The Impact of Artificial Intelligence and Social Media on Relationship Marketing for Customer Satisfaction

Introduction

Today, Artificial intelligence and social media have become essential for relationship marketing, concentrating on customer retention and satisfaction rather than sales. This research explored the role of artificial intelligence and social media in strengthening relationship marketing and improving customer satisfaction for SMEs.

Artificial intelligence processes massive amounts of data on customer preferences, providing distinctive opportunities to forecast customer behaviors for competitive advantage (Steinhoff & Palmatier, 2021). Based on these insights, SMEs can develop efficient, personalized, marketing campaigns that improve customer engagement and satisfaction. For instance, fully engaged customers generate 33% higher revenue and sales than actively disengaged customers (Sleiman et al., 2021). Thus, they also spend over 10% more, on average. Therefore, increasing customer retention rates for SMEs by just 5% could increase profits by 25%. Further, attaining one new customer is ten times more costly than retaining an existing one (Hennig-Thurau et al., 2022; Thompson et al., 2018; Iankova et al., 2019). 

Nevertheless, social media have become essential to many people’s lives (Sleiman et al., 2021). These media serve as massive storage for customer data and a vigorous space for interaction between businesses and consumers. The interactive nature of social media encourages a sense of community and trust, necessary elements of strong customer relationships (Hennig-Thurau et al., 2022). Moreover, the viral prospect of social media can strengthen positive customer experiences, improving brand prestige and customer loyalty.

The author used a mixed methodology, a combination of a survey study (30 questions) and interviews (8 respondents with four main questions). Secondary data were collected from a systematic literature review. Based on the analysis of secondary data, primary research was conducted. Moreover, findings highlighted that AI and social media deliver an exceptional opportunity for businesses to transform their relationship marketing approaches. AI can improve social media marketing by automating content creation and targeting the right audience segments. Similarly, AI can analyze social media interactions to measure and determine emerging trends. By identifying and addressing issues promptly, SMEs prevent potential dissatisfaction and strengthen customer relationships. Besides, integrating AI and social media in relationship marketing has challenges such as data privacy and algorithmic bias to maintaining customer trust (Li et al., 2021). 

The relevance of this research is to identify and show the transformative impact of artificial intelligence and social media in relationship marketing, specifically enhancing customer satisfaction. The purpose is to improve relationship marketing by indicating how these technologies can work together. This integration is essential for building long-term loyalty. Overall, this study’s findings are significant for marketing professionals as they underscore the full potential of AI and social media. This allows them to use informed decision-making and develop innovative marketing campaigns.

Literature Review  

Artificial intelligence and social media integration in relationship marketing have received significant attention in recent years. According to Kim and Trail (2011), retaining current customers might cost up to five times as much as acquiring new ones. Furthermore, to be competitive in the new eco-system, businesses must rapidly adopt new technology capabilities (Appel et al., 2020).

The role of AI is not only data analysis and automation (Turban & King, 2012). The objective is to put the customer at the center of marketing strategies (Abeza et al., 2019). The improvement in technology has given marketing practitioners access to digital gadgets, impacting how social media are used in daily life (Achen, 2017). Moreover, according to Agnihotri et al., (2016), algorithms and predictive analytics permit businesses to process massive data to recognize customer behaviors. These insights facilitate highly personalized marketing strategies, relevant to customers (Peters et al., 2013). Besides, social networks make it possible to reach unreachable customers than conventional approaches (Brison et al., 2013). Besides, AI can analyze purchasing patterns to recommend products tailored to individual needs, enhancing the customer experience (Hennig-Thurau et al., 2022). Additionally, AI-powered chatbots provide immediate customer support, resolving queries and issues in real-time and significantly improving customer satisfaction (Li et al., 2021).

To cultivate loyal consumer connections, marketers must shift from traditional methods to contemporary marketing techniques (Peppers, 2009). As the name suggests, relationship marketing is about building good relationships with customers; therefore, before practicing relationship marketing, businesses should consider the unique customer service problems they face (Bataineh et al., 2015). Relationship marketing evolves with time and changing customer preferences (Young & Rossmann, 2015). Through energetic activity, relationship marketing strengthens the bonds between consumers and markets (Peppers & Rogers, 2011). Additionally, relationship management (RM) facilitates collaboration between organizations and their stakeholders (Thompson et al., 2018). RM’s primary objective is to retain clients by ensuring that consumers and companies are satisfied (Felix et al., 2017). Long-term customer satisfaction requires constant communication, interaction, and a two-way discussion between businesses and customers (Williams & Chinn, 2010). Relationship Marketing manages the interactive partnership between a business and its stakeholders (Ittisa, 2020). Communication and interaction are utilized to maintain the working connection, maintain its strength, and continue to provide value to the primary product (Reinikainen et al., 2020). The relationship marketing strategy is implemented so the firm can get closer and learn more about its consumers, resulting in a shared understanding of where the firm can assist its clients (Coen, 2016). The approach contributes to the businesses’ aims to become closer to clients, provide them with better service, retain more customers, boost customer loyalty, forge enduring relationships, reduce marketing expenses, and secure long-term profitability (Gummesson, 2017).

Modern customers have more options than ever (Bataineh et al., 2015). The development of social media during the past ten years has altered the scope and pace of communication and engagement between individuals and organizations globally (Filo et al., 2015). Social media platforms have become indispensable in contemporary marketing strategies due to their vast user bases and interactive capabilities (Aka et al., 2016). They serve as critical channels for customer engagement, enabling businesses to communicate directly with their audience (Thaichon et al., 2019). It would be wise to take advantage of opportunities to maintain contact with current and potential prospects (Iankova et al., 2019). Due to the nature of social media, businesses must communicate with clients differently than they would in a broadcasting-based market (Misirlis & Vlachopoulou, 2018). The real-time nature of social media allows maintaining effective customer relationships (Payne & Frow, 2017). Moreover, social media develop community marketing which increases a sense of loyalty and belonging (Sleiman et al., 2021). SMEs can reach specific demographics more effectively through targeted advertising and personalized content (Charoensukmongkol & Sasatanun, 2017).

Customers want businesses to respond promptly (Alalwan et al., 2017). Customers increasingly believe that social media are the simplest method to receive assistance (Stebner et al., 2017). Therefore, the synergy between AI and social media shows the benefits of each technology in relationship marketing (Boateng, 2018). AI optimizes social media strategies by automating content creation and identifying key audience segments (Gilboa et al., 2019). For instance, AI can analyze user interactions to tailor social media content and engage followers (Steinhoff et al., 2019). This level of personalization leads to higher engagement rates and effective customer relationships (Hall & Peszko, 2016).

Furthermore, AI enhances social media analytics by deeper insights into customer sentiments (Tiago & Veríssimo, 2014). Determining customer retention may be difficult, but a robust program may go a long way (Tuten & Solomon, 2017). AI-powered analysis uses vast social media data to assess public opinion about a brand or product (Christopher et al., 2013). This enables businesses to respond proactively to negative feedback and capitalize on positive sentiment leading to effective customer engagement (Csordás et al., 2014). Understanding customer opinion in real time permits SMEs to alter their campaigns more effectively.

Using social media and customer relationship management together facilitates the resolution of technical issues and answering inquiries (Gilboa et al., 2019). Besides, empirical studies and case analyses demonstrate the effectiveness of combining AI and social media in relationship marketing across various industries. According to Abeza et al. (2019), RM manages the interactive partnership between a business and its stakeholders.  Moreover, as a result, customer service will improve, and more marketing data will be extracted from social media (Salesforce, 2022). According to Baran and Zerres (2010), using technology is crucial in relationship marketing. With the Internet, companies can now collect, store, analyze, and utilize vast amounts of client information (Hambrick & Kang, 2015). As a result, customers loyal to a business are rewarded with personalized advertising, discounts, and expedited service (Bruhn, 2015). For instance, retail companies like [Amazon] utilize AI-driven recommendation systems alongside social media campaigns to boost sales and customer engagement (Csordás et al., 2014). In the hospitality sector, [Marriott] uses AI to personalize guest experiences, while social media platforms like [Instagram] are employed to maintain ongoing customer interactions. These practices improve customer satisfaction and increase brand loyalty and repeat business (Appel et al., 2020).

Due to the expansion of information technology and the Internet over the past two decades, there has been more openness, and the purchasing power of customers is constantly rising (Sousa & Alves, 2019). Customers demand more from businesses than mass-produced items; they want to be delighted and pleased (Appel et al., 2020). However, it is essential to note that adopting AI and social media in relationship marketing has challenges (Tuten & Solomon, 2017).  Data privacy concerns are paramount, as the use of personal data for targeted marketing must comply with regulations and ethical standards (Steinhoff & Palmatier, 2021). Technology and fresh ideas are constantly evolving. Search engine optimization is the key to getting things done in the Internet age. In relationship marketing, blogs, videos, social networks, etc., are increasingly utilized (Steinhoff & Palmatier, 2021). These interactive media enable companies to maintain contact with clients throughout time (Reinikainen et al., 2020). Besides, algorithmic biases in AI systems can have unintentional consequences concerning the fairness and effectiveness of marketing efforts. It is necessary to keep transparency in how data are used and how AI-driven decisions are made to maintain customer trust (Csordás et al., 2014).

According to Jones et al., (2015), the importance of consumer interactions and experiences will increase. Moreover, Hays et al., (2013) stated that engaging your customers through social media is possible in many ways. Whether posting your latest sales or answering their questions, your current, past, and potential customers can easily reach out to you (Appel et al., 2020).

Finally, the literature review suggests that AI and social media are essential in relationship marketing. This integration proposes effective customer engagement and satisfaction benefits. As technology continues to grow, AI and social media in relationship marketing are endless, promising even more modern ways to improve customer satisfaction.

Research Methodology

This research aimed to explore the role of artificial intelligence and social media in strengthening relationship marketing and improving customer satisfaction for SMEs. The objective was to identify the influences of relationship marketing practices on customer satisfaction, resulting in increased customer retention, enhanced by artificial intelligence. Consequently, the author formulated the hypothesis:

• H₀: Integrating artificial intelligence and social media significantly impacts relationship marketing effectiveness and customer satisfaction in SMEs.
• H₁: Integrating artificial intelligence and social media does not significantly impact on relationship marketing effectiveness and customer satisfaction in SMEs.

The author used mixed methods to explore the research problem. The research articles consist of three main areas such as a literature review, a survey study, and expert interviews. Lastly, smart data were synthesized, and conclusions were drawn.

At first, a systematic literature review was conducted. This process included a search and analysis of existing literature on artificial intelligence, social media, relationship marketing, customer satisfaction and retention, brand loyalty, and more. The author used SCOPUS, WoS, Google Scholar, and EBSCO databases. Moreover, the search used inclusion and exclusion criteria to screen relevant research works, articles, and reports. To continue, the data were screened on keywords, titles, abstracts, and full papers to select relevant materials and provide comprehensive search terms carefully. Lastly, based on the literature review, the author identified patterns, gaps, and key findings, which permitted a better understanding and emphasized the research problem and the construction of a survey study.

The author developed primary research that consisted of a survey study and expert interviews. This survey comprised 30 questions to capture quantitative data on artificial intelligence and social media in relationship marketing. The questions included demographic information, customer attitudes, experiences, and perceptions, all of which are customer satisfaction characteristics. A combination of multiple-choice and Likert scales offered extensive data collection.

The author used snowball and convenient sampling methods. To maximize response rates, the questionnaire was sent out on LinkedIn, Facebook, WhatsApp, and Instagram, and the survey was distributed via Google Forms. The survey data was subsequently analyzed to determine trends, correlations, and critical findings. One hundred fifty-eight marketing professionals completed the survey. 

Following the survey, the author conducted eight in-depth interviews with marketing experts. These experts were selected from 28 candidates based on their extensive knowledge, experience, and contributions to artificial intelligence, social media marketing, and relationship marketing. The interviews provided qualitative insights that improved the overall data analysis. The interviews were semi-structured, allowing respondents to concentrate on predefined topics. A set of guiding questions was prepared and sent to respondents beforehand. All respondents chose Zoom. Interviews lasted between 28 – 30 minutes. The Zoom interviews were transcribed. Thematic analysis was used to identify recurring themes and patterns. After this process, the transcribed interview was sent to the respondents for the final review. All respondents agreed on the information to be used in the research. The interview results provided a richer understanding of the research problem.

Research Findings

This research, backed by the insights of 158 respondents with diverse marketing backgrounds, explored the role of artificial intelligence and social media in strengthening relationship marketing and enhancing customer satisfaction for SMEs. The survey was distributed to professionals with expertise in various marketing professions through social media platforms using convenience and snowball sampling methods. Figure 1 illustrates the demographics of the respondents. The majority of the respondents, 32.3%, were represented by age categories 23-27, representing early professionals. Gender was equally distributed. Moreover, 19.6% of the respondents represented the USA, 17.7% from Lithuania, 15.2 % from Latia, and so on. Lastly, others were represented by 7 different countries (Malta, Italy, Spain, France, Romania, Poland, and Bulgaria) and they were grouped. 

Fig 1. Demographics (Created by the author)

Furthermore, figure 2 illustrates the professional experience and years of experience of the respondents: 18.9% in digital marketing, 23.8% in content marketing, 17% in marketing management, 20.2% in strategic management, 1.6% in SEO, 17.5% in marketing analytics and other was 1.3%. It must be underlined that the majority of the respondents were employed, which adds additional value to the research, as the feedback gained is relevant and practical. Additionally, 29.7% have 3 to 5 years of experience in the marketing field, and 5.96% have more than 10 years. It could be concluded that respondents were well-positioned to offer valuable insights exploring artificial intelligence and social media in relationship marketing, leading the customer satisfaction.

Fig 2. Professional Experience (years) (Created by the Author)

Figure 3 illustrates and discusses the role of AI and social media in customer engagement and satisfaction. Social media and AI enable data to be gathered from the audience, which are later transformed into insight, providing responsive customer service. Figure 3 illustrates that 75.5% were aware of the benefits of social media marketing, artificial intelligence, and relationship management; 7.5% were not, while 17% were slightly aware. It indicates that the audience is well aware of the benefits of social media.

Respondents had to respond to AI in customer services and whether it encourages engagement. So, Figure 3 illustrates the following: 47.8% of the respondents significantly agreed, 30.2% entirely agreed, 13.2% somewhat agreed, 6.9% slightly agreed, and 1.9% were not satisfied. This indicates that marketing experts feel strongly about digital technologies and AI’s role in customer service, especially when artificial intelligence is increasingly integrated into various business processes.  Furthermore, social media engagement is a critical structure for actions that reflect and measure how the audience interacts with the content created and proposed by the businesses. Figure 3 illustrates the following: 40.3% of them highly agreed that the customers should engage in an informal and ongoing way, 29.6% quietly agreed, 21.4% somewhat agreed with the statement, 5.6% slightly agreed with the statement, and 3.1% not all agreed with the statement.

The customer service representative’s role is complex. Moreover, customer service representatives provide and act as primary problem solutions’ individuals who prioritize customer needs in every single process of business operations. Figure 3 illustrates the following: 34.2% were delighted, 33.5% were quite satisfied, 22.3% were somewhat satisfied, 6.3% were slightly satisfied, and 3.7% did not agree.  Moreover, in modern practice, user experience is vital when discussing the development of various engagement platforms with customers. 5.2 % of the respondents were delighted, 13.9% were quite satisfied, 21.5% were somewhat satisfied, 33.5% slightly agreed, and 25.9% were unsatisfied. This indicates that social media customer service assists businesses in meeting customer issues quickly and responding accordingly. 

Fig 3. AI and Social Media in Relationship Marketing (Created by the Author)

Direct response marketing strategizes on encouraging immediate responses from potential customers. From the results, most respondents highlight the importance of direct response marketing strategies versus sales transactions. Sales transactions are an essential part of customer retention and satisfaction. However, the majority of the work to attract, acquire, and maintain is still heavily on marketing planning. Additionally, to be efficient in social media customer services, it is advisable to respond quickly, as today’s customers need real-time information when making real-time decisions.

The goal of social media customer services is to resolve various questions or concerns that emerge at the points of purchase or post-purchase. Social customer support is critical and efficient, allowing customers to reach and communicate with businesses. Figure 5 indicates the following. It is clear from the above survey that 30.7% of the total respondents were pleased with the social media marketing service support, 35% were quite satisfied, 21.7% were somewhat satisfied with it, 8.2% were slightly satisfied, and 4.4% were not at all satisfied with it.

Whether believe it or not, in today’s competitive environment, social media and artificial intelligence enhance customer relationship management and allow businesses to manage their retention and customer satisfaction numbers better. However, it needs to be clarified if this leads to frequent use of social media applications, especially for online purchases to help retention. 40.6% entirely agreed with it, 20% somewhat agreed with it, 7.1% slightly agreed with it, and the remaining respondents disagreed. Nevertheless, relationship marketing aims to create customer retention, satisfaction, and lifetime customer value. The goal is to focus on current customers to boost sales and relationships. Today, if brands are willing to share their imperfections, customers will trust them; however, it also must be noted that this is not the only case. 27.6% of the respondents believe that social media platforms have enhanced engaging tactics and tools to satisfy customers, 47.1% comparable, 6.4% felt poor, and 9% were unsure and needed more clarification. Authenticity on social media is about being dependable or reliable. It is not only an individual perspective, but businesses also must be valid and act the way they present themselves to the customers. 

Fig 5. Social media and AI for relationship marketing (Satisfaction and retention)

 (Developed by the Author)

Interview

The interview was conducted among eight respondents to explore the influence of social media and artificial intelligence on relationship marketing. Of eight interviewees, only two were female, and the others were male. The majority of the respondents represent the age group 25-40, followed by 18-28. All interviewees represented the professional field related to customer relationships and artificial intelligence on social media platforms. The majority of the respondents have earned a graduate degree. Lastly, the interviewees had, on average, seven years of professional experience in marketing, which is hugely significant as it indicated more validity when analyzing interview results. The respondents were asked a series of thought-provoking questions to explore the relationship between social media, artificial intelligence, and relationship marketing.

 Tab 1. Survey Questions

All respondents provided positive reviews for question 1. Interviewee 4 highlighted that social media facilitate a dynamic two-way conversation between organizations and consumers, which enhances relationship marketing. This opinion was supported by interviewees 1, 2, and 3. Additionally, interviewee 6 noted that social media enable companies to offer personalized interactions, enhancing customer experience and positive impacts.

Interviewee 2 highlighted that social media networks enhance relationship marketing by promoting communication benefits. Similarly, interviewee 6 mentioned that daily social media usage makes purchasing more accessible for consumers. Interviewee 8 concluded that a business can create close relationships with suppliers, customers, and other partners by experiencing in the value chain. Building a strong value chain is crucial for relationship marketing as it enhances the opportunity to engage with more customers.

The interviewees indicated the positive impact of artificial intelligence on relationship marketing. Interviewee 2 mentioned the decreased advertising costs associated with social media. Other interviewees examined benefits such as brand loyalty, customer engagement, and other positive outcomes from AI on relationship marketing.

Most interviewees responded positively to the role of social media and AI in achieving impressive customer satisfaction. Some highlighted that social media and AI help with customer engagement and customer satisfaction. Interviewees 2, 3, and 6 noted that social media enhance customer loyalty and improve relationships. Interviewee 5 noted that AI and social media positively influence customer buying behavior. 

The interviewees consistently emphasized the importance of relationship marketing in building and developing customer satisfaction. They agreed that relationship marketing is crucial in building a loyal customer base. The interviewees also noted that relationship marketing has evolved with modern innovative communication methods. Overall, the interviewees revealed a positive impact of social media and artificial intelligence on relationship marketing, leading to customer satisfaction.

Discussions  

This research explored the role of artificial intelligence and social media in strengthening relationship marketing and improving customer satisfaction for SMEs.

• H₀: Integrating artificial intelligence and social media significantly impacts relationship marketing and customer satisfaction in SMEs.
• H₁: Integrating artificial intelligence and social media does not significantly impact relationship marketing and customer satisfaction in SMEs.

By testing the impact of integrating AI and social media in relationship marketing and customer satisfaction for SMEs, it was determined that there is a significant effect, therefore accepting H₀ and rejecting H_1. Figure 6 highlights the data collected and analyzed. It was revealed that social media serve as a valuable instrument for marketers and managers, contributing a cost-effective means to gather market data, address customer issues, identify new revenue streams, and improve business offerings based on customer feedback. Moreover, the research focused on understanding relationship marketing dynamics and evaluating social media’s role in customer satisfaction. The findings highlighted that relationship marketing, reinforced by vigorous engagement and strategic understanding between businesses and customers, is decisive for nurturing customer connections.

Furthermore, this research explored explicit research questions concerning social media’s role in relationship marketing. It was detected that the extensive adoption of mobile technology has reformed people’s social media usage behaviors, with most recognizing its benefits. In addition, leveraging social media influencers and nurturing informal yet continuous engagement were emphasized as functional and effective strategies in relationship marketing.

Fig 6. Synthesizing research findings (Developed by the author)

Further, it was found that artificial intelligence is fundamental in optimizing social media strategies for improved customer satisfaction. By using AI-powered analytics, businesses can obtain strategic insights into customer behaviors, and preferences. Machine learning algorithms can examine massive social media data to recognize patterns and trends, enabling marketers to modify their campaigns.

Fig 7. Social Media and AI Impact on Relationships Marketing (Developed by the author)

Nevertheless, AI-driven personalization improves the significance and effectiveness of marketing efforts on social media platforms (Figure 7). By analyzing user interactions and past behaviors, AI algorithms can develop personalized content and approvals tailored to individual customer preferences which is fundamental for relationship marketing. This level of customization not only improves the overall customer experience but also raises the probability of customer retention.

Additionally, AI-powered ad targeting guarantees that promotional content influences the most appropriate segments, maximizing advertising ROI and driving engagement. It can be concluded that establishing dedicated social media channels for customer service, monitoring relevant keywords, and deploying chatbots are recommended for SMEs. Moreover, targeted campaigns to build positive community relationships enable live engagement on select social media platforms increasing customer satisfaction and relationship management efforts.  Furthermore, integrating artificial intelligence technologies allows businesses to leverage social media platforms more efficiently for customer satisfaction and improved marketing results. By accepting these recommendations, marketers and SME owners can control the power of social media to enhance customer experiences and drive business growth.

Conclusion

This research explored the role of artificial intelligence and social media in strengthening relationship marketing and improving customer satisfaction for SMEs. Statistical testing determined a significant effect, so, H0 is accepted, and H1 is rejected.

It was determined that relationship marketing creates value, markets to the customers, and encourages customer engagement. Therefore, enhancing it with AI and social media could deliver higher retention and satisfaction. With relationship marketing, the objective is to create valued customers based on experience, not on price.

Furthermore, based on the analyzed data, it was explored that AI-powered personalization increases customer satisfaction. It creates an ideal opportunity for receiving feedback and provides a competitive advantage. Besides, effective social media engagement strategies strengthen customer relationships. This allows SMEs to efficiently create and develop their marketing campaigns for their target audience. Moreover, integrated AI and social media strategies increase customer satisfaction, retention, and loyalty.

Lastly, findings emphasized that AI and social media provide a superior opportunity for SMEs to alter their relationship marketing approaches and become competitive. Besides, AI can improve social media marketing by automating content creation, optimizing posting schedules, and targeting the right audience segments.

Limitations to the research

In the research, there are some limitations.  First, convenience sampling may present selection bias, as respondents were primarily selected based on their availability and willingness to participate, potentially skewing the sample toward specific demographics or viewpoints. Second, snowball sampling might rely on the initial participants’ networks, limiting reach to the broader population. Finally, integrating data from different methodologies posed challenges, slightly affecting the reliability of the findings.

Future research

These limitations indicate that the research’s conclusions should be interpreted cautiously, emphasizing the need for further research with more rigorous sampling methods.

Acknowledgment

The research article was prepared based on collaborative research with my master’s student, Nithin Gopalakrishnan Nair. I acted as Nithin’s Master’s Study supervisor from 2021 to 2022. 

References

• Abeza, G., O’Reilly, N., & Seguin, B. (2019). Social media in relationship marketing: The perspective of professional sport managers in the MLB, NBA, NFL, and NHL. Communication & Sport, 7(1), 80-109.
• Achen, R. M. (2017). Measuring social media marketing: Moving towards a relationship-marketing approach. Managing Sport and Leisure, 22(1), 33-53.
• Agnihotri, R., Dingus, R., Hu, M. Y., & Krush, M. T. (2016). Social media: Influencing customer satisfaction in B2B sales. Industrial marketing management, 53, 172-180.
• Aka, D., Kehinde, O., & Ogunnaike, O. (2016). Relationship marketing and customer satisfaction: A conceptual perspective. Binus Business Review, 7(2), 185-190.
• Alalwan, A. A., Rana, N. P., Dwivedi, Y. K., & Algharabat, R. (2017). Social media in marketing: A review and analysis of the existing literature. Telematics and Informatics, 34(7), 1177-1190.
• Appel, G., Grewal, L., Hadi, R., & Stephen, A. T. (2020). The future of social media in marketing. Journal of the Academy of Marketing Science, 48(1), 79-95.
• Baran, R., & Zerres, M. (2010). Customer relationship management.
• Bataineh, A. Q., Al-Abdallah, G. M., Salhab, H. A., & Shoter, A. M. (2015). The effect of relationship marketing on customer retention in the Jordanian’s pharmaceutical sector. International Journal of Business and management, 10(3), 117-131.
• Boateng, S. L. (2018). Online relationship marketing and customer loyalty: a signaling theory perspective. International Journal of Bank Marketing.
• Brison, N. T., Baker III, T. A., & Byon, K. K. (2013). Tweets and crumpets: Examining UK and US regulation of athlete endorsements and social media marketing.  Legal Aspects Sport, 23, 55.
• Bruhn, M. (2015). Relationship marketing. München: Vahlen.
• Charoensukmongkol, P., & Sasatanun, P. (2017). Social media use for CRM and business performance satisfaction: The moderating roles of social skills and social media sales intensity. Asia Pacific Management Review, 22(1), 25-34.
• Christopher, M., Payne, A., & Ballantyne, D. (2013). Relationship marketing. Routledge.
• Coen, B., (2016). Using Social Media for Customer Relationship Management. Retrieved from https://www.socialmediatoday.com/social-business/using-social-media-customer-relationship-management last accessed on 20th July 2022.
• Csordás, T., Markos-Kujbus, É., & Gáti, M. (2014). The attributes of social media as a strategic marketing communication tool. Journalism and Mass Communication, 4(1), 48-71.
• Felix, R., Rauschnabel, P. A., & Hinsch, C. (2017). Elements of strategic social media marketing: A holistic framework. Journal of Business Research, 70, 118-126.
• Filo, K., Lock, D., & Karg, A. (2015). Sport and social media research: A review. Sport management review, 18(2), 166-181.
• Gilboa, S., Seger-Guttmann, T., & Mimran, O. (2019). The unique role of relationship marketing in small businesses’ customer experience. Journal of Retailing and Consumer Services, 51, 152-164.
• Gummesson, E. (2017). From relationship marketing to total relationship marketing and beyond. Journal of services marketing.
• Hall, H., & Peszko, K. (2016). Social media as a relationship marketing tool of modern university. Marketing i Zarządzanie, 46, 41-56.
• Hambrick, M. E., & Kang, S. J. (2015). Pin it: Exploring how professional sports organizations use Pinterest as a communications and relationship-marketing tool. Communication & Sport, 3(4), 434-457.
• Hays, S., Page, S. J., & Buhalis, D. (2013). Social media as a destination marketing tool: its use by national tourism organisations. Current issues in Tourism, 16(3), 211-239.
• Hennig-Thurau, T., Gwinner, K. P., & Gremler, D. D. (2002). Understanding relationship marketing outcomes: An integration of relational benefits and relationship quality. Journal of service research, 4(3), 230-247.
• Iankova, S., Davies, I., Archer-Brown, C., Marder, B., & Yau, A. (2019). A comparison of social media marketing between B2B, B2C and mixed business models. Industrial Marketing Management, 81, 169-179.
• Ittisa, (2020). Social Media Marketing: The Complete Guide for Everyone 2020. Retrieved from https://ittisa.com/social-media-marketing-the-complete-guide-for-everyone-2020/ last accessed on 11th August 2022.
• Jones, N., Borgman, R., & Ulusoy, E. (2015). Impact of social media on small businesses. Journal of small business and enterprise development.
• Kim, Y. K., & Trail, G. (2011). A conceptual framework for understanding relationships between sport consumers and sport organizations: A relationship quality approach. Journal of sport management, 25(1).
• Kim, Y. K., Trail, G. T., Woo, B., Zhang, J. (2011). Sports consumer-team relationship quality: Development and psychometric evaluation of a scale. International Journal of Sports Marketing and Sponsorship, 12, 57–74.
• Li, F., Larimo, J., & Leonidou, L. C. (2021). Social media marketing strategy: definition, conceptualization, taxonomy, validation, and future agenda. Journal of the Academy of Marketing Science, 49(1), 51-70.
• Misirlis, N., & Vlachopoulou, M. (2018). Social media metrics and analytics in marketing–S3M: A mapping literature review. International Journal of Information Management, 38(1), 270-276.
• Payne, A., & Frow, P. (2017). Relationship marketing: looking backwards towards the future. Journal of services marketing.
• Peppers, D., & Rogers, M. (2011). Managing Customer Relationships: A Strategic Framework, Wiley. Hoboken, NJ.
• Peters, K., Chen, Y., Kaplan, A. M., Ognibeni, B., & Pauwels, K. (2013). Social media metrics—A framework and guidelines for managing social media. Journal of interactive marketing, 27(4), 281-298.
• Reinikainen, H., Kari, J. T., & Luoma-Aho, V. (2020). Generation Z and organizational listening on social media. Media and Communication, 8(2), 185-196.
• Salesforce, (2022). What is Social CRM? Retrieved from https://www.salesforce.com/eu/learning-centre/crm/social-crm/ last accessed on 20th July 2022.
• Sleiman, K. A. A., Cai, X., Lan, J., Lei, H., & Liu, R. (2021). Relationship Marketing and Information Technology’s Impact on Customer Satisfaction and Commitment. Open Journal of Business and Management, 9(03), 1030.
• Sousa, B. M., & Alves, G. M. (2019). The role of relationship marketing in behavioural intentions of medical tourism services and guest experiences. Journal of Hospitality and Tourism Insights.
• Stebner, S., Baker, L. M., Peterson, H. H., & Boyer, C. R. (2017). Marketing with more: An in-depth look at relationship marketing with new media in the green industry. Journal of Applied Communications, 7-19.
• Steinhoff, L., & Palmatier, R. W. (2021). Commentary: Opportunities and challenges of technology in relationship marketing. Australasian Marketing Journal, 29(2), 111-117.
• Steinhoff, L., Arli, D., Weaven, S., & Kozlenkova, I. V. (2019). Online relationship marketing. Journal of the Academy of marketing science, 47(3), 369-393.
• Thaichon, P., Liyanaarachchi, G., Quach, S., Weaven, S., & Bu, Y. (2019). Online relationship marketing: evolution and theoretical insights into online relationship marketing. Marketing Intelligence & Planning.
• Thompson, A. J., Martin, A. J., Gee, S., & Geurin, A. N. (2018). Building brand and fan relationships through social media. Sport, Business and Management: An International Journal.
• Tiago, M. T. P. M. B., & Veríssimo, J. M. C. (2014). Digital marketing and social media: Why bother?. Business horizons, 57(6), 703-708.
• Tuten, T. L., & Solomon, M. R. (2017). Social media marketing. Sage.
• Williams, J., & Chinn, S. J. (2010). Meeting relationship-marketing goals through social media: A conceptual model for sport marketers. International Journal of Sport Communication, 3(4).
• Young, S. W. H., & Rossmann, D. (young). Building library community through social media. Infoation technology and libraries, 34(1), 20-37.