Information and communication technology plays essential role for people’s day-to-day business activities. People receive most of their knowledge by processing, recording and transferring necessary information through surfing Internet websites. Internet as an essential part of information technology (IT) has grown remarkably. Nowadays, there have been significant amount of efforts in Iran for developing e-commerce. This paper studies the effects of environmental internet features on internet purchase intention. The study divides internet environment into demographic and technologic parts and, for studying each of them, many features are investigated such as internet connection speed, connectivity model, web browser, type of payments, user’s income, user’s education, user’s gender, frequency of online usage per week and users’ goal for using internet. Using Logistic regression technique, the study has determined a meaningful effects of income, education, connection type, browser and goal on consumers’ behavior.

In today' s extremely competitive environment, customers are the most important asset of any business and success of any organization depends on loyal customer retention. Therefore, it is important to learn more about different groups of customers and propose appropriate plans to take care of them. Customer segmentation is one of the most common methods to analyze customer’s behavior. The market can be divided into several smaller homogeneous groups, which helps organizations deliver targeted marketing techniques and provides optimized techniques for resource allocation. This paper uses the information gathered from Point of Sales (POS) in one of Iranian private banks and using two methods of K-Means and Kohonen, customers are clustered into four segments to detect the most profitable customers.