Identifying the relationship between area characteristics by social class and bank branches distribution using GIS - A case study of Tokyo 23 Wards  Young Joo Lee, Hiromichi Fukui Keio University, Japan Endo5322, Fujisawa, Kanagawa, 252-8520, Japan Email: yjlee@sfc.keio.ac.jp, hfukui@sfc.keio.ac.jp 1. Introduction Over the last few years, the financial service market has seen a proliferation of new players and channels by changes in the external environments. Banks have found themselves facing more aggressive competition, uncertainty and unlimited opportunities. Therefore, they must examine their strengths and opportunities and take a competitive position in the competitive marketplace. Furthermore, banks have to reconsider and reevaluate fundamental assumptions about how they reach their markets to build efficient branch marketing strategies. That is what market segmentation analysis is for awareness of their customers and marketplace. Specifically, GIS based these analyses by spatial data and attributes data such as demographic and socioeconomic data, and are relevant and useful to identify the area characteristics and find new market with similar characteristics. The purpose of this paper is to examine the relevance between area characteristic by social class and distribution characteristics of existing branches of five major banks in Tokyo 23 wards for making efficient bank branch strategies using GIS with socioeconomic data, major commercial banks data, and spatial data of Tokyo 23 wards. 2. Study Area Segmentation involves identifying customer groups that are fairly homogeneous among themselves but are different from other customer types. Its purpose is to determine differences between customers that are of relevance to the marketing decision maker. Wendell Smith(1956) first defined market segmentation as “viewing a heterogeneous market as a number of smaller homogeneous markets, in response to differing preferences, attributable to the desires of customers for more precise satisfaction of their varying wants”. And, Wedel and Kamakura(1998) note that “even if a market can be partitioned into homogeneous segments, market segmentation will be useful only if the effectiveness, efficiency and manageability of marketing activity are influenced substantially by discerning separate homogeneous group of customers”. Initially, segmentation in retail financial services basically followed the demographic lines. Categories such as age, gender, education, income, family size and geographic location were used(Dickens and Chappell, 1977; Frank, 1989; Chisnall, 1992.) However, this form of segmentation is limited in solving marketing problems because, it is very general and was often used as a matter of convenience. Therefore, we implemented the segmentation analysis by social class from two approaches - geographic and demographic – to resolve the complicated problems in the financial sector using GIS in this study. GIS based analysis helps to understand how a potential new branch would perform based on the performance of a bank’s best matching existing branches as well as define more precisely the target group of customers.
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