Big Data Analytics And Predictive Analysis In Enhancing Customer Relationship Management (CRM): A Systematic Review Of Techniques And Tools

Abstract

This systematic review examines the transformative role of big data analytics and predictive techniques in Customer Relationship Management (CRM), focusing on how these advancements enhance customer engagement, satisfaction, and retention strategies. Adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, this review analyzed a final selection of 100 articles, exploring CRM applications such as predictive modeling, real-time data processing, data integration, and Natural Language Processing (NLP). Findings indicate that predictive analytics enables CRM systems to anticipate customer behaviors and personalize interactions, while real-time data processing supports immediate responses to customer needs, essential in high-demand sectors. Data integration helps overcome silos, creating a cohesive customer view that enhances personalized engagement across all touchpoints. NLP applications, including sentiment analysis and chatbots, further improve CRM by fostering empathy and responsiveness in customer interactions. Despite these advancements, challenges related to data privacy and regulatory compliance remain central, necessitating strict data protection and ethical handling practices. This review underscores that while CRM technology is evolving to meet modern demands, effective implementation depends on a balance between technical innovation and adherence to ethical standards in data management, ultimately fostering meaningful and sustainable customer relationships.