Automation of Analytical System for Measuring Service Effectiveness by Customer Type

Presently, data analysis has become an indispensable part in various fields of technological applications. The development of analytical methods that do not require analysts to repeatedly analyze data is becoming important. These methods are expected to automate the analysis of large quantities of data gathered on a daily basis. The purpose of this study is to propose and examine a method for automating the process of measuring service effectiveness by customer type. In particular, we propose a method for automating the decisions for a number of factors, applying text mining for automation of interpretation of factor, using decision-making rules for automation of customer classification, and extracting meaningful variables to facilitate an effective feedback on customer satisfaction. The proposed analytical automation system is able to analyze the data and produce results with almost the same amount of information just as analysts do without automation.