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The Role of Big Data Analytics in Customer Relationship Management in Retail Banking: A Case Study of GTBank, Enugu State

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Background of the Study:

Big Data Analytics has emerged as a powerful tool in transforming customer relationship management (CRM) in the retail banking sector. In Enugu State, GTBank leverages big data techniques to analyze vast amounts of customer data, enabling the bank to tailor services, predict customer needs, and enhance overall engagement. By utilizing advanced analytical models and machine learning algorithms, GTBank can segment its customer base more accurately and deliver personalized financial products and services that drive satisfaction and loyalty (Ibrahim, 2024). Big data allows for real-time insights into customer behavior, transaction patterns, and service usage, thereby facilitating proactive customer service and targeted marketing campaigns. The integration of big data into CRM systems also helps in identifying potential churn and in devising strategies to retain valuable customers. However, despite its transformative potential, the adoption of big data analytics is not without challenges. Issues related to data quality, integration of disparate data sources, and privacy concerns can hinder effective implementation. Moreover, the complexity of data analytics requires significant investment in technology and skilled personnel, which may be a barrier for some financial institutions. This study explores how GTBank employs big data analytics to enhance customer relationship management, assessing its impact on customer satisfaction, retention, and service innovation. The research draws on both qualitative and quantitative data from 2023 to 2025 to provide a comprehensive overview of the benefits and challenges associated with big data-driven CRM in retail banking (Okafor, 2023).

Statement of the Problem:

Despite significant investments in big data analytics, GTBank in Enugu State faces challenges in fully realizing its potential to improve customer relationship management. Data integration issues, inconsistencies in data quality, and concerns about customer privacy have limited the effectiveness of personalized marketing and service strategies. Additionally, the high cost of implementing advanced analytics tools and the need for specialized skills create barriers to leveraging data insights across all customer segments. As a result, there is often a gap between the intended benefits of data-driven CRM and the actual improvements in customer satisfaction and retention. Furthermore, rapid technological changes and increasing customer expectations make it difficult for the bank to maintain an up-to-date analytics framework that can adapt to evolving market conditions. These challenges hinder the bank’s ability to provide timely and personalized services, potentially reducing competitive advantage and customer loyalty. This study aims to identify the key obstacles in the adoption and effective use of big data analytics for CRM at GTBank, examine their impact on customer outcomes, and propose actionable strategies to overcome these issues. The goal is to enhance the overall effectiveness of CRM initiatives, thereby improving customer satisfaction and long-term loyalty (Chinwe, 2023).

Objectives of the Study:

• To assess the impact of big data analytics on customer relationship management at GTBank.

• To identify challenges in data integration, quality, and privacy affecting CRM.

• To recommend strategies for optimizing big data use in enhancing customer relationships.

Research Questions:

• How does big data analytics influence customer relationship management at GTBank?

• What are the main challenges in implementing big data solutions for CRM?

• What measures can improve data integration and privacy while enhancing CRM?

Research Hypotheses:

• H₁: Effective use of big data analytics significantly improves CRM outcomes.

• H₂: Data quality and integration challenges negatively affect personalized service delivery.

• H₃: Addressing privacy concerns and investing in analytics skills will enhance CRM performance.

Scope and Limitations of the Study:

The study focuses on GTBank’s CRM practices in Enugu State, analyzing internal data systems and customer feedback. Limitations include possible data integration challenges and evolving data privacy regulations.

Definitions of Terms:

• Big Data Analytics: The process of examining large data sets to uncover hidden patterns, correlations, and insights.

• Customer Relationship Management (CRM): Strategies and technologies used by banks to manage customer interactions and improve satisfaction.

• Data Quality: The accuracy, completeness, and reliability of data used for analysis.

 





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