Customer Segmentation in Banking: Identifying Profitable Customer Groups in Cameroon
DOI:
https://doi.org/10.47941/jms.3569Keywords:
Banking Industry, Customer Segmentation, Customer Profitability, CameroonAbstract
Purpose: This study aims to identify the factors that influence customer profitability in the Cameroonian banking industry and to develop a customer segmentation framework that can be used by banks to identify profitable customer groups. The study argues that customer profitability can be predicted by analysing behavioural and financial factors, while bank type and customer loyalty have no significant impact.
Methodology: Using a quantitative research approach, this study collected data from a sample of 180 bank customers and professionals in Cameroon through structured questionnaires. The data was analysed using descriptive statistics, correlation analysis, and regression analysis. The validity and reliability of the instruments were ensured through pilot testing and expert review.
Findings: The principal findings reveal that customer profitability is significantly influenced by behavioural factors (β = 0.266, p < 0.001) and financial factors (β = 0.335, p < 0.000), while bank type (p = 0.131) and customer loyalty (p = 0.523) have no significant impact. The study also found that the data is not normally distributed, and that heteroskedasticity is present in the data. The regression model explains approximately 36.7% of the variance in customer profitability (R² = 0.367).
Unique Contribution to Theory, Practice and Policy: This study contributes to the existing literature on customer segmentation by providing empirical evidence from the Cameroonian banking context, an under-researched setting. Theoretically, it validates the application of behavioural and financial factors in predicting customer profitability. Practically, it offers bank managers a evidence-based framework for identifying profitable customer segments, enabling more targeted marketing strategies and product development. For policymakers, the findings highlight the need to encourage data-driven decision-making in the financial sector to enhance overall banking sector stability and profitability.
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