Abstract:

The personalization of consumption is advancing because of the increase in single person households, which is due to the heightening maturation of consumption mind and individualistic orientation since the middle of the eighties. It has become necessary to have personal marketing that is based on marketing strategic information systems (MSIS), which limitlessly specify information about the living concepts, needs, and wants of the individual persons. And through the MSIS, making just-in-time the individual person's living scenes, the sales scenes, distribution scenes, and production scenes has become more and more important. The most of MSIS, will be realized by systemizing information through the use of computer- based advanced technology. In addition, unlike the mass production and mass consumption era, in the personal marketing of the consumption personalization era rough average values extracted from mass sample quantitative surveys of mass databases and broad clusters of data are not effective in the qualitative specification of the individual person. Quantitative data only describe the conditions in the past, and are inadequate for grasping the minutely changing personal image of the consumer of the present and the near future. Consequently, personal marketing does not use the average values of samplings to understand the situation, but begins by drawing a precise picture of the everyday living scene and story of the consumer, which is as endlessly close to the individual as possible. The use of qualitative data (which uses words and images) is indispensable in doing this. Through, not mass samples, but group interviews with market innovators, trendsetters, and market leaders, consumer behavior diary databases, and observation (town watching, fixed point observation, etc.), the unspecific minority's reality is grasped using words and images. On the other hand, quantitative data are used to understand the shifts and framework of the market from the past to the present. Therefore, it is most effective to understand market shifts using quantitative time series panel surveys, and to predict how a market will be minutely changing in the near future using qualitative data