Research Topics:

Data Analysis | Quantitative Research

Content Type:

Glossary

Factorial Design Definition

An experimental design in which all levels of each independent variable are combined with all levels of the other independent variables. A factorial design allows investigation of the separate main effects and interactions of two or more independent variables.

Factorial design is a statistical experimental design used to investigate the effects of two or more independent variables. In this process, all levels of each independent variable are combined with all levels of other independent variables to investigate separate main effects and interactions of two or more independent variables. In marketing research, this design studies how factors interact and influence consumer behavior or outcomes. Factorial design is beneficial because it simulates real-world scenarios by considering multiple factors at once, which enables researchers to identify individual effects and interactions of variables.

Who relies on factorial design?

Businesses, advertising agencies and market strategists rely on factorial design to determine what combination of variables yields the most favorable results, as well as to provide insights for improving business decisions and enhancing product features, pricing and promotions. Other users of this research method are marketing researchers, analysts and professionals.

Why should I care about factorial design?

Factorial design uncovers complex relationships among variables. Findings create a deeper understanding of consumer behaviors. With this approach, companies and marketing professionals can optimize marketing strategies, thus leading to better targeting, product design and customer engagement.