There are a wide variety of statistical techniques that either form the main research process or act as a ‘bolt on’ in order to glean maximum insight from a research study. Ci Research has over 20 years’ experience of applying advanced statistical techniques to survey data. We recognise that ‘the language of stats’ can be daunting for some and, indeed, statistical analysis may not be relevant for a variety of research scenarios. We therefore only utilise advanced techniques when they will bring further valuable insight and will always deliver the output in layman terms. Most importantly, we also ensure that results are actionable with total clarity around outcomes and implications.
Our top 10 statistical techniques are as follows:
1. Factor Analysis – Factor analysis is a useful data reduction technique, helping the researcher to see the ‘woods for the trees’. The technique groups’ issues together into a more manageable number of factors. Factor analysis can therefore help determine the underlying factors that summarises customer opinion from a whole host of product / service issues.
The technique is often used as a first stage in an analysis process. Factor analysis can be used to reduce the number of variables utilised to model customer behaviour, satisfaction etc. More concise variables will lead to a more robust model and an outcome, which can be easier for clients to interpret. Factor analysis can also assist the development of perceptual maps of customer opinion.
2. Regression Analysis – Regression analysis is a widely used modelling technique and comes in a variety of forms. The basic aim of this technique is to establish causal relationships between a dependent variable, for example, sales, and one or more explanatory variables, for example consumer spending, season of year, interest rates etc.
The technique can be used to gain a snapshot of the drivers of a variable under analysis. A successful analysis will identify which issues best explain the movement in the dependent variable and so can help a client decide which parts of their business to concentrate upon in order to improve sales, satisfaction etc. Regression analysis is also commonly used as a forecasting tool. Continue reading