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    Analysis of customer lifetime value and marketing expenditure decisions through a Markovian-based model
    (Elsevier, 2014) Ekinci, Yeliz; Ulengin, Fusun; Uray, Nimet; Ulengin, Burc
    The general aim of this study is to provide a guide to the future marketing decisions of a firm, using a model to predict customer lifetime values. The proposed framework aims to eliminate the limitations and drawbacks of the majority of models encountered in the literature through a simple and industry-specific model with easily measurable and objective indicators. In addition, this model predicts the potential value of the current customers rather than measuring the current value, which has generally been used in the majority of previous studies. This study contributes to the literature by helping to make future marketing decisions via Markov decision processes for a company that offers several types of products. Another contribution is that the states for Markov decision processes are also generated using the predicted customer lifetime values where the prediction is realized by a regression-based model. Finally, a real world application of the proposed model is provided in the banking sector to show the empirical validity of the model. Therefore, we believe that the proposed framework and the developed model can guide both practitioners and researchers. (C) 2014 Elsevier B.V. All rights reserved.
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    A customer lifetime value model for the banking industry: a guide to marketing actions
    (Emerald Group Publishing Ltd, 2014) Ekinci, Yeliz; Uray, Nimet; Ulengin, Fusun
    Purpose - The aim of this study is to develop an applicable and detailed model for customer lifetime value (CLV) and to highlight the most important indicators relevant for a specific industry - namely the banking sector. Design/methodology/approach - This study compares the results of the least square estimation (LSE) and artificial neural network (ANN) in order to select the best performing forecasting tool to predict the potential CLV. The performances of the models are compared by the hit ratio, which is calculated by grouping the customers as top 20 per cent and bottom 80 per cent profitable. Findings - Due to its higher performance; LSE based linear regression model is selected. The results are found to be highly competitive compared with the previous studies. This study shows that, beside the indicators mostly used in the literature in measuring CLV, two additional groups, namely monetary value and risk of certain bank services, as well as product/service ownership-related indicators, are also significant factors. Practical implications - Organisations in the banking sector have to persuade their customers to use certain routine risk-bearing transaction-based services. In addition, the product development strategy has a crucial role to increase the CLV of customers because some of the product-related variables directly increase the value of customers. Originality/value - The proposed model predicts potential value of current customers rather than measuring current value considered in the majority of previous studies. It eliminates the limitations and drawbacks of the majority of models in the literature through simple and industry-specific method which is based on easily measurable and objective indicators.