Intelligent Digital Intermediation Solution: Exploring Growth Potential with Analytics
Purpose: To understand the factors that affect the choice of payment intermediation solution on an e-commerce website and use data analytics to proactively suggest the appropriate payment solution which can enhance user experience.
Methodology: The study was conducted by reviewing literature on payment methods, customer preferences, data analytics and artificial intelligence. The gaps identified in literature review were studied to find the application of analytics for suggesting appropriate payment intermediation solution. Survey of customer payment preferences in different use cases was conducted on sample basis using questionnaire. The relationship of user demographics, product type and payment transaction characteristics with payment preference through use of analytics was studied in the paper.
Findings: The analysis conducted on responses received from sample suggest that there exists a pattern of selection of payment method for given use cases. The same can be intelligently predicted using data analytics to suggest appropriate digital payment intermediation solution.
Research Implications: Since the customer payment preference under given use case can be predicted with the application of data analytics, payment service providers, banks and e-commerce websites can improve the user experience by intelligently offering appropriate digital payment intermediation solution. Further, using the factors which influence the most, they may determine their strategies to improve acceptance and usage of their own digital payment intermediation solution.
Originality / Value: Although various studies exist with respect to analytics for personalized up-selling or cross-selling, the personalization in the area of intelligent customer payment preference is yet to be exploited and implemented.
Keywords— Analytics for Digital Transformation, Customer Payment Preference, Cards, Mobile Wallets, Intelligent Digital Intermediation Solution