Segmentation/Cluster Analysis
Main aspects
- Groups together respondents with similar characteristics
- Each respondent belongs to only one group
- Via hierarchical, non-hierarchical or latent class methods
- Again commonly used on attitudinal data e.g. two dozen statements concerning prescribing may be used as input to a cluster analysis which might identify three or four different GP 'types'
- Number of clusters is determined by how much variation they explain and their interpretability
- Each respondent can be coded with the relevant cluster number and these can be used as breaks in crosstabs
- Resultant clusters often targeted in ad campaigns