Market segmentation plays essential role on understanding the behavior of people’s interests in purchasing various products and services through various channels. This paper presents an empirical investigation to shed light on consumer’s purchasing attitude as well as gathering information in multi-channel environment. The proposed study of this paper designed a questionnaire and distributed it among 800 people who were at least 18 years of age and had some experiences on purchasing goods and services on internet, catalog or regular shopping centers. Self-organizing map, SOM, clustering technique was performed based on consumer’s interest in gathering information as well as purchasing products through internet, catalog and shopping centers and determined four segments. There were two types of questions for the proposed study of this paper. The first group considered participants’ personal characteristics such as age, gender, income, etc. The second group of questions was associated with participants’ psychographic characteristics including price consciousness, quality consciousness, time pressure, etc. Using multinominal logistic regression technique, the study determines consumers’ behaviors in each four segments.

One of the most important objectives of any modern organization is to gain competitive advantage of customers & apos; 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.