1. Introduction
The constantly changing context of the market nowadays often challenges businesses and leads many of them to adverse financial situations. From this status, small and medium enterprises (SMEs) are in more danger than bigger organizations. Especially in markets where a few big companies dominate, such as the energy sector, SMEs should focus on more innovative methods to attract customers. This can be achieved by offering more flexible electronic services (e-services) and by better understanding their customers’ behavior. For this to happen, a constant process of digitization and digital transformation is required.
Digitization refers to creating a digital representation of physical objects or attributes [
1]. Digitalization refers to enabling or improving processes by leveraging digital technologies and digitized data. Therefore, digitalization presumes digitization. Digital transformation is business transformation enabled by digitalization [
1]. Digital transformation tactics of a pre-digital entity are based on searching for an innovative digitization strategic plan and establishing a flexible framework in which installments between understanding and conducting with a service provider are entangled, according to Chanias et al. [
2]. Skogland [
3] investigated how a corporation with an institutional plan to enhance corporate digital transformation might create a new notion of customer engagement. Once the view that marketing is primarily a corporate strategy that places consumer happiness at the center of the decision-making system is accepted, the importance of marketing reengineering could be seen as a highly favorable option [
4].
Businesses should seek to obtain an improved comprehension of the links among the digitalization and sustainability transformation and connected macroscale emerging advancements (e.g., blockchain technologies) and cultural patterns (e.g., personal data protection, electricity preference, and local government preferences) [
5]. In this way, more possibilities would arise for firms to harvest and increase their digital marketing efficiency by re-engineering core marketing procedures. The surge of skeptical inquiry and consciousness about the institutional function of marketing has corresponded well with the birth of a revolutionary unique management strategy, the process of re-engineering [
4]. The basic idea of re-engineering argues that the emerging economic perspective requires companies to embrace significant, if not transformational, different insights into their activities [
6].
Several electronic-commerce (e-commerce) and e-service businesses, in addition to the economy’s largest competitors, function as small and medium-sized enterprises (SMEs). These are frequently developed by small parties of relatives, associates, families, or individuals, and are enlarged and refined throughout time [
7]. They make the consumer feel at ease by using their particular e-service offering approach, which is very customizable. The bulk of service firms are in the SME market, which means they have reduced economic resources to implement expensive reforms. SMEs’ sustainability revolution is enabled and constrained by digital transformation.
Analysts predict a comeback in carbon levels and an upsurge in electricity consumption, aided by extremely cheap worldwide resource costs [
8]. Given that the energy sector, both generation and consumption, accounts for 75% of the European Union’s (EU) carbon emissions, measures are needed to minimize such a recovery all over the market, notably in buildings/heat, industry, and transportation [
9]. In this context, following energy efficiency policies, customers may search for alternative and innovative services provided by energy SMEs that could limit energy consumption and provide engaging services [
10]. SMEs that have correctly created their web pages, arranged an e-commerce platform, and a good delivery network are among many that may expand and earn an appropriate income regardless of global energy issues. E-commerce has established a doorway into the market, a method to make even the most mundane transactions. Customers began to purchase increasingly more under the constraints of e-markets, with the context of e-commerce being altered remarkably [
7].
During the time customers spend on SMEs’ websites, they create digital traits that sum up their behavior. That information originated from website usage data, belonging to the wider field of big data, and can either reflect single-user or aggregated data. Big data is described as a massive quantity of unordered data [
11]. Marketers should construct and methodically process substantial quantities of information in an attempt to obtain awareness from them [
11]. Web analytics is a category of big data that can be created by webpage visitors by performing online searches [
12]. This process can be defined as collecting and analyzing customer behavior on a firm’s website so that firms can gain a better understanding of the interrelations between website visitors and company webpages [
13]. Web analytics are critical success factors that are derived from commercial websites, converted, and filtered in a quantitative manner [
14].
The paper’s structure is organized accordingly, with
Section 1 including the literature review;
Section 2 analyzing the extraction of customers’ behavioral data and settling research hypotheses; and
Section 3 showing the outcomes of the regression and correlation analysis, as well as the Fuzzy Cognitive Mapping (FCM) model that was developed for supporting the study’s findings. FCM models represent a modeling process that provides fuzzy stationary variances to all included factors by applying factor relationships to the system. Lastly,
Section 4 presents the discussion of the performed analyses’ results, as shown in the previous section, and
Section 5 elaborates on the research’s conclusions.
1.1. Energy Markets, SMEs, and Digitalization
SMEs are critical to economic systems, especially those in emerging nations. SMEs support a large proportion of corporations worldwide and are critical for job establishment and worldwide financial advancement. SMEs account for approximately 90% of enterprises and hire over 50% of the global workforce [
15]. SMEs do have high possibilities for energy savings, namely 37%, according to Richert [
16], due to their versatility, direct engagement, and instant staff influence [
17].
Concerning the energy markets, multiple innovations have been proposed to lower energy costs for customers through online approaches [
15]. Other developments utilized scheduling methods to improve household electricity consumption and increase customers’ preferences and comfort [
16]. Another notable fact is the advanced energy-saving method, which is plain and can be quickly embraced by SMEs all over the world, and was aided by the digitalization context, ultimately contributing to enhanced employee engagement and improved customer behavior while constructing areas [
17].
The digitalization trend has exerted a significant beneficial influence on the growth of e-commerce [
18]. E-commerce refers to completing commercial activities via the internet, and webpages serve as the platform for such operations [
19]. Webpages are growing into essential platforms for merchants all over the globe, and via them, electronic shops give accurate data, as well as establish trustworthy and protected information tools to ensure a satisfying service-providing process and supply [
20]. SMEs’ sustainability is being driven by flexible e-services and smart gadgets [
21]. The same applies to SMEs in the energy sector.
Customers are increasingly aware of new services and innovations, as a result of technological advancements, and it is becoming increasingly challenging to engage them via conventional advertising [
22]. Based on the energy market, service-oriented firms might utilize a variety of tools and services targeted at digitalizing operations. Digitalization of service procedures necessitates vast amounts of data processing, connectivity, and database server needs, as well as the prospect of digital isolation of some client segments [
23]. Through the digitalization framework, energy SMEs could harvest any available customer behavior data at their disposal to efficiently segment their client base.
1.2. Customers’ Behavior in Energy Markets through Web Analytics
SMEs should pay more attention to activities that enable technological advances to boost organizational performance [
24]. Consumers engage with e-services through websites, selecting personal characteristics of the arranged services they wish to purchase, and afterward, selecting the technique of payment and business operations [
25]. The value of e-services is largely determined by how the e-service company’s webpage is organized, how it functions, how rapidly a provided service is offered, and what the outcome of the e-service requirement procedure is [
26].
Due to the high demand of the energy market’s service sectors, regarding power supply and supplementary services, customers are searching the world wide web for sustainable and beneficial alternatives. Through these quests, websites carry a plethora of web data concerning customers’ behavioral information. As referred to above, web analytics reflects the behavior of website visitors, which can adequately indicate customers’ preferences for energy SMEs’ services. Hence, the analysis of such behavioral data is necessary for the sustainability of firms in highly competitive markets, such as the energy one. Utilization of customers’ behavior over firms’ websites has been proven capable of providing valuable information for enhancing their digital marketing campaigns and sustainability [
27].
Moreover, customers’ behavior metrics have been strategically harvested by other sectors, such as the air forwarding and airline industry, leading to higher profitability and sustainability [
28,
29]. Most recently, the behavior of website customers of decentralized and centralized payment networks has been a key implication in improving their marketing strategies’ efficiency [
30]. At this point, the authors tend to exploit customers’ website behavioral patterns to present a potential way for energy SMEs to enhance their digital marketing efficiency and corporate performance.
1.3. Benefits from Re-Engineering of Marketing for SMEs
Customers expect a progressively increasing quality of service that corresponds to their rising expectations. A portion of small businesses have started to recognize that greater quality of consumer service influences the performance of the offered services, allowing them to compete in the sector. Numerous consumers make purchasing decisions based on cost, although many of them value the standard and value of customer experience more [
31]. According to Pires et al. [
32], the massive portion of information produced as a consequence of activity digitalization necessitates the development of the latest experience and understanding and the ability to endorse decision-making, problem-solving, and procedure improvement.
Effective execution of digital transformation is heavily based on the capabilities of the firms’ employees [
7]. Vital changes in organizations’ strategy, based on marketing and customer data, provide better corporate performance [
33], underlining the strong bond between marketing activities and re-engineering decisions. The design and implementation of efficient business processes in an intensive marketing environment with high customer expectations, such as the energy sector, are extremely important in achieving the required business performance and sustainability [
34].
Furthermore, re-engineering marketing strategies to adopt IT tools and implement strategic planning can increase firms’ effectiveness, sustainability, and adaptability [
35]. A plethora of potential advantages arise from implementing and adopting customer behavioral data in improving businesses’ digital marketing efficiency as a novel marketing re-engineering process. The authors focus on identifying whether adjusting various customer behavioral web metrics could aid the improvement of key digital marketing efficiency metrics.
1.4. Related Literature and Research Motivations
Adaptable and innovative e-services, based on essential and efficient operations and procedures, are at the center of client engagement and successful preservation. The focus on specialty tasks (including the specialized marketing team) is key to re-engineering thinking, which is motivated by an inter-functional, interdisciplinary viewpoint. Re-engineering emphasizes the importance of flexible, inter-functional organizations that continually grow and restructure to deal with contextual unpredictability and rising market competition [
4]. For SMEs, re-engineering and improving the efficacy of their digital marketing strategy is vital due to their competitive environment and declining market share.
Whilst digital innovations serve an essential role in allowing novelty in service supply operations, assessing their influence on service features and interactions between the service provider and consumer remains highly important [
36]. Firms that have yet to position themselves in a digital world must digitalize their existing services as quickly as feasible. Multiple advantages for businesses’ marketing tool arsenals, particularly for SMEs, provide the capitalization of all types of big data [
37] (such as web analytics), which may aid in trend re-engineering. Establishing techniques and approaches to enhance information systems for services that may aid in the administration and implementation of re-engineering activities connected to service development and operations management has been and will continue to be a continuous process [
38].
Digitalization may assist in transforming a tangible organization into one that includes digital principles, greater interactions, and clients [
39]. Company and construction planning are required to accomplish digital transformation because they augment one another, concealing constraints that could each be accomplished individually, which should be considered in other concepts which only fixate on the institution, facilities, or transformation monitoring [
39].
Throughout the reviewed literature, a research gap can be discerned over the potential advantages of modeling website customers’ behavior in favor of SMEs’ performance. More specifically, more light should be shed on the usage of customers’ behavioral data to re-engineer the marketing activities for SMEs in the energy sector to accomplish the refinement of their digital marketing results. Through modeling the website behavior of their customers (web analytics), energy SMEs could obtain valuable information for adjusting their digital marketing plan and enhancing their efficiency. In this way, they will be able to attract more potential customers and reduce their marketing costs by re-engineering their marketing procedures. The overall theoretical framework is depicted in
Figure 1.
2. Materials and Methods
2.1. Sample Selection and Data Availability
For the analysis to be performed, the authors should define the SMEs that will form the sample for the analysis. Some of the most innovative SMEs in the energy market consist of our study’s sample. Innovation in energy-related services is not common, leading to the projection of a small number of SMEs. So, we collected data from five innovative energy SMEs’ websites [
40] during a period of 90 days of observation. This information, known as website analytics, is a representative factor of customers’ behavior on SMEs’ websites. For this reason, we examined the gathered website analytics as indicators of customers’ digital behavior and elaborated through Fuzzy Cognitive Mapping simulation. Hence, daily values of web analytic metrics form the study’s variables, such as websites’ new and total visits, organic traffic and keywords, bounce rates, traffic sources, average time on site, and pages per visit (
Table 1). The referred website data were collected from online platform applications that collect and provide usage rates and behavioral data of website visitors through payment. For research reasons, the Semrush platform [
41] was selected to collect these data due to its data variety and availability. This dataset will undergo extensive statistical and simulation analysis to produce efficient results to support energy SMEs’ need to re-engineer their core activities for the marketing orientation.
2.2. Research Hypotheses
In this phase of the paper, the main research hypotheses are presented, followed by extensive analysis. Re-engineering core business activities has been proven to be quite beneficial in various sectors. This raises the question of whether utilizing big data in enhancing digital marketing activities and thus re-engineering SMEs’ activities to marketing is beneficial. To assess the efficiency of the marketing re-engineering process, SMEs in the energy sector should capitalize on their customers’ behavior and how they affect important factors of digital marketing activities, such as organic traffic, organic costs, new visits, and website bounce rates. For this purpose, five key research hypotheses are gathered, aiming to point the direction of the study to highlight the marketing re-engineering process by analyzing customers’ website behavior. The research hypotheses are presented below:
The first research hypothesis is based on the concept of whether a marketing re-engineering process could enhance the website efficiency of energy SMEs. We aim to answer if SMEs in the energy sector could attract more visitors to their websites by improving their digital marketing activities via a neat marketing re-engineering process.
H1. “Re-engineer SMEs’ digital marketing activities would impact positively the attraction of new potential customers”.
Next, the second hypothesis relies on the fact that by re-engineering the core processes of marketing, visitors to SMEs’ websites could tend to abandon them less. So, for SMEs in the energy market, knowing that the abandonment rate of their website is affected by the re-engineering of marketing processes could potentially benefit them.
H2. “The tendency of customers to abandon an energy SMEs’ website depends on how well their digital marketing activities are re-engineered”.
The third hypothesis of this paper concerns the costs related to organic marketing campaigns for energy SMEs and how re-engineering their activities could assist. SMEs should acknowledge whether re-engineering their digital marketing activities could help them control and reduce the cost of organic marketing campaigns.
H3. “The re-engineering of digital marketing activities influences the marketing campaign costs of energy SMEs”.
Having analyzed the SME’s website performance through the re-engineering of their digital marketing activities, our focus should be shifted to whether the use of big data represents the variation of re-engineering trends. If SMEs could collect and analyze big data from their websites with ease, their corporate performance could be boosted, given the fact that big data was enabling the promotion of re-engineering trends.
H4. “Big Data can impact the promotion of re-engineering trends”.
In the final hypothesis (H5), the usage of data modeling is examined through its role as a useful Decision Support System (DSS) for re-engineering procedures. To examine this hypothesis, the authors performed the simulation analysis by utilizing a well-known Decision Support System (DSS) and examined the validity of its results, under the appropriate outcomes that would constitute in favor of re-engineering procedures.
H5. “Data modeling could stand up as a Decision Support System (DSS) by aiding re-engineering procedures”.
4. Discussion
At this point of the research, the authors aimed to comprehend whether the elaboration of energy SME customers’ behavior through their website analytic metrics could help indicate any variation in their digital marketing efficiency. The implication of customers’ behavioral data to SMEs has been found to enhance their digital marketing performance since it is capable of explaining the variation of key customer and traffic analytics [
27,
28,
29,
30] such as organic traffic, new visits, etc. For this purpose, the authors deployed regression and correlation analyses followed by the static simulation modeling of FCM, based on the big data collected from five innovative SMEs in the energy sector.
Depending on the results of the regression analyses and based on the significance and explainability the independent variables have with the dependent ones, we can see that customer behavioral analytics, part of big data, can create strong bonds with key performance indicators of websites. So, website analytic metrics (web analytics), as part of big data, are capable of depicting onsite consumers’ behavior due to the representative metrics of any individual website visitor. A successful re-engineering process needs real-time information on a firm’s performance to provide accurate insights for corporate decision-making. Since big data is capable of presenting the direct experience and characteristics of website customers, as shown by the regression results, we can assume that big data can significantly contribute to promoting and distinguishing re-engineering trends, thus verifying our fourth research hypothesis (H4).
Furthermore, from the FCM simulation analysis, a crucial outcome regarding the usage of Decision Support Systems is derived. From the overall process of the FCM scenarios’ simulation, it can be deduced that the contribution of Decision Support Systems (DSS), such as the MentalModeler [
46] platform software, is very important in estimating the efficiency of re-engineering procedures. Re-engineering procedures such as the proposed one for improving the digital marketing efficiency of SMEs through customer website behavioral data. This is due to DSS’ capability of depicting the direct effects of various factors’ variations in key metrics that promote re-engineering assessment. Utilizing and modeling data through Decision Support Systems (DSS), such as the MentalModeler FCM simulation software [
46] in this study, has proven to be a decisive factor in illustrating the direction of re-engineering procedures. Through this assumption, we can verify the paper’s last hypothesis (H5), which means that data modeling can aid in re-engineering procedures by using Decision Support Systems (DSS).
5. Conclusions
After settling the verification of the last hypotheses of the paper, the main results of the study are analyzed next. Throughout this research, the authors’ interest has been shifted to SMEs operating in the energy markets and their potential benefits from analyzing their website customers’ behavior. The competitiveness of the energy SME market makes the utilization of any efficient process that promotes businesses’ sustainability mandatory. Data that indicate website visitors’ and customers’ preferences consists of a valuable tool for enhancing SMEs’ digital marketing performance and, thus, sustainability.
Energy SMEs that capitalize on their website customers’ data and further re-engineer their marketing processes can effectively develop models and simulations that predict the course of their digital marketing performance. Strategic modeling of customers’ behavior optimizes offered services’ resonance and increases the engagement of customers. The results of the paper outline the need for energy SMEs to re-engineer current marketing strategies and focus more on improving digital marketing performance via analyzing website customers’ behavior.
The outcomes of this study highlight the fact that website behavioral data of energy SMEs’ customers covariate with important variables of their digital marketing performance, like organic costs. Moreover, consumer analytic data (average time on site, average pages per visit) and traffic analytic data (direct, social traffic, etc.) tend to affect digital marketing performance variables (organic costs, traffic, new visits, and bounce rate) differently. Since customer behavioral analytics can explain the variance of key digital marketing performance indicators, we discern these data as parameters capable of identifying re-engineering trends for improving SMEs’ digital marketing efficiency and sustainability.
Related studies and research align with our study’s findings in most of the analyzed areas while providing opportunities for further expansion of the topic’s literature. The digitalization of the service process provides a plethora of advantages for SMEs, according to Ingaldi & Klimecka-Tatara [
7]. Based on Akbaba & Altındağ [
51] findings, re-engineering processes on the SMEs’ performance has been found to positively affect the organizational climate of the firms, thus promoting enhanced customer engagement and loyalty. Adoption of Decision Support Systems from SMEs leads to increased business performance, combined with useful intel for corporate decision-making [
52]. Various digital marketing strategies tend to increase website traffic and visibility, as supported by Madlenák et al. [
53], highlighting potential ways for SMEs to enhance digital marketing performance. Moreover, our research comes in terms with Sakas et al. [
54,
55] studies, where businesses’ digital marketing strategies can be predicted by modeling website customers’ behavior. SMEs’ digital marketing strategies can be refined [
56] and further insights regarding key marketing metrics (traffic sources, SEO and SEM strategies, etc.) [
56] could be obtained. These benefits can lead to increased amounts of website traffic and higher customer engagement for energy SMEs [
30,
54,
55], which improves the overall performance of SMEs’ digital marketing activities. Many researchers have utilized contiguous simulation methods (for example, FCM) for extracting the required results [
57,
58,
59,
60].
Apart from the referred results, valuable insights also arise that regard the process of re-engineering SMEs’ marketing procedures. It is highlighted that SMEs in the energy sector can benefit from focusing on their website customers’ behavior. Web analytics that reflect website customers’ behavior can efficiently impact and explain key digital marketing performance indicators, like organic costs, new visits, and bounce rate [
30]. Re-engineering the digital marketing activities of energy SMEs through modeling their customers’ online behavior has been found critical for enhancing SMEs’ digital marketing results and, as a consequence, ensuring their sustainability. Thereby, this paper contributes to the re-engineering science by underlining the importance of focusing on exploiting SMEs’ customer behavioral data to improve digital marketing performance.
Because the paper’s results focused on SMEs in the energy market, some limitations arise regarding the generalization of the study’s conclusions. Energy SMEs can increase the engagement of their customers and their website visibility by modeling their website behavior, but more testing should be conducted in other sectors too. Moreover, apart from examining SMEs in other sectors, multiple types of web analytics could be tested for their impact on digital marketing efficiency, such as website technical factors. Through the implication of other web analytic metrics, additional insights for the re-engineering of SMEs’ marketing.