Abstract
As the range of the customer choice becomes more diverse, the average life span of companies' products and services is becoming shorter. Most companies are striving to maximize the revenue by understanding the customer's needs and providing customized products and services. However, companies had to bear a significant burden, in terms of the time and cost involved in the process of determining each individual customer's needs. Therefore, an alternative method is employed that involves grouping the customers into different categories based on certain criteria and establishing a marketing strategy tailored for each group. In this way, customer segmentation and customer clustering are performed using demographic information and behavioral information. Demographic information included sex, age, income level, and etc., while behavioral information was usually identified indirectly through customers' purchase history and search history. However, there is a limitation regarding companies' customer behavioral information, because the information is usually obtained through the limited data provided by a customer on a company's website. This is because the pattern indicated when a customer accesses a particular site might not be representative of the general tendency of that customer. Therefore, in this study, rather than the pattern indicated through a particular site, a customer's interest is identified using that customer's access record pertaining to external news. Hence, by utilizing this method, we proposed a methodology to perform customer segmentation. In addition, by extracting the main issues through a topic analysis covering approximately 3,000 Internet news articles, the actual experiment applying customer segmentation is performed and the applicability of the proposed methodology is analyzed.
