Classifying Attitudes of Thai Business Organizations Toward the Perceived Benefit of Customer Predictive Analytics

Abstract

In this paper, we applied K-means++, Agglomerative and Decision Tree techniques to classify characteristics of Thai business organizations toward the perceived benefit of predictive analytics. We believe that different characteristics of business organizations require different solution approaches to overcome challenges and gain business value. In the exploratory survey, we collected 84 respondents, who are data analysts, business analysts, business owners, management, and IT managers. The respondents' size of organization varies from small firms to large firms. The result from three techniques of classification shows that Thai business organizations perceiving the benefit of predictive analytics could be divided into two groups. We further confirmed that with the analysis of variance technique to identify the difference of means in each parameter. We also found that the most important descriptive profile is led by customer-related factors such as a change in the percentage of customers, the number of direct customers, and number of sales and marketing staff. These are followed by technology factors, which are the number of external and internal data sources and number of analytics and technologies currently used for data analytics.