A Methodology of Market Segmentation Using Customer’s Surfing and Buying History on the Internet Shopping Malls |
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A Methodology of Market Segmentation Using Customer’s Surfing and Buying History on the Internet Shopping Malls
A Methodology of Market Segmentation Using Customer’s Surfing and Buying History on the Internet Shopping Malls
ABSTRACT
Lots of shopping malls continue to search for a competitive advantage in an increasingly tight market in the electronic marketplace. Market segmentation is considered to be one of important strategies for competitive advantage because of its capability to manage customers. There are three types of information that might be used for segmentation in the Internet shopping malls, which are customer’s profile, surfing and buying history. We suggest a methodology of benefit segmentation using customer’s surfing and buying history. Traditional market segmentation methodologies based only on customer’s profile fail to utilize abundant information that customer’s surfing and buying history give about his/her preference. Our methodology consists of four steps: 1) analysis of product web pages, 2) data preparation, 3) estimation and its interpretation, 4) development of marketing mix. Our methodology is to give a useful guideline to the Internet shopping malls for market segmentation.
KEYWORDS
Market segmentation, Electronic marketplace, Internet shopping mall, Surfing and buying history, Marketing
A Methodology of Market Segmentation Using Customer’s Surfing and Buying History on the Internet Shopping Malls
1. INTRODUCTION
For years, the Internet and its World Wide Web (WWW) have created a number of electronic shopping malls in an unprecedented speed [1]. Lots of electronic shopping malls employ one-to-one marketing strategies by using database technologies [2]. However, inadequate uses of these strategies force their customers into being dissatisfied. For instance, a lot of shopping malls e-mail to their customers indiscriminately. For this reason, their customers have to struggle against enormous amount of junk mails every day and night, which are hardly of interest to them.
Market segmentation for the customer’s benefit may be one of good solutions to this problem. By market segmentation, marketers who engage in shopping malls can find out what motivates customers to respond, how to communicate to each customer, and they are able to increase a customer’s lifetime value by increasing customer loyalty [2].
Market segmentation has long been considered to be one of the most fundamental concepts of modern marketing [3]. Kotler and Armstrong [4] suggested several variables for market segmentation, which were geographic, demographic, psychographic and behavioral. Since there are too many consumers who don’t have membership to shopping malls, the first three variable sets are not applicable to the Internet shopping malls for the reason that they cannot be aware of the customer’s profile for segmentation. Fortunately, The Internet shopping malls facilitate the storage and recall of each history of customer’s surfing [5], and these can be information for behavioral segmentation in their Internet shopping malls. Many marketers believe that behavioral variables are the best starting point for building market segments. That’s why we used surfing and buying history for segmentation.
A powerful form of segmentation is to group buyers according to the different benefits that they seek from the product [4]. For the identification of segments, both the segmentation base and method are vitally important. Of all the segmentation base or variables, the benefits that customers derive from the attributes of products or services have proved to be the most powerful variables [6-9]. This kind of segmentation is called benefit segmentation. The benefit segmentation requires finding the major benefits which people look for in the product class, the kinds of people who look for each benefit, and the major brands that deliver each benefit.
However, there are no detailed procedures and methodologies of benefit segmentation in the Internet shopping malls yet. This paper suggests a methodology of benefit segmentation using customer’s surfing a...