A Probabilistic Approach to Maximize Cross-Selling Revenues of Financial Products

Authors

  • Yasin Altun Industrial Engineering Department, Kadir Has University, Istanbul, Turkey
  • Ahmet Yucekaya Industrial Engineering Department, Kadir Has University, Istanbul, Turkey

Keywords:

Cross-selling, Financial products, Banking, Simulation, Integer programming

Abstract

Customer oriented approach and developing analysis for customers have become more important as the competition became a global issue, especially after technological advancements. Companies aim to sell more products to new customers and also to their current customers while keeping them in the portfolio and making sure that they are happy. Cross-selling of products and services to their customers is almost as important as gaining new customers. In this paper, a probabilistic and integrated method of cross-selling financial products is proposed. The proposed method first segments the customers based on the selected criteria and then calculates the probability of buying each product using product and customer relationship matrixes. Then, the expected yield for each group of customers and offer is calculated, and the best cross-selling strategy is determined. The proposed methodology is applied to a Turkish bank that aims to sell financial products through cross-selling. The results show that the methodology successfully determines the product order to be used in cross-selling in an effort to increase the success rate in the selling process and expected revenue.

References

. Akçura, M. T., & Srinivasan, K. (2005). Research note: customer intimacy and cross-selling strategy. Management Science, 51(6), 1007-1012.

. Jarrar, Y. F., & Neely, A. (2002). Cross-selling in the financial sector: customer profitability is key. Journal of Targeting, Measurement and Analysis for Marketing, 10(3), 282-296.

. Li, S., Sun, B., & Wilcox, R. T. (2005). Cross-selling sequentially ordered products: An application to consumer banking services. Journal of Marketing Research, 42(2), 233-239.

. Kamakura, W. A., Wedel, M., De Rosa, F., & Mazzon, J. A. (2003). Cross-selling through database marketing: a mixed data factor analyzer for data augmentation and prediction. International Journal of Research in marketing, 20(1), 45-65.

. Knott, A., Hayes, A., & Neslin, S. A. (2002). Next‐product‐to‐buy models for cross‐selling applications. Journal of interactive Marketing, 16(3), 59-75.

. Kamakura, W. A., Ramaswami, S. N., & Srivastava, R. K. (1991). Applying latent trait analysis in the evaluation of prospects for cross-selling of financial services. international Journal of Research in Marketing, 8(4), 329-349.

. Kamakura, W. A., Kossar, B. S., & Wedel, M. (2004). Identifying innovators for the cross-selling of new products. Management Science, 50(8), 1120-1133.

. Netessine, S., Savin, S., & Xiao, W. (2006). Revenue management through dynamic cross selling in e-commerce retailing. Operations Research, 54(5), 893-913.

. Li, S., Sun, B., & Montgomery, A. L. (2011). Cross-selling the right product to the right customer at the right time. Journal of Marketing Research, 48(4), 683-700.

. Peltier, J. W., Schibrowsky, J. A., Schultz, D. E., & Davis, J. (2002). Interactive psychographics: Cross-selling in the banking industry. Journal of Advertising Research, 42(2), 7-22.

. Harrison, T., & Ansell, J. (2002). Customer retention in the insurance industry: using survival analysisto predict cross-selling opportunities. Journal of Financial Services Marketing, 6(3), 229-239.

. Wong, R. C. W., Fu, A. W. C., & Wang, K. (2005). Data mining for inventory item selection with cross-selling considerations. Data mining and knowledge discovery, 11(1), 81-112.

. Liu-Thompkins, Y., & Tam, L. (2013). Not all repeat customers are the same: Designing effective cross-selling promotion on the basis of attitudinal loyalty and habit. Journal of Marketing, 77(5), 21-36.

. Lee, D., Park, S. H., & Moon, S. (2013). Utility-based association rule mining: A marketing solution for cross-selling. Expert Systems with applications, 40(7), 2715-2725.

. Zhang, R. Q., Kaku, I., & Xiao, Y. Y. (2011). Deterministic EOQ with partial backordering and correlated demand caused by cross-selling. European Journal of Operational Research, 210(3), 537-551.

. Wong, R. C. W., Fu, A. W. C., & Wang, K. (2003, November). MPIS: Maximal-profit item selection with cross-selling considerations. In Third IEEE International Conference on Data Mining (pp. 371- 378). IEEE.

. Armony, M., & Gurvich, I. (2010). When promotions meet operations: Cross-selling and its effect on Call center performance. Manufacturing & Service Operations Management, 12(3), 470-488.

. Nash, D., & Sterna-Karwat, A. (1996). An application of DEA to measure branch cross selling efficiency. Computers & operations research, 23(4), 385-392.

. Schmitz, C., Lee, Y. C., & Lilien, G. L. (2014). Cross-selling performance in complex selling contexts: an examination of supervisory-and compensation-based controls. Journal of Marketing, 78(3), 1-19.

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Published

2021-04-24

How to Cite

Altun, Y. ., & Yucekaya, A. . (2021). A Probabilistic Approach to Maximize Cross-Selling Revenues of Financial Products. American Scientific Research Journal for Engineering, Technology, and Sciences, 79(1), 1–14. Retrieved from https://www.asrjetsjournal.org/index.php/American_Scientific_Journal/article/view/6748

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