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OPPORTUNITY MANAGEMENT - MINIMUM SEGMENTS VALUE METHOD BASED ON FUZZY CLUSTERING
Abstract
This paper deals with the use of fuzzy clustering techniques to effectively segment potential customers and existing customers in business opportunity management. Customer segmentation plays a key role in modern businesses, enabling personalized marketing and sales strategies. Traditional clustering methods often wrestle with uncertainty and overlapping customer data characteristics. In this article, we propose the use of fuzzy clustering algorithms to overcome these limitations and provide a more flexible and accurate approach to customer segmentation. The aim of the paper is to suggest a novel method for identification the optimual number of target segments within the business opportunity management. The initial part focuses on the benefits of implementing business opportunity management within the Customer Relationship Management (CRM) system. Implementation of this strategic tool brings a number of key benefits to businesses. The first is centralized data management, which allows to collect and organize all information about customers, potential customers and business opportunities in one place. This increases the enterprise efficiency and minimizes the risk of losing important information. Another benefit is better tracking of potential deals, which enables enterprises to better plan and manage the course of each business opportunity from initial contact with the consumers to its conclusion. The paper concludes with the proposed method to identify the optimal number of target segments of prospect and existing customer withing the opportunity management based on fuzzy clustering.
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Guerola-Navarro, V., Gil-Gomez, H., Oltra-Badenes, R., & Soto-Acosta, P. (2022). Customer relationship management and its impact on entrepreneurial marketing: A literature review. International Entrepreneurship and Management Journal, 1-41.
Kamkankaew, P., Sribenjachot, S., Wongmahatlek, J., Phattarowas, V., & Khumwongpin, S. (2022). Reconsidering the Mystery of Digital Marketing Strategy in the Technological Environment: Opportunities and Challenges in Digital Consumer Behavior. International Journal of Sociologies and Anthropologies Science Reviews, 2(4), 43-60.
Gajanova, L., Nadanyiova, M., & Moravcikova, D. (2019). The use of demographic and psychographic segmentation to creating marketing strategy of brand loyalty. Scientific annals of economics and business, 66(1), 65-84.
Blakeman, R. (2023). Integrated marketing communication: creative strategy from idea to implementation. Rowman & Littlefield.
Frank R.E., Massy W.F., Wind Y., (1972). Market Segmentation, Prentice-Hall, Englewood Cliffs, NJ.
Lilien G., Rangaswamy A., De Bruyn A. (2007). Principles of marketing engineering (2nd ed.). Victoria, B.C.: Trafford Publishing, p. 286.
McDonald M., Dunbar I. (2004). Determining the attractiveness of market segments. In Market segmentation how to do it, how to profit from it (3rd ed.). Amsterdam: Elsevier/Butterworth-Heinemann, p. 490.
Bose C. (2004). Principles of Management of Administration. India: Prentice-Hall, p. 592.
Xu, Y., Liu, X., Cao, X., Huang, C., Liu, E., Qian, S., & Zhang, J. (2021). Artificial intelligence: A powerful paradigm for scientific research. The Innovation, 2(4), 100179.
23. Huang, M. H., & Rust, R. T. (2021). A strategic framework for artificial intelligence in marketing. Journal of the Academy of Marketing Science, 49, 30-50.
Verma, S., Sharma, R., Deb, S., & Maitra, D. (2021). Artificial intelligence in marketing: Systematic review and future research direction. International Journal of Information Management Data Insights, 1(1), 100002.
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