Data analysis

Research data analysis that provides actionable insights to drive business change. All analysis is designed to meet research user needs and support our customer requirements.

Data analysis methods

Through a collaborative research design process, we ensure:

easy identification of actions and improvement priorities and prioritised
visibility of different respondent groups and research segmentation views
advanced analysis techniques to reveal insight and opportunities for improvement.

We have full in-house analytical capability and experience in supporting customer requirements. Our team work with SPSS and other appropriate analysis packages, enabling high quality data transition, manipulation and analysis of data.

We have significant experience using statistical tools to uncover data trends and build insightful feedback from customers, employees and other stakeholder groups. More importantly, we are able to insightfully interpret and apply findings from different business environments.

Applying statistical knowledge we support the use of advanced data analysis techniques including:

Significance testing
Correlation analysis
Regression models
Factor analysis
Discriminant analysis
Conjoint analysis
Key driver analysis
Trade-off analysis
Gap analysis

All data analysis specifications and formats are agreed with our clients to ensure their needs are met, in terms of data content and visual presentation.