Prior research shows that in-store displays have a significant effect on product sales, but no study so far has measured this effect using a qualitative approach that considers the size of the in-store display or its general theme. In this study, a smartphone-based user generated contents (UGC) was used to encourage consumers to post about the in-store displays they liked. This study investigates the relationship between the qualitative content of in-store displays and the sales of the products featured in such displays, and the relationship between posts or likes and the sales of the products featured in the posted liked display. We examine the effects of the contents of in-store display on sales and the mediation effect of the POST or LIKE on these relationship. As the result, this study is the first to explicate the difference of the mediation effect of post on sales by the type of the content of the in-store display. Specifically, the following three aspects were elucidated: (1) “Seasonality” drives user posting on UGC and such posts contribute to increased sales, (2) “Mass” both directly contributes to increased sales and also promotes user postings on UGC, which contribute to increase sales, and (3) “Character” directly influences sales but does not contribute to sales through postings. This study also provides important managerial implications. The results highlight the role of the content of in-store displays in promoting sales. Specifically, if the goal is to simply increase sales, a character themed in-store display will suffice. If the goal is to induce postings to UGC, which will result in increased sales, then a seasonally themed in-store display will work. In this way, expanding consideration to the qualities of in-store displays makes it possible to develop a more strategic understanding of their effects rather than the simple on/off or numerical frequency approach of the past. It must be taken into account that the type of in-store display content that is called for will differ according to whether the objective is to simply increase sales or to also attempt to create WOM promotion.

This article focuses on the use of the cosmetics channel of customers. There are many papers about channel choice behavior of consumers. Blattberg et al (2008) pointed out that the consumer decide their channel by marketing action, channel attribute, social influence, channel integration, individual difference, and situation factors. Kushwaha, et al (2013) said that in the case of buying an axiomatic product, consumers who are using only Web are excellent customers, whereas consumers using many channels are excellent customers in the case of a hedonistic product. Neslin, et al (2014) implied that the channel and brand are interrelated, so the customer think about both channel choice and brand choice at same time. Valentine et al (2014) found that multi-channel user is more information sensitive than that of single-channel user, and customer who are satisfied the service of their chosen channel do not try to use new channel. From these papers, it is clear that consumer’s channel choice behavior depends on, not only channel specialty, but also product specialty. On the other hand, there are not many studies about consumer behavior of cosmetic buying. Bloch et al (1992) implied that makeup made person more active, and an evaluation from another person lead to self-satisfaction. Fabricant (1993) pointed out that the purpose of makeup is self-expression and hiding one's fault. From the research of Coulter, et al (2000), opinion leader are more interested in cosmetics and much quantity of purchasing. Because cosmetic is very image oriented products, customer’s information sensitivity and cosmetic lifestyle are important to buy cosmetics Gathering data about channel choice behavior of consumers in Japan, it becomes clear that stylish and fashionable customers are willing to buy at department stores as their priority is channel images, while non-fashionable customers tend to buy at drugstores and GMS, as their priority is low price. It imply that stylish and fashionable score, cosmetic lifestyle of customer, and channel image are important factors for channel choice behavior of customer. Some customer use both department stores and drugstores, and some customer use both GMS and drugstores. Customers who use both department stores and drugstores are almost same lifestyle of customers who use department stores only, otherwise lifestyle scores of customers who use both GMS and drugstores are, almost same as drugstore only customers. It means that customer of department stores use drugstore as the sub channel of department stores, but customer of GMS use drugstore as the main channel. We must take care about customer combination of store channels. It becomes clear that channel images and customer lifestyle are very important to explain consumer’s channel choice.

A large body of recent research has established that word-of-mouth websites have a major impact on consumer purchases and that this trend is particularly prevalent among the young in Japan. However, prior research into consumer decision-making processes has mainly discussed the sequence of events leading up to purchase, and only a few studies have considered the generation of word-of-mouth communication. Moreover, in the empirical analyses of this research, data was mainly gathered by experiments, and a survey field to firmly gather data has not been developed. This research has two objectives: 1) To propose a new decision-making process that considers the generation of word-of-mouth communication and 2) to create and empirically demonstrate a field that can observe the generation of such communication. Specifically, the author presents a new model of the consumer decision-making process that is based on the AISAS model, a model of advertisement flow, and empirically exhibits a survey field that uses mobile phones. From the results of the analysis in this paper, the following findings were confirmed for the three consumer packaged goods (CPG) investigated: the actual existence of a decision-making process of word-of-mouth communication for the functional drink; in post-purchase behavior, a high percentage of consumers not only engage in word-of-mouth communication, but also view product official homepages; in the case of the line-extension product, while awareness is easy to obtain, only a small amount of word-of-mouth communication takes place on the Internet and even for a private-brand product, information can be spread widely by skillfully utilizing topics in the mass media. Theoretical Background Research into consumers’ decision-making processes can be broadly divided into two flows. The first is constructed from research into consumer behavior and the second from research into advertising messages. The differences between the two are that the former is advanced by investigators who are focused on attitude formation in the decision-making process, while the latter is developed by practitioners who concentrate on how information flows. The stimulation-response type and the information-processing type decision-making processes have been constructed by research into consumer behavior. In the stimulation-response type, it is thought that consumers are mobilized by external stimuli, such as advertisements, store promotions, and discounts, which ultimately cause them to make a purchase. The Howard-Sheth model that appeared in the 1960s is representative of this type, and it describes a decision-making processes that occurs when the product purchased is comparatively inexpensive and requires low participation. In contrast, the information-processing type is a decision-making process for a purchase in which the consumer actively collects information and decides on his or her attitude in achieve personal purchasing goals. It is represented by the Bettman model and describes actions taken when the product price is comparatively high and when risks exist at the time of purchase. Consumers are assumed to adopt either of these decision-making processes, depending on which is more appropriate for their particular situations, but both models mainly describe the process up to the time the purchase is made and hardly mention word-of-mouth communication after it. The area that has been being researched from the perspective of successfully communicating an advertising message to consumers has relied on the AIDMA (Attention, Interest, Desire, Memory, and Action) model that was published in 1956, which was based on the AID (Attention, Interest, and Desire) model, advocated in 1898. Searching for advertisement effects based on this flow is known to be useful in predicting consumer behavior and in corporate branding. It is widely used in the business world, since it can be usefully applied to actual businesses, but it involves hardly any empirical analysis and so is frequently used just as a concept. As described above, consumer decision-making processes have developed as two systems, but as is seen in the review, the conventional decision-making process barely touches on word-of-mouth effects after purchase. Incidentally, during the last few years in the area of advertising messages, models incorporating word-of-mouth communication after purchase have spread in Japan. A typical example is AISAS, which is an abbreviation of Attention about the product; Interest; Search, including on the Internet; Action, namely, the purchase; and Share, such as purchasers writing their impressions of the product on the Internet. Related research has established that those people who are aware of and interested in the product are more likely to listen to word-of-mouth communication and that some people tend to be more likely to listen to it than others. The SIPS model, which was developed from AISAS and assumes that word-of-mouth communication is the starting point for a purchase, is an abbreviation of Sympathize→Identify→Participate→Share & Spread. It is a model with a new paradigm in that rather than the mass media, the trigger for a purchase is word-of-mouth communication, such as a comment on Facebook. From the above, it is clear that a decision-making process for the Internet age that addresses the following points needs to be established: 1) Rather than the conventional one-way model that starts with awareness and ends with the purchase, it is necessary to consider the effects that the sharing of information after a purchase have on others who are searching for information; and 2) the decision-making process is not concluded solely within the individual, and it is necessary to consider the effects that individuals have on the market as a whole. However, in actual purchase scenes, if there are products that are bought through the proliferation of information via SNS, then, as before, there are still many purchases generated by promotions. In other words, it is thought that decision-making processes will vary according to differences in products and consumers and that these various processes coexist. Therefore, next, we will consider how these processes vary because of differences in products and consumers. Empirical Analysis For the analysis in this paper, Minrepo from Docomo Insight Marketing Inc. (DIM) was used. DIM is a joint venture between NTT Docomo Inc., which is the mobile phone company with the largest share of the Japanese market, and Intage Inc., which is Japan’s largest research company. DIM’s Minrepo is a survey and an experiment field for an SNS that uses smart phones and a mechanism by which information posted on the SNS can be confirmed. The Docomo smartphone users post reports with attached photographs of products, meals, and other items they have been used or consumed, in response to which other Docomo smartphone users click on buttons such as “Looks good” and “Wish.” Unlike Facebook, users connect loosely with people with whom they are not acquainted, and so, in actuality, its network structure is closer to that of Twitter or blogs. In addition to observing their actions, it also enables the participants to be surveyed. The current survey period was one month, July 2013, and 2,342 people participated in the survey (of whom, 1,140 were men and 1,202 were women), and a total of 19,196 reports were posted. These postings included reports on three product brands: A, a high-selling functional beverage; B, a line-extension ice bar; and C, a private-brand sweet roll. Brand A was surveyed twice via smartphone, at the beginning and at the end of the survey period. Results First, data were compiled on whether many routes existed for the decision-making processes. From these data, among the 374 people who bought brand A during the relevant period, it was found that 254 of them had some sort of awareness or interest in the product prior to their purchase, that 55 of them purchased it without thinking, and that 65 were aware of and interested in the product and had word-of-mouth communication about it prior to their purchases. Moreover, of these purchasers, 33 of them said word-of-mouth communication was the information that spurred their purchases. Many people were aware of and interested in the low-price beverage prior to their purchase of it, which might be because it is a functional beverage. The percentage of people who sent out word-of-mouth communication was slightly more than 15%, while marginally more than 10% of people were influenced by it, and it is thought that this demonstrates that it is meaningful to take word-of-mouth communication into account when considering decision-making. Next, the routes for the awareness of the three products and the consumers’ behavior after the purchase were investigated. Table 1 shows the results of this investigation. In terms of this characteristic, the awareness rate within the store was high for each of the products, but the awareness rate for brand A was often the result of the many TV commercials that were broadcast for it, while the awareness rate for brand B, which is a line-extension product, was significantly influenced by the parent brand. In contrast to these findings, the cognizance from SNS was high for brand C, and even though consumers were not subject to advertisements about it through the mass media; it was ascertained that this brand succeeded in earning awareness in stores and via SNS. Table 2 shows the consumers’ behavior after their purchases. From it, we see that much word-of-mouth communication was generated for each of the three brands, but compared to brands A and C, the volume of word-of-mouth communication generated on the Internet for brand B was extremely small. This is result is thought to reflect the fact that brand B is a brand-extension product, and so while awareness of it tends to be high, it lacks freshness to the extent that it becomes a topic on the Internet. In addition, for brand A, a large percentage of the people surveyed checked the product on the company site after their purchases of it. It is thought that this was to ascertain what was meant by it being described as functional. Finally, for brand A, the results of the surveys of the conditions before and after the experiment were compared, and the characteristics of those people who responded that they did not first send out word-of-mouth communication but did so after the experiment were investigated. From this investigation, it was ascertained that those who frequently use Twitter and Facebook and those who believe that other people expect them to be a source of information engage in word-of-mouth behavior. This shows that it is not only the product, but also the characteristics of the consumer that greatly influence word-of-mouth communication. Discussion From a review of prior research on consumers’ decision-making processes and on the flow of advertisements, this paper presents a consumer decision-making process that corresponds to the present age of a developed Internet environment. This process was confirmed with data obtained from a pseudo-Twitter world, via actual mobile phones. From this, the following findings were established: the existence of decision-making behaviors that generate word-of-mouth communication; the coexistence of conventional information-processing and stimulation-response processing, according to the product investigated; differences in behaviors for coming into contact with information prior to purchase and for transmitting and searching for information after purchase; and the greater likelihood that people who use Twitter and Facebook to engage in word-of-mouth communication.