A data mining method for service marketing: A case study of banking industry

One of the most important objectives of any modern organization is to gain competitive advantage of customers' data. In order to find hidden patterns or models from data, application of modern and steady methodologies is a necessity. Banking industry is not exceptional from this trend and they may often wish to make more profit by providing appropriate services to potential customers. Analyzing databases to manage customer behaviors seems difficult since databases are multi-dimensional, comprised of monthly account records and daily transactional records. Therefore, to analyze databases, we propose a methodology by considering human factors and building an integrated data utilization system. Moreover, self-organizing neural network map is used to identify groups of customers based on repayment behavior, recency, frequency, and monetary behavioral scoring predicators. We also perform more analysis using Apriori association rule to make marketing strategies for services used by banks.