Abstract
Digitalization of value chains and company processes offers new opportunities to measure and control a firm’s activities and to make a business more efficient by better understanding markets, competitors, and consumers’ behaviors. Among other methodologies, field experiments conducted in online and offline environments are rapidly changing the way companies make business decisions. Simple A/B tests as well as more complex multivariate experiments are increasingly employed by managers to inform their marketing decisions.
This chapter explains why field experiments are a reliable way to reveal and to prove that a business action results in a desired outcome and provides guidelines on how to perform such experiments step by step covering issues such as randomization, sample selection, and data analysis. Various practical issues in the design of field experiments are covered with the main focus on causal inference and internal and external validity. We conclude the chapter with a practical case study as well as a brief literature review on recent published articles employing field experiments as a data collection method, providing the reader with a list of examples to consider and to refer to when conducting and designing a field experiment.
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Notes
- 1.
Edward W. Deming was an eminent engineer, statistician, professor, and management consultant for more than half a century. His work on statistical process control and other strategies for data-driven decision making continues to be relavent today.
- 2.
For an interesting discussion on the choice of participants for an experiment and the questionability of employing students, refer to Koschate-Fisher and Schandelmeier (2014).
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Valli, V., Stahl, F., Feit, E.M. (2022). Field Experiments. In: Homburg, C., Klarmann, M., Vomberg, A. (eds) Handbook of Market Research. Springer, Cham. https://doi.org/10.1007/978-3-319-57413-4_3
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