Once we have collected good quality data the next step is to carry out analysis to discover actionable insights and support decision making. Analysis may be based upon models of customer motivations, attitudes, beliefs, values and cognitive decision-making processes.

Statistical Analysis - creating actionable customer insight.

We have a great deal of experience finding patterns and abstracting out the essence from a sea of data. We use a variety of statistical tools to:
Build reliable and valid questionnaires (i.e. factor analysis).
Identify groups of people who share similar characteristics (market segments or consumer profiles) (i.e cluster analysis).
Map customers by geography (geo-demographic analysis).
Explore how customers make choices between products, features and pricing strategies (conjoint analysis).
Build predictive models (i.e. regression, correlation, structural equation modelling). With sufficient data it is possible to build models that allow you to explore the relationships between product features, price or service levels and propensity to purchase or defect.
Text mining. We can automatically extract words and phrases from customer comments - and turn these frequencies into quantitative statistics to be investigated and combined with other figures.

We are experienced in a range of tools including SQL, SAS, SPSS, and advanced Excel.