ANALYSING THE MAJOR DETERMINANTS OF IMPLEMENTING ARTIFICIAL INTELLIGENCE IN ENHANCING CUSTOMER RELATIONSHIP MANAGEMENT IN PRIVATE BANKING COMPANIES
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Abstract
Technology advancements and the broad incorporation of digital practises into corporate operations have contributed significantly to the rapid development of customer relationship management during the last ten years. Because the firm's marketing activities have been using artificial intelligence (AI) to better understand its customers' shifting desires and requirements react more effectively to consumer enquiries, and deepen its connections with its clients, the company has been successful in reaching its goals. Automated responses to customer inquiries used to be monotonous and non-interactive; but, now that AI and other technologies are available, businesses are able to develop customised automation processes to enhance customer interactions and experiences. The abbreviation "Customer Relationship Management" (CRM) refers to a collection of computer software that is used to improve efficiency in dealing with customers and to boost sales.
Artificial Intelligence (AI) is fast revolutionising how consumer enquiries are answered to within customer relationship management by examining wants and requirements, concentrating on developing unique customer interaction, and enhancing customer loyalty. This is being done within the context of Customer Relationship Management (CRM). The use of Artificial Intelligence (AI) in the workplace is fast becoming ubiquitous in the 21st century as an increasing number of businesses see its usefulness. The purpose of this empirical study is to investigate the key facets of AI that have an influence on Customer Relationship Management (CRM). The researchers intend to conduct their quantitative analysis using IBM SPSS, and a comprehensive report of their findings will be produced.
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References
Bipasha Rajkhowa and Aniket Das. (2020). Impact of Artificial Intelligence on Customer Experience. International Journal of Recent Technology and Engineering (IJRTE). 9(2)
Dash, R., McMurtrey, M., Rebman, C., & Kar, U. K. (2019). Application of Artificial Intelligence in Automation of Supply Chain Management. Journal of Strategic Innovation and Sustainability, 14(3)
Davenport, T., Guha, A., Grewal, D., & Bressgott, T. (2019). How artificial intelligence will change the future of marketing. Journal of the Academy of Marketing Science, 24-42
Görgens, M. (2019). How can Artificial Intelligence use big data to form a better customer experience. Computer Science, 1(1) pp 1-12
Hopkinson, P, Perez-Vega, R & Singhal, A (2018). Exploring the Use of AI to manage Customer Relationship. In Proceedings of the 51st Academy of Marketing Conference, 51st Academy of Marketing Conference 2018, Stirling, United Kingdom, 2/07/18
Ivanov, S., & Webster, C. (2017). Adoption of robots, artificial intelligence and service automation by travel, tourism and hospitality companies – A cost-benefit analysis. International Scientific Conference “Contemporary tourism – traditions and innovations, 19- 21 October 2017, Sofia University
Jarrahi, M. H. (2018). Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business Horizons, 577-586
Jarek, K., Mazurek, G. (2019). Marketing and Artificial Intelligence. Central European Business Review, 8(2), 46-55. DoI: 10.18267/j.cebr.213.
Jain.A, Yadav A.K & Y. Shrivastava (2019), Modelling and optimization of different quality characteristics in electric discharge drilling of titanium alloy sheet, Material Today Proceedings, 21, 1680-1684
Jain.A, Pandey.A.K., (2019), Modeling and Optimizing of Different Quality Characteristics in Electrical Discharge Drilling Of Titanium Alloy (Grade-5) Sheet, Material Today Proceedings, 18, 182-191
Jain.A, Pandey.A.K, (2019). Multiple Quality Optimizations in Electrical Discharge Drilling of Mild Steel Sheet. Material Today Proceedings, 8, 7252-7261
Mahdavinejad, M. S., Rezvan, M., Barekatain, M., Adibi, P., Barnaghi, P., & Sheth, A. (2018). Machine Learning for Internet of Things data analysis: A survey. Digital Communications and Networks, 161-175
Martin Adam, Michael Wessel and Alexander Benlian. (2020). AI-based chatbots in customer service and their effects on user compliance. Electron Markets
Syam, N., & Sharma, A. (2018). Waiting for a sales renaissance in the fourth industrial revolution: Machine learning and artificial intelligence in sales research and practice. Industrial Marketing Management
Panwar.V, Sharma D.K, Kumar K.V.P, Jain.A & Thakar.C, (2021). Experimental investigations and optimization of surface roughness in turning of EN 36 alloy steel using response surface methodology and genetic algorithm. Materials Today: Proceedings
Tahir Iqbal. (2021). The Impact of Artificial Intelligence (AI) on CRM and Role of Marketing Managers. University of Gavle, Department of Business and Economics Studies