Optimizing Customer Insights with Machine Learning Algorithms: An AI-Based Approach to CRM Systems

Authors

  • Chitrapradha Ganesan

Keywords:

Machine Learning, Customer Insights, CRM Integration, Predictive Analytics.

Abstract

Machine learning (ML) algorithms can take customer insights to next level, and is an innovative way to implement AI in Customer Relationship Management (CRM) system like Salesforce CRM, Oracle Siebel. By using advanced machine learning methods, companies can find useful trends in large amounts of data, like how customers connect with them, what they buy, and their feedback.  This data is used to create more appropriate customer segmentation, personalized marketing, predictive analytics for sales and retention, and more. From sentiment analysis, churn prediction, up to performance forecasting, the ML models can be utilized to enhance the CRM features. As a result, customer engagement, loyalty and revenue increase. Additionally, merging AI and CRM enhances operational efficiency — it automates redundant tasks, reduces manual intervention, and provides real-time analytics to facilitate decision-making. As organizations continue to become more obsessed with enhancing customer experience, we expect an infusion of AI into CRM platforms to be a key driver of data-driven and experience-rich endeavors that provide sustainable competitiveness.

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Published

29.12.2022

How to Cite

Chitrapradha Ganesan. (2022). Optimizing Customer Insights with Machine Learning Algorithms: An AI-Based Approach to CRM Systems. International Journal of Intelligent Systems and Applications in Engineering, 10(3s), 361–370. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/7544

Issue

Vol. 10 No. 3s (2022)

Section

Research Article

License

Creative Commons License

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