How Text Mining Approach can be Used to Understand Automobile Purchase

Abstract

Word of mouth has long been recognized to be an influential variable in marketing. With the growth of Internet applications, traditional word of mouth has evolved into the online form where individuals spread their perceptions via the written word. With the rapid growth of comments by consumers over the Internet, in-depth purchasing related information is available to markers. In this paper we try to extract the essence of consumers’ attitudes from the online reviews posted on kbb.com through text-mining approach, which is the most popular and highly visited website in automobile industry. Thus we can identify the key features that are related to the prediction of positive/negative overall attitudes of online users. Then with the diagnostic of these identified key features through Gini indexing, they can be used to help to marketers in designing their keyword choices for more effective application of search engine marketing strategies for positive associated key features while identification of the negative associated key words will lead to discovery of problematic areas.