ANALYTICAL APPROACH TO DIGITAL CHANNEL PERFORMANCE OPTIMIZATION OF MOBILE MONEY TRANSACTIONS IN EMERGING MARKETS

Understanding marketing channel performance is a crucial and complex task for the mobile financial technology segment of the mobile industry in emerging markets. However, poor techniques and capabilities for channel optimization of the mobile money users across available channels by the service providers often undermine the performance of these channels. The research aims to develop a target selection and campaign optimization framework for mobile money customers along two channels of transactions. It is complemented by mapping the appropriate campaign techniques across digital and non-digital channels of mobile money transactions. The key analytical method is the combination of fuzzy c-means clustering and RFM algorithm for the target selection development through the usage logs of customers (n = 300) of a mobile service provider. The results indicated that fuzzy c-means clustering and RFM algorithm are efficient for target selection. Also, the mapping of clusters with the appropriate channel of transactions revealed that mobile money users' transactions could be optimized along the digital channel. The analytic model's output enables appropriate cross-selling and up-selling campaigns that optimize the service provider revenue from existing and new mobile money users within the customer base. The channel evaluation revealed mobile application channels to be a promising and future channel for mobile money transactions as smartphone penetration continues to grow in emerging mobile markets. That is a positive sign of the digital channel's future potential for mobile money transactions in developing markets.