data we use a full range of univariate, bivariate, and multivariate statistical techniques, including Bayesian analysis, conjoint analysis, and structural equation modelling. While clients don’t need to understand the details of these techniques, using them enables us to provide much deeper insights than would be possible by just discussing summary statistics or qualitative responses.

Here are some quantitative examples that illustrate how this works:

• Chi-square Example
• T-test Example
• ANOVA Example
• Factor Analysis Example
• Cluster Analysis Example
• Regression Analysis Example
• Conjoint Example

Note that neither the analytical techniques listed nor the example applications are exhaustive; they are simply intended to illustrate the types of things that can be done. Most projects we do involve multiple types of analysis.