University of Twente Student Theses


The Individual & Organizational Factors Influencing the Implementation of Data-Driven Marketing

Pepping, J.J. (2017) The Individual & Organizational Factors Influencing the Implementation of Data-Driven Marketing.

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Abstract:The world produces every day 2.5 quintillion bytes of data. Of those data, 90% is unstructured (Dobre & Xhafa, 2014). To become of value for companies, Big Data must be analyzed and structured. Big Data analytics is increasingly becoming popular as tool to improve organizational efficiency (Sivarajah et al., 2017), inter alia it is used for marketing purposes. That is why many organizations implement Data-Driven Marketing for marketing purposes. Prior research provides a lot of implementation models, but all of them are focused on IT projects in general. When implementing Data-Driven Marketing, the IT department is of course involved, but many others are too. For example, E-commerce, Marketing, or Data departments can be involved. As the implementation of Data-Driven Marketing is totally different from the implementation of general IT projects, there is a need for a specific model for the implementation of Data-Driven Marketing. Big Data refers to large volumes of data being created by people, tools and machines and is to derive real-time business insights. It requires new, innovative technology to collect, host and process. Data-Driven Marketing is collecting and connecting large amount of online data with traditional offline data, rapidly analyzing and gaining cross-channel insights about customers, the bringing that insight to market via a highly-personalized marketing campaign tailored to the customer at his/her point of need (Teradata, 2016). This study aims at developing an appropriate model that describes the individual and organizational factors influencing the implementation of Data-Driven Marketing within organizations. It will do so by developing a conceptual model based on prior literature. After that, the conceptual framework will be tested using a two-round Semi-Delphi method. In the first round, five experts that implemented Data-Driven Marketing in an organization are interviewed. Based on those interviews, the conceptual model is updated. The updated model is used in the second round of the Semi-Delphi study. In this round, two experts from within the same organization are being interviewed. The results of these interviews are again used to update the conceptual model. The results of this study present an accurate model for the implementation of Data-Driven Marketing within organizations that describes individual and organizational factors that are of influence on the different processes of the implementation of Data-Driven Marketing. The findings of this study are an attribution to the current literature on Data-Driven Marketing and implementation models. Besides that, it can be used by organizations that want to implement Data-Driven Marketing and marketing agencies that help organizations by implementing Data-Driven Marketing.
Item Type:Essay (Master)
Faculty:BMS: Behavioural, Management and Social Sciences
Subject:85 business administration, organizational science
Programme:Business Administration MSc (60644)
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