An examination of ATM service quality improvement on customer retention in banking: a case study of AB Microfinance Bank
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Background of the Study
ATMs are a critical channel through which customers interact with banks, and their service quality directly influences customer retention. AB Microfinance Bank has undertaken various initiatives to improve ATM service quality, including hardware upgrades, software enhancements, and the implementation of real-time monitoring systems (Olayinka, 2023). These improvements aim to reduce downtime, enhance transaction accuracy, and provide a seamless customer experience. By ensuring that ATMs function reliably, the bank seeks to maintain high levels of customer satisfaction, thereby fostering long-term customer loyalty. Recent literature emphasizes that superior ATM service quality is associated with higher customer retention, as it reduces inconvenience and builds trust in the bank’s operational capabilities (Ikechukwu, 2024).
The bank’s strategy includes a robust maintenance schedule, proactive repair protocols, and integration of predictive analytics to anticipate potential failures. These measures are essential in a competitive market where customers expect 24/7 service availability. However, challenges such as regional disparities in network infrastructure and integration issues with older machines can lead to inconsistent service quality. This study aims to examine the impact of improved ATM service quality on customer retention at AB Microfinance Bank by analyzing transaction performance data, maintenance records, and customer feedback. The goal is to determine the extent to which service quality improvements translate into enhanced customer loyalty and to identify the operational challenges that must be addressed.
Statement of the Problem
Despite improvements in ATM service quality, AB Microfinance Bank still experiences challenges in achieving consistent customer retention. A major problem is that service quality varies significantly across different locations, with some ATMs operating flawlessly while others suffer from frequent outages and errors (Emeka, 2023). This inconsistency can lead to customer frustration and drive them to competitors. Additionally, integration issues between upgraded ATMs and legacy systems sometimes result in delays in addressing technical issues, thereby prolonging downtime. These operational inefficiencies not only affect customer satisfaction but also increase the cost of maintenance and reduce overall retention rates. The study seeks to determine whether current efforts to improve ATM service quality are effective in enhancing customer retention and to identify the factors that contribute to service variability across the bank’s network.
Objectives of the Study
• To assess the impact of improved ATM service quality on customer retention at AB Microfinance Bank.
• To identify operational challenges affecting ATM performance consistency.
• To recommend strategies for optimizing ATM service quality to boost customer loyalty.
Research Questions
• How does ATM service quality improvement affect customer retention?
• What are the primary operational challenges causing service variability?
• How can AB Microfinance Bank optimize ATM performance to improve retention?
Research Hypotheses
• H1: Enhanced ATM service quality significantly increases customer retention.
• H2: Operational inconsistencies negatively impact overall customer loyalty.
• H3: Streamlined maintenance and integration processes improve service quality and retention.
Scope and Limitations of the Study
This study examines ATM service quality improvements at AB Microfinance Bank over the past two years, using performance logs, maintenance reports, and customer surveys. Limitations include regional infrastructure differences and external network issues.
Definitions of Terms
• ATM Service Quality: The reliability, speed, and accuracy with which ATMs process transactions.
• Customer Retention: The ability of a bank to retain its customers over time.
• Predictive Analytics: The use of data analysis to forecast potential equipment failures.
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