Intensions Consulting provides market segmentation, identifying target audiences that fall into different groups based on geo-demographic, psycho-graphic, and behavioural characteristics.
Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) are statistical techniques that are used to uncover relationships among multiple variables and identify a smaller number of underlying latent factors. These tools have been developed for over one hundred years and have become one of the most frequently used statistical methods for assessing validity in psychological testing (Izquierdo et al., 2014).
Exploratory factor analysis and confirmatory factor analysis are both frequently used for developing quantitative measures in psychology (Peterson, 2017), adding to academic literature on theories of intelligence, personality, executive functioning, and psychopathology (Flora & Flake, 2017).
Likewise, principal components analysis (PCA) is a data analysis technique that can be used to extract information from data to uncover a simplified underlying structure of the data set (Abdi & Williams, 2010). Such statistical tools can be used to cluster market audiences into distinct groups, based on characteristics such as attitudes and spending habits (James et al., 2013).
From food to finance, healthcare to advertising, Intensions Consulting have used market segmentation around the world to define target audiences, uncover market opportunities, and improve business impact. If you'd like to learn more about market segmentation, please contact us at: email@example.com.
- Abdi, H., & Williams, L. J. (2010). Principal component analysis. Wiley Interdisciplinary Reviews: Computational Statistics, 2(4), 433-459. doi:10.1002/wics.101
- Flora, D. B., & Flake, J. K. (2017). The purpose and practice of exploratory and confirmatory factor analysis in psychological research: Decisions for scale development and validation. Canadian Journal of Behavioural Science / Revue Canadienne Des Sciences Du Comportement, 49(2), 78-88. doi:10.1037/cbs0000069
- Izquierdo, I., Olea, J., & Abad, F. J. (2014). Exploratory factor analysis in validation studies: Uses and recommendations. Psicothema, 26(3), 395-400. doi:10.7334/psicothema2013.349
- James, G., Witten, D., Hastie, T., & SpringerLink ebooks - Mathematics and Statistics. (2013). An introduction to statistical learning with applications in R. New York: Springer New York. doi:10.1007/978-1-4614-7138-7
- Peterson, C. (2017). Exploratory factor analysis and theory generation in psychology. Review of Philosophy and Psychology, 8(3), 519-540. doi:10.1007/s13164-016-0325