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

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.