Re-Engineering of Marketing for SMEs in Energy Market through Modeling Customers’ Strategic Behavior

Despina S. Giakomidou (), Athanasios Kriemadis, Dimitrios K. Nasiopoulos and Dimitrios Mastrakoulis
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Despina S. Giakomidou: Department of Management Science and Technology, University of Peloponnese, Karaiskaki 70, 221 00 Tripoli, Greece
Athanasios Kriemadis: Department of Management Science and Technology, University of Peloponnese, Karaiskaki 70, 221 00 Tripoli, Greece
Dimitrios K. Nasiopoulos: Bictevac Laboratory—Business Information and Communication Technologies in Value Chains Laboratory, Department of Agribusiness and Supply Chain Management, School of Applied Economics and Social Sciences, Agricultural University of Athens, 118 55 Athens, Greece
Dimitrios Mastrakoulis: Bictevac Laboratory—Business Information and Communication Technologies in Value Chains Laboratory, Department of Agribusiness and Supply Chain Management, School of Applied Economics and Social Sciences, Agricultural University of Athens, 118 55 Athens, Greece

Energies, 2022, vol. 15, issue 21, 1-20

Abstract: In recent years, the energy market has seen an increase in small and medium enterprises (SMEs) participating in the sector and providing relevant services to customers. The energy sector SMEs need to acknowledge whether reengineering their marketing strategy by modeling customers’ website behavior could enhance their digital marketing efficiency. Web Analytics refers to the extracted data of customers’ behavior from firms’ websites, a subclass of big data (big masses of uncategorized data information). This study aims to provide insights regarding the impact that energy SMEs’ web analytics has on their digital marketing efficiency as a marketing reengineering process. The paper’s methodology begins with the retrieval of behavioral website data from SMEs in the energy sector, followed by regression and correlation analyses and the development of simulation models with Fuzzy Cognitive Mapping (FCM). Research results showed that customer behavioral data originating from SMEs’ websites can effectively impact key digital marketing performance indicators, such as increasing new visits and reducing organic costs and bounce rate (digital marketing analytics). SMEs in the energy sector can potentially increase their website visibility and customer base by re-engineering their marketing strategy and utilizing customers’ behavioral analytic data.

Keywords: re-engineering of marketing; digital marketing; big data applications in energy systems; big data in energy markets; digitalization; energy market; customer behavior; regression analysis; FCM simulation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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