TITLE:
Utilizing Social Media Data Analytics to Enhance Banking Services
AUTHORS:
Mohamed Abd El-Hamid Farag Ahmed Askar, Amal Elsayed Aboutabl, Amr Galal
KEYWORDS:
Natural Language Processing (NLP), Sentiment Analysis, Social Banking, Information Retrieval (IR), Social Media Analytics
JOURNAL NAME:
Intelligent Information Management,
Vol.14 No.1,
January
21,
2022
ABSTRACT: The two most important challenges facing banks today are attracting new customers and retaining their existing ones. Research shows that 30 percent of banks cited customer loyalty as their biggest challenges. Thus, given that customer loyalty is completely connected to customer delight. The challenging question is: How do banks achieve customer delight by making every interaction a pleasant experience? In our viewpoint “The key is to stop treating customers as segments and personalize all customer interactions and services which can be achieved by using the latest technological advancements in Big Data Analytics, Artificial Intelligence (AI) and Machine Learning”. With the rapidly increasing usage of social media like Facebook, Twitter, LinkedIn, and Instagram, business organizations are now moving towards adapting this technology to drive business advantages. This research will explore the power of social media and how it can be used by banks to provide an edge over their competitors by providing improved products and services to their customers thereby making their experience easy and responsive. It also proposes a framework for social media analytics and its important components to address all the technical and business aspects of the retail and online banking, however, what customer expects from this medium and what banks offer to them needs to be widely studied and understood.