American Journal of Business and Operations Research

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https://doi.org/10.54216/AJBOR

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2692-2967ISSN (Online) 2770-0216ISSN (Print)

Volume 10 , Issue 1 , PP: 16-24, 2023 | Cite this article as | XML | Html | PDF | Full Length Article

Enhancing Customer Relationship Management through Sentiment Analysis and Social Media Data Mining

Esmeralda Kazia 1 * , Bledar Kazia 2

  • 1 Department of Computer and Applied Sciences, Barleti University,Tirana, Albania - (e.kazia@umb.edu.al)
  • 2 Software Engineering Department, Canadian Institute of Technology,Tirana, Albania - (bledi.kazia@cit.edu.al)
  • Doi: https://doi.org/10.54216/AJBOR.100102

    Received: November 18, 2022 Accepted: March 11, 2023
    Abstract

    Customer Relationship Management (CRM) is a crucial aspect of modern business that enables companies to maintain healthy relationships with their customers. In today's digital age, customers interact with companies through multiple channels, including social media, email, and phone. Therefore, analyzing customer feedback and sentiment has become increasingly important in understanding their needs and improving the overall customer experience. To this end, this work proposes a new system that applies deep learning for sentiment analysis in a way that improves the performance of CRM by analyzing customer feedback from various sources, companies can gain valuable insights into customer needs and preferences and identify areas for improvement in their products and services. Then, we present a case study of a company that implemented the proposed system in its CRM strategy. The results showed that our system could improve customer satisfaction and retention rates and enable the company to identify and address customer concerns more efficiently.Our approach can be applied as a powerful tool to enable companies to gain valuable insights into customer needs and preferences, identify areas for improvement in their products and services, and develop targeted marketing campaigns and personalized communication strategies.

    Keywords :

    Sentiment Analysis , Customer Relationship , Management , Social Media Analysis

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    Cite This Article As :
    Kazia, Esmeralda. , Kazia, Bledar. Enhancing Customer Relationship Management through Sentiment Analysis and Social Media Data Mining. American Journal of Business and Operations Research, vol. , no. , 2023, pp. 16-24. DOI: https://doi.org/10.54216/AJBOR.100102
    Kazia, E. Kazia, B. (2023). Enhancing Customer Relationship Management through Sentiment Analysis and Social Media Data Mining. American Journal of Business and Operations Research, (), 16-24. DOI: https://doi.org/10.54216/AJBOR.100102
    Kazia, Esmeralda. Kazia, Bledar. Enhancing Customer Relationship Management through Sentiment Analysis and Social Media Data Mining. American Journal of Business and Operations Research , no. (2023): 16-24. DOI: https://doi.org/10.54216/AJBOR.100102
    Kazia, E. , Kazia, B. (2023) . Enhancing Customer Relationship Management through Sentiment Analysis and Social Media Data Mining. American Journal of Business and Operations Research , () , 16-24 . DOI: https://doi.org/10.54216/AJBOR.100102
    Kazia E. , Kazia B. [2023]. Enhancing Customer Relationship Management through Sentiment Analysis and Social Media Data Mining. American Journal of Business and Operations Research. (): 16-24. DOI: https://doi.org/10.54216/AJBOR.100102
    Kazia, E. Kazia, B. "Enhancing Customer Relationship Management through Sentiment Analysis and Social Media Data Mining," American Journal of Business and Operations Research, vol. , no. , pp. 16-24, 2023. DOI: https://doi.org/10.54216/AJBOR.100102