Marketing Research and Insight Glossary

Definitions, common uses and explanations of 1,500+ key market research terms and phrases.

What are Predictor variables?

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Predictor variables Definition

The variables that explain or predict the differences in dependent variables. Examples: demographics, attitudes. Also called independent variables or factor.

Predictor variables, also known as independent variables, are factors believed to influence or forecast an outcome of interest (the dependent variable). In marketing research, they are used in models to explain or predict consumer behavior, brand performance or market trends.

What are key aspects of predictor variables in marketing research?

  • Used to estimate or explain changes in a dependent variable.
  • Can be demographic, psychographic, behavioral or attitudinal.
  • Serve as inputs in regression and other statistical models.
  • May be categorical (e.g., gender) or continuous (e.g., income).
  • Should be theoretically relevant and statistically valid.

Why are predictor variables important in market research?

Predictor variables help researchers understand what drives consumer choices and market outcomes. They form the backbone of modeling efforts aimed at forecasting, segmentation, targeting and strategic decision-making.

Who relies on predictor variables as they pertain to marketing research?

  • Data scientists building forecasting models.
  • Analysts conducting regression or conjoint analysis.
  • Brand managers identifying key purchase drivers.
  • Customer insights teams segmenting audiences.
  • Product developers linking features to satisfaction.

How do market researchers use predictor variables?

Market researchers use predictor variables to uncover relationships between different aspects of consumer behavior and desired outcomes, such as purchase intent or brand loyalty. For example, they might analyze how age, income and social media usage (predictor variables) influence likelihood to try a new product (dependent variable). By inputting these variables into regression models or machine learning algorithms, researchers can identify which factors are most influential, quantify their effects and use the insights to inform marketing strategies, product development and audience targeting.