• Journal of Distribution Science
• /
• v.9 no.4
• /
• pp.5-13
• /
• 2011

This study provides analysis of the effectiveness of domestic marketing strategies of the Korean coffee shop "Caffe Bene". It bases its evaluation on statistical outputs of 'choice attributes,' "market segmentation," demographic characteristics," and "satisfaction differences." The results are summarized in four points. First, five choice attributes were extracted from factor analysis: price, atmosphere, comfort, taste, and location; these are related to coffee shop selection behavior. Based on these five factors, cluster analysis was conducted, with statistical results classifying customers into three major groups: atmosphere oriented; comfort oriented; and taste oriented. Second, discriminant analysis tested cluster analysis and showed two discriminant functions: location and atmosphere. Third, cross-tabulation analysis based on demographic characteristics showed distinctive demographic characteristics within the three groups. Atmosphere oriented group, early-20s, as women of all ages was found to be 'walking down the street 'and 'through acquaintances' in many cases, as the cognitive path, and mostly found the store through 'outdoor advertising', and 'introduction'. Comfort oriented group was mainly women who are students in their early twenties or professionals, and appeared as a group to be very loyal because of high recommendation to other customers compared to other groups. Taste oriented group, unlike the other group, was mainly late-20s' college graduates, and was confirmed, as low loyalty, with lower recommendation activity. Fourth, to analyze satisfaction differences, one-way ANOVA was conducted. It shows that groups which show high satisfaction in the five main factors also show high menu satisfaction and high overall satisfaction. This results show that segmented marketing strategies are necessary because customers are considering price, atmosphere, comfort, taste, location when they choose coffee shop and demographics show different attributes based on segmented groups. For example, atmosphere oriented group is satisfied with shop interior and comfort while dissatisfied with price because most of the customers in this group are early 20s and do not have great financial capability. Thus, price discounting marketing strategies based on individual situations through CRM system is critical. Comfort oriented group shows high satisfaction level about location and shop comfort. Also, in this group, there are many early 20s female customers, students, and self-employed people. This group customers show high word of mouth tendency, hence providing positive brand image to the customers would be important. In case of taste oriented group, while the scores of taste and location are high, word of mouth score is low. This group is mainly composed of educated and professional many late 20s customers, therefore, menu differentiation, increasing quality of coffee taste and price discrimination is critical to increase customers' satisfaction. However, it is hard to generalize the results of study to other coffee shop brand, because this study have researched only one domestic coffee shop, Caffe Bene. Thus if future study expand the scope of locations, brands, and occupations, the results of the study would provide more generalizable results. Finally, research of customer satisfactions of menu, trust, loyalty, and switching cost would be critical in the future study.

• Industrial Engineering and Management Systems
• /
• v.14 no.4
• /
• pp.335-346
• /
• 2015

The electronic commerce site (EC site) has become an important marketing channel where consumers can purchase many kinds of products; their access logs, including purchase records and browsing histories, are saved in the EC sites' databases. These log data can be utilized for the purpose of web marketing. The customers who purchase many product items are good customers, whereas the other customers, who do not purchase many items, must not be good customers even if they browse many items. If the attributes of good customers and those of other customers are clarified, such information is valuable as input for making a new marketing strategy. Regarding the product items, the characteristics of good items that are bought by many users are valuable information. It is necessary to construct a method to efficiently analyze such characteristics. This paper proposes a new latent class model to analyze both purchasing and browsing histories to make latent item and user clusters. By applying the proposal, an example of data analysis on an EC site is demonstrated. Through the clusters obtained by the proposed latent class model and the classification rule by the decision tree model, new findings are extracted from the data of purchasing and browsing histories.

• Journal of the Korea Fashion and Costume Design Association
• /
• v.24 no.2
• /
• pp.59-72
• /
• 2022

The online fashion market in the 21st century has shown rapid growth. Against this backdrop, using consumer activity data to provide customized customer services has emerged as a viable business model that draws attention. Algorithm-based personalized recommendation services are a good example. But their application in fashion products has clear limitations. It is not easy to identify consumers' perceptions of the attributes of fashion, which are various, hard to define, and very sensitive to trends. So there is a need to compile data on consumers' underlying awareness and to carry out defined research to increase the utilization of such services in the fashion industry and further engage consumers. This research aims to classify the attributes and types of fashion products and to identify consumers' perceptions of a given situation where a recommendation service is offered. To find out consumers' perceptions of and satisfaction with recommendation services, an online and mobile survey was conducted on women in their 20s and 30s, a group that uses recommendation services frequently. A total of 455 responses were used for analysis. SPSS 28.0 was used, combined with Conjoint Analysis and multiple regression, to analyze data. The study results could provide insights into a better understanding of recommendation services and be used as basic data for companies to identify consumers' preferences and draw up a detailed strategy for market segmentation.

• Journal of Intelligence and Information Systems
• /
• v.21 no.2
• /
• pp.93-112
• /
• 2015

Depending on the change in consumer's consumption pattern, existing retail shop has evolved in hypermarket or convenience store offering grocery and daily products mostly. Therefore, it is important to maintain the inventory levels and proper product configuration for effectively utilize the limited space in the retail store and increasing sales. Accordingly, this study proposed proper product configuration and inventory level strategy based on RFM(Recency, Frequency, Monetary) model and SOM(self-organizing map) for manage the retail shop effectively. RFM model is analytic model to analyze customer behaviors based on the past customer's buying activities. And it can differentiates important customers from large data by three variables. R represents recency, which refers to the last purchase of commodities. The latest consuming customer has bigger R. F represents frequency, which refers to the number of transactions in a particular period and M represents monetary, which refers to consumption money amount in a particular period. Thus, RFM method has been known to be a very effective model for customer segmentation. In this study, using a normalized value of the RFM variables, SOM cluster analysis was performed. SOM is regarded as one of the most distinguished artificial neural network models in the unsupervised learning tool space. It is a popular tool for clustering and visualization of high dimensional data in such a way that similar items are grouped spatially close to one another. In particular, it has been successfully applied in various technical fields for finding patterns. In our research, the procedure tries to find sales patterns by analyzing product sales records with Recency, Frequency and Monetary values. And to suggest a business strategy, we conduct the decision tree based on SOM results. To validate the proposed procedure in this study, we adopted the M-mart data collected between 2014.01.01~2014.12.31. Each product get the value of R, F, M, and they are clustered by 9 using SOM. And we also performed three tests using the weekday data, weekend data, whole data in order to analyze the sales pattern change. In order to propose the strategy of each cluster, we examine the criteria of product clustering. The clusters through the SOM can be explained by the characteristics of these clusters of decision trees. As a result, we can suggest the inventory management strategy of each 9 clusters through the suggested procedures of the study. The highest of all three value(R, F, M) cluster's products need to have high level of the inventory as well as to be disposed in a place where it can be increasing customer's path. In contrast, the lowest of all three value(R, F, M) cluster's products need to have low level of inventory as well as to be disposed in a place where visibility is low. The highest R value cluster's products is usually new releases products, and need to be placed on the front of the store. And, manager should decrease inventory levels gradually in the highest F value cluster's products purchased in the past. Because, we assume that cluster has lower R value and the M value than the average value of good. And it can be deduced that product are sold poorly in recent days and total sales also will be lower than the frequency. The procedure presented in this study is expected to contribute to raising the profitability of the retail store. The paper is organized as follows. The second chapter briefly reviews the literature related to this study. The third chapter suggests procedures for research proposals, and the fourth chapter applied suggested procedure using the actual product sales data. Finally, the fifth chapter described the conclusion of the study and further research.

• Journal of Nutrition and Health
• /
• v.53 no.4
• /
• pp.431-444
• /
• 2020

Purpose: The purposes of this study were to understand the health interest of consumers in the United States and Japan and thus understand the motivation of food choices, in order to provide basic data on the country's strategy based on healthy and correct food choices in the future. Methods: A customer survey was conducted in 2019 from October 18 to 31, and it targeted 115 American and 120 Japanese local consumers between the ages of 20- to 64-years-old. Eight questions were formed using General Health Interest. Based on food choice motivation, 27 questions were reconstructed and asked about demographic information. All data were analyzed by SPSS Statistics (ver. 25). Results: Health consciousness was categorized into 2 types: nutrition-seeking type and preference-seeking type. Based on these 2 factors, customers were grouped into 3 clusters: healthy dietary life-seeking group, nutrition balance-seeking group and health indifference group. Food choice motivation was categorized into 4 types: health, efficiency, value, and mood. All 3 groups showed a high tendency for efficiency in common. The results show that consumers want higher satisfaction with their time and money invested in food consumption. It is believed that the focus and investment of market segmentation strategy should be focused on product development, especially for American and Japanese consumers who are interested in health. Conclusion: The results of this study reflect consumer needs that can assist in the selection of healthy and correct foods in the future.

• CRM연구
• /
• v.2 no.1
• /
• pp.33-52
• /
• 2009

This research focused on the moderating role of the influence an expectation exerts on a performance by a regional festival and the experience to get visitor's feeling and satisfaction. A survey design was used for the last analysis targeted for the respondent who experienced an experience directly targeted for the regional where a regional festival is promoted actively targeted for the visitor. Results are show a positive influence on the expectation exerts on a performance of festival. In addition, it was confirmed that festival experience activity the role important to feeling and satisfaction of a visitor. We suggest, therefore, that it has to raise the efficiency of the strengthening of an experience program to raise an performance of festival participants and the festival manage to draw out the various feeling formation and satisfaction through participation customers' segmentation.

• The Journal of the Korea Contents Association
• /
• v.8 no.1
• /
• pp.48-58
• /
• 2008

This study intends to figure out the image evaluation properties of internet shopping malls and suggest a strategic direction for positioning through establishing a perceptual map on how the actual customers remember them and which image expression would make the most effective marketing. According to the result of analysis, the images of internet shopping malls were drawn as elements such as product information service, customer service after purchase, atmosphere, convenience, safety, and fame. And according to the result of making a perceptual map, it showed that there was a meaningful difference in the customers' perception on competitive shopping malls. The most discriminative property among the images of shopping malls was product information service, and the least discriminative property was convenience. In addition, there showed a meaningful difference in the customers' preference and ideal point on internet shopping malls between the subdivided groups of customers. It was verified that in this internet shopping mall market where competition is getting severe, the result of this study can be a useful foundational data in establishing a marketing strategy of market segmentation.

• Journal of Global Scholars of Marketing Science
• /
• v.16 no.2
• /
• pp.55-75
• /
• 2006

This study aims to identify the unknown essential condition to form the blue ocean market, in addition to the innovation of customer value which does not become a sufficient condition though it is one of the essential conditions to form a blue ocean market, and induce companies to take a firm foothold in the blue ocean market after going to the blue ocean market by segmenting the market after setting up appropriate strategies. On the basis of those goals of this study, we dealt with subjects like the problem of approaching the market that possesses factors of differentiated value innovation, the segmentation of value innovative market, the problem about the major variables that shed light on the character of blue ocean optical illusion market, the strategy for following companies to enter the market, which we applied to the actual analysis based on the investigation into the literature related to value innovation and blue ocean strategy, investigation into the actual cases and objective data. We analysed a domestic refrigerator market and a domestic chewing gum market as representative examples of durables and nondurables and segmented each market on a value innovation market. We discovered the blue ocean and the blue ocean's illusive market of the two markets. I've mentioned and studied the characters of those positively.

• The Korean Journal of Archival Studies
• /
• no.62
• /
• pp.139-183
• /
• 2019

Today, the archives strive to move towards more open and hospitable spaces for its users and to provide differentiated services based on detailed user needs and behavior for their own survival and development. Building services for children is especially vital in changing public awareness and expanding the customer base. Therefore this study aims to present fundamental data required for improving exhibit services by understanding children users' perceptions and needs. For such purposes, this study examines the cases of both domestic and overseas exhibit services of presidential archives. Also, the study included the surveys of children and parents who have accompanied children visiting the presidential archive and experiencing the exhibit services. This study is meaningful in that it conducted the evaluation of archival exhibit services in the perspective of the children users. In addition, the analysis of children's satisfactions and needs can contribute to the spread of archival culture and the revitalization of children users' visitations.

• Journal of the Korea Society of Computer and Information
• /
• v.19 no.2
• /
• pp.193-200
• /
• 2014

Due to the advent of ubiquitous computing environment, it is becoming a part of our common life style. And tremendous information is cumulated rapidly. In these trends, it is becoming a very important technology to find out exact information in a large data to present users. Collaborative filtering is the method based on other users' preferences, can not only reflect exact attributes of user but also still has the problem of sparsity and scalability, though it has been practically used to improve these defects. In this paper, we propose clustering method by user's features based on SOM for predicting purchase pattern in u-Commerce. it is necessary for us to make the cluster with similarity by user's features to be able to reflect attributes of the customer information in order to find the items with same propensity in the cluster rapidly. The proposed makes the task of clustering to apply the variable of featured vector for the user's information and RFM factors based on purchase history data. To verify improved performance of proposing system, we make experiments with dataset collected in a cosmetic internet shopping mall.