Revolutionising Marketing: Leveraging Blockchain and AI for Impactful Management
DOI:
https://doi.org/10.37591/ecft.v10i3.675Keywords:
Marketing management, Blockchain, Artificial Intelligence, Data, Trust, Secure, Automation, customerAbstract
In today's rapidly evolving business landscape, marketing management faces numerous challenges, including effective decision-making, customer engagement, and data security. Advanced technologies like AI and Blockchain have revolutionized the marketing domain, providing novel solutions to address these challenges. AI plays an essential role in marketing management through its utilization of data analysis, predictive modelling, and automation, providing marketers with the ability to extract valuable insights from extensive data sources, facilitating data-informed decision-making. Furthermore, AI-driven chatbots and virtual assistants enhance customer interactions, making them more efficient and tailored, ultimately enhancing customer engagement and contentment. The combination of AI and marketing automation enhances operational efficiency, streamlines workflows, and enables real-time monitoring and optimization of marketing campaigns. Utilizing blockchain technology in marketing management establishes a decentralized and transparent platform that guarantees data integrity, security, and fosters trust among all parties involved. Through the implementation of blockchain, marketers can safeguard customer data, mitigate the risk of data breaches, and cultivate confidence among their clientele. Blockchain-enabled smart contracts facilitate secure and automated execution of marketing agreements, eliminating intermediaries and reducing transaction costs. Blockchain-based loyalty programs enable seamless and secure reward distribution, enhancing customer loyalty and retention. However, the integration of AI and Blockchain technology presents significant opportunities for businesses to gain a competitive edge in the digital era. By leveraging AI's data analytics and automation capabilities and Blockchain's data integrity and security features, organizations can make informed decisions, personalize marketing campaigns, build customer trust, and enhance operational efficiency. Future research should focus on addressing ethical concerns and technical challenges to maximize the benefits of AI and Blockchain in marketing management.
References
Queiroz MM, Telles R, Bonilla SH. Blockchain and supply chain management integration: a systematic review of the literature. Supply Chain Manag: An International Journal. 2020 Feb 24; 25(2): 241–54.
Gummesson E. Total Relationship Marketing: Marketing Strategy Moving From the 4Ps-Product, Price, Promotion, Place-of Traditional Marketing Management to the 30 Rs. -The Thirty Relationships-of a New Marketing Paradigm. 2nd Edn. Butterworth; 2002.
Sattar AM, Ranjan MK, Singh G. Social, Emotional and Ethical (SEE) Attributes, Which Configures Our Bioinformatics Systems to Activate the Hidden Forces to Shape Human Decisions. In: Nature-Inspired Intelligent Computing Techniques in Bioinformatics. Singapore: Springer Nature Singapore; 2022 Nov 1; 175–202.
Ljepava N. AI-enabled marketing solutions in Marketing Decision making: AI application in different stages of marketing process. TEM J. 2022; 11(3): 1308–15.
Casino F, Dasaklis TK, Patsakis C. A systematic literature review of blockchain-based applications: Current status, classification and open issues. Telemat Inform. 2019 Mar 1; 36: 55–81.
Ouyang L, Yuan Y, Wang FY. Learning markets: An AI collaboration framework based on blockchain and smart contracts. IEEE Internet Things J. 2020 Oct 21; 9(16): 14273–86.
Kong X, Wu Y, Wang H, Xia F. Edge Computing for Internet of Everything: A Survey. IEEE Internet Things J. 2022 Aug 22; 9(23): 23472–85.
Reyes PM, Visich JK, Jaska P. Managing the dynamics of new technologies in the global supply chain. IEEE Eng Manag Rev. 2020 Jan 23; 48(1): 156–62.
Khan S, Iqbal M. AI-Powered Customer Service: Does it Optimize Customer Experience? In 2020 IEEE 8th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). 2020 Jun 4; 590–594.
Sharif MM, Ghodoosi F. The ethics of blockchain in organizations. J Bus Ethics. 2022 Jul; 178(4): 1009–25.
Hemker S, Herrando C, Constantinides E. The transformation of data marketing: how an ethical lens on consumer data collection shapes the future of marketing. Sustainability. 2021 Oct 11; 13(20): 11208.
Hasija A, Esper TL. In artificial intelligence (AI) we trust: A qualitative investigation of AI technology acceptance. J Bus Logist. 2022 Sep; 43(3): 388–412.
Green PE, Carmone FJ, Wachspress DP. On the analysis of qualitative data in marketing research. J Mark Res. 1977 Feb; 14(1): 52–9.
Moutinho L, Huarng KH, editors. Quantitative modelling in marketing and management. 2nd Edn. World Scientific; Singapore; 2015 Nov 6.
Ruiz CA, Kowalkowski C. Market representations in industrial marketing: Could representations influence strategy? Ind Mark Manag. 2014 Sep 1; 43(6): 1026–34.
Woodin J. How to research interculturally and ethically. In: Hua Z, editor. Research methods in intercultural communication: A practical guide. Wiley; New Jersey, United States; 2015 Dec 14; 103–19.
Buhalis D, Lin MS, Leung D. Metaverse as a driver for customer experience and value co-creation: implications for hospitality and tourism management and marketing. Int J Contemp Hosp Manag. 2022 Sep 22; 35(2): 701–16.
Germann F, Lilien GL, Rangaswamy A. Performance implications of deploying marketing analytics. Int J Res Mark. 2013 Jun 1; 30(2): 114–28.
