DATA PROCESSING AND ANALYSING

DATA PROCESSING AND ANALYSING

Data analysis and interpretation: We have our own team of professionals who can process and analysis even large-scale postal capabilities This allows us to pre-empt and tackle problems during data processing, and to be flexible with data analysis.

We use robust and reliable sources of information (usually available in the public domain, but not always) are interrogated to extract as much information as possible with this we also combine our data collection techniques so the data which collected is more authentic and updated. This way we apply a comprehensive range of content analysis techniques to ensure a thorough interrogation of in-depth information gathered and to identify emerging trends and themes.

STATISTICAL AND ANALYTIC TECHNIQUES:

We carry out statistical analysis such as significance testing on trends, cluster analysis to segment target audiences or multiple regression to identify key drivers of stakeholder satisfaction. Our analytical services add insight through multivariate analysis and other techniques across a range of methods.

Techniques we use:

  • Correlations
  • Regression analysis
  • Key Driver Analysis through appropriate methods (regression, MaxDiff, random forests).
  • Conjoint analysis
  • Maximum Difference Scaling
  • Tree and Forest models
  • Cluster analysis
  • Segmentation of groups through appropriate methods (cluster analysis, latent class analysis)
  • Random Forests
  • Log-linear modelling
  • IRT models
  • Correspondence and multiple correspondence analysis.
  • Missing value imputation
  • Analysis of Variance