Data and resource maximization in business-to-business marketing experiments: Methodological insights from data partitioning

Abstract Data management is an integral part of knowledge engineering in business-to-business (B2B) marketing experiments. This article introduces the concept of data partitioning as a fresh and useful form of data management in the process of knowledge engineering in B2B marketing experiments; articulates the method for partitioning data in B2B marketing experiments; and discusses the implications of data partitioning in the form of data and resource maximization for B2B marketing experiments. It is the hope of the authors that this article will encourage greater visibility and contribute to the advancement of resource-efficient B2B marketing experiments.

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