Research Topics:

Data Analysis | Quantitative Research

Content Type:

Glossary

Factor Analysis Definition

A procedure for data simplification through reducing the many rating scales (or set of variables) used by the researcher to a smaller set of factors or composite variables by identifying dimensions underlying the data.

Factor analysis identifies underlying patterns or relationships among a large set of variables, then transforms the complex data into actionable insights. This statistical process simplifies data by reducing the many rating scales, or variables, used by researchers into a smaller set of factors or composite variables by identifying dimensions underlying the data. In other words, this method simplifies the complexity of data by grouping variables that tend to co-vary – vary in the same time period – together. These factors may not be directly observable but they could impact consumer behavior or preferences.

Who relies on factor analysis?

Marketing researchers, analysts and professionals use factor analysis to uncover concealed dimensions in customer opinions, perceptions and behaviors. Knowing these factors can lead to improved decision making, product development and branding.

Why should I care about factor analysis?

Factor analysis uncovers the driving forces behind customer preferences. It also provides valuable insights that can guide a company’s marketing efforts to bolster strategies. By understanding the connections among variables, businesses and marketing professionals can enhance product features, pricing and messaging to target marketing. Insights from factor analysis can lead to improved customer satisfaction, increased sales and a stronger market position.