The Effects Of Different Ugc On Users Marketing Essay

The Effects Of Different Ugc On Users Marketing Essay Since the advent of Web 2.0, social media, such as social networking sites and user-generated services, have emerged into mass use Boyd and Ellison, 2008. Academic research is starting to explore related concepts, such as social networking sites (Boyd and Ellison, 2008; Utz, 2010), user-generated content (Shao, 2009), and social media (Walker Rettberg, 2009). Basically, what characterizes user-generated content (UGC) is the fact that consumers are the ones producing, designing, publishing, or editing the content in the media (Krishnamurthy and Dou, 2008), i.e. the service is user-created. Social media in turn enable people to share and interact with each other and the content becomes more democratized (Drury, 2008). User generated content (UGC) is fast becoming one of the most valuable and influential sources of information in the on-line world, supporting millions of consumers who have come to rely on product and service reviews to support the purchase process. There is considerable interest in the value of UGC and its antecedents. Research shows that product reviews, for instance, influence consumer search and product choice, enhance sales forecast quality, affect product sales, and drive viewership (Chevalier and Mayzlin, 2006; Godes and Mayzlin, 2004; Li and Hitt, 2008). Current research on UGC has focused mainly on the motivations of consumers to produce UGC. Studies on brand-related UGC and its causality to brand perceptions is still in its infancy. It has been mentioned as part of future research to study consumers of UGC who are individuals exposed to brand-related UGC to investigate whether simply viewing rather than creating UGC may effect a change in consumer perception of brands. (Ch ristodoulides, et. al., 2012). Future research has also been suggested to distinguish between incentive- and non-incentive driven UGC and examine differences in terms of drivers and brand perceptions (Christodoulides, et. al., 2012). As consumers are increasingly performing activities previously controlled by companies, the entire marketing landscape is changing. Therefore, companies need to better understand the changing behaviour of consumers, in order to create mutual benefits from the use of social media (Heinonen, 2011). This research is an extension of current work to examine the effects of the different types of UGC on users perceptions of brands. This research is an exploratory study to address this subject by first discussing current literature on UGC and its relation to brand equity. Then, the design of the study and its results are presented and discussed. The research hopes to bring new knowledge about the positive and negative influences of UGC on brands, and highlights managerial implications for brand-related activities on online platforms containing UGC. 2 Literature Review: User Generated Content (UGC) and its growing influence in brand marketing The term social media here refers to user-created services, such as blogs, online review/rating sites, social networking sites, and online communities. The term consumer is used to describe the individual user that is active in the social media, however, not necessarily only consuming the media but also performing other activities, such as participating in, using, or producing activities.(Heinonen, 2011). Consumption means reading the content that is posted by other users; participation occurs when people comment on others creations, and production means posting ones own content on the site (Shao, 2009). In brief, information technology is empowering consumers, and their role is shifting from being passive recipients of information to becoming active generators of information (Stewart and Pavlou, 2002). Research has suggested that the classic notion of individuals as mere consumers is outdated and that consumers should also be seen as active producers of business value (Heinonen, 201 1). Marketers think that brand-related UGC is a more effective and targeted way of reaching disparate audiences than standard paid media (Lovett, 2011). The recent boom in social media provides opportunities for more targeted distribution of branded content (Lovett, 2011). Social networks are not just targeting tools but rather egalitarian and inexpensive platforms for broadcast and distribution (Lovett, 2011). Many websites such as YouTube, MySpace, Facebook, Twitter and weblogs enable consumers to easily create UGC (Dwyer, 2012). With the enormous interest in social media and user-generated content on these sites, consumers are seen to be actively contributing to the marketing content. A significant amount of UGC concerns brand-related material (Burmann and Arnhold, 2008). For example, recent evidence shows that about 70 percent of brand-related searches on social-networking sites such as YouTube, Facebook, and Twitter relate to UGC (360i, 2009). This active consumer behaviour is changing the media and marketing landscape as consumers are invading companies marketing sphere (Berthon, et al.2008). Some of the online activities performed by consumers may influence the company image and brand positively whereas other consumer activities are perhaps not favourable (Heinonen, 2011). This is explained by a finding that consumers of UGC often consider it more credible than professional content (Cheong and Morrison, 2008). Hence, negative UGC can have harmful implications for building and sustaining a brands market presence. It is, therefore, important for managers to understand the impact of UGC on brands (Berthon, et. al., 2008; Christodoulides, 2009). One of the motivation for social media activity is information processing. A key activity in information processing is sharing information and experiences, and accessing shared knowledge online. Contrary to factual information that has lower trustworthiness, opinions were considered to be reliable and value adding. It was felt that UGC is a reliable way to get opinions of products. As they do not benefit anything from advertising a certain product, producers who create product reviews are seen to be more motivated to tell the truth. When the truth is unfavourable, this may negatively impact consumers perception of a brand and their subsequent decision to use it (Heinonen, 2011). Information processing is also concerned with applying knowledge from UGC for utilitarian purposes. This activity often results in monetary benefits and economic gain. Higher levels of brand awareness and associations may prompt perceptions of choice and progress cues (Hoyer and Brown, 1990). When applying su ch knowledge appropriately, UGC may inform consumers selection of brands. Thus, we hypothesise: H1: The platform type of incentive-driven UGC has an effect on the users awareness of the sponsoring brand. H2a: The platform type of incentive-driven UGC has an effect on the users related purchasing decisions of the sponsoring brand. H2b: The users general opinion on the bias-ness of incentive-driven UCC has an effect on the difference between the effects of the platform type of incentive-driven UGC in the users related purchasing decisions of the sponsoring brand H3a: The platform type of positive incentive-driven UGC has an effect on the users evaluation of the sponsoring brand. H3b: The users general opinion on the bias-ness of incentive-driven UCC has an effect on the difference between the effects of the platform type of incentive-driven UGC in the users evaluation of the sponsoring brand. 3 Research Design and Measures This study used the uses and gratifications approach as the theoretical fundament. This method is commonly used in internet studies, see for example (Sangwan, 2005), (Papacharissi and Rubin, 2000) or (Kaye and Johnson, 2002). The approach assumes people using media actively and goal orientated and according to their needs (Katz and Blumler, 1974). This implicitly means that people know their needs and can articulate them. The uses and gratifications approach is seen to be appropriate for studying the motivations of people using media (Lin, 1996). To complement the perspective given through the uses and gratifications approach, the study used concepts common in economic theory, namely the consideration of monetary rewards and signalling incentives (Lerner and Tirole 2002). This means of data gathering has been found useful in a number of studies concerning user motivation (Lakhani and Wolf, 2005; Hars and Ou, 2002; Hippel and Lakhani, 2003). The authors develop a questionnaire to capture quantitative data administered via survey of a small sample of NTU graduate students. The chosen procedure for recruitment has the disadvantage not to be statistically representative (Ruggiero, 2000). It is therefore an exploratory study. The survey questionnaire was sent out to about 100 people, of which the return rate was 68% with 68 users. The questionnaire was in the form of an online survey, which was emailed to the randomly selected participants in the form of an embedded link. The survey was open for 2 days. Of the 68 responses, all of them were useable with no incomplete responses. The brand awareness construct was measured through one item, while the users purchasing decision of the brand construct was measured through three items. Finally, the users evaluation of the brand construct was measured through eight items. In all of the items, survey participants are asked to rank their responses based upon a 5-unit Likert scale of 1 to 5 (1- Strongly Agree; 2 Agree; 3 Neutral; 4 Disagree; 5 Strongly Disagree). For each of the dependent constructs relating to the users perceptions of brands, we calculate the sum of all the results of the survey items relating to that construct respective to each platform type (namely Facebook-related UGC or product review). Then, we begin by first conducting reliability analysis for each of the construct. A paired t-test was performed to test if there is any significant difference between the effects of the platform types of incentive-driven UGC on each of the constructs to test the postulated hypotheses. For the dependent constructs of the users related purchasing decision of the sponsoring brand, and the users evaluation of the sponsoring brand, a further linear regression analysis was performed to test if the users general opinion of the biasness of incentive-driven UGC has an effect on the difference between each platform types sum of all the results of the survey items relating to each of those dependent constructs (i.e., difference =[sum of Facebook-related survey items for construct A] [sum of product reviews-related survey items for construct A] ) 4 Results In the testing of the hypothesis H1, it is found that the difference between incentive-driven UGC on Facebook and in the form of product reviews is not statistically significant (p = 0.816, ÃŽÂ ±=0.05). Therefore, H1 is rejected. However, there is a moderate correlation between the users awareness of the sponsoring brand as a result of incentive-driven UGC on Facebook and the users awareness of the sponsoring brand as a result of incentive-driven UGC in the form of product reviews, and the Pearsons coefficient of 0.543 is significant at ÃŽÂ ± =0.05 (p In the test for the next hypothesis H2a, two analogous sets of 3 items are used; one set for measuring the construct of users related purchasing decisions with respect to incentive-driven UGC on Facebook and the other for incentive-driven UGC in the form of product reviews. In the initial reliability analysis, Cronbachs alpha for each of the Facebook and product reviews-related set of items was 0.802 and 0.891 respectively. The mean of the users related purchasing decisions as a result of incentive-driven Facebook-related UGC is 8.82, which suggests an almost neutral opinion on the average for each of the three survey items (3 = neutral). Similarly, the mean of the users related purchasing decisions as a result of incentive-driven Facebook-related UGC is 9.05, which suggests a neutral opinion on the average for each of the 3 survey items (3 = neutral). The mean of the users related purchasing decisions as a result of incentive-driven Facebook-related UGC was not significantly different from that of the users related purchasing decisions as a result of incentive-driven UGC in the form of product reviews (p =0.539, ÃŽÂ ±= 0.05). Thus, H2a is rejected. However, there is fairly moderate correlation between the two variables, and the Pearsons coefficient of 0.338 is significant (p =0.005, ÃŽÂ ±= 0.05). In the testing of the hypothesis H2b, the R2 value is 0.158, and there is a statistically significant negative linear relationship (standardised coefficient ÃŽÂ ² = -0.398) between the users opinion of the bias-ness of incentive-driven UGC and the difference in the platform types effect on the users related purchasing decisions (p = 0.001, ÃŽÂ ± = 0.05). In other words, the more the user agrees that the incentive-driven UGC are biased, the greater the positive effect that product reviews will on the users purchasing decisions than the same by Facebook-related UGC. Thus, hypothesis H2b is accepted. In the test of the hypothesis H3a, two analogous sets of 8 items are used. One set is for measuring the construct of users evaluation of brands with respect to positive incentive driven UGC on Facebook, and the other for incentive-driven UGC in the form of product reviews. Cronbachs alpha for each of the Facebook and product reviews-related set of items was 0.891 and 0.926 respectively in the reliability analysis. The mean rating of the users evaluation of the sponsoring brand as a result of Facebook-related UGC or product reviews are 22.35 and 22.94 respectively, both of which denote that the average opinion is between that of agree and neutral for each of the 8 survey items in each set. The mean of the users evaluation of brands as a result of positive incentive-driven UGC on Facebook was not significantly different from the same as a result of positive incentive-driven UGC in the form of product reviews ( p = 0.510, ÃŽÂ ± = 0.05). Thus, H3a is rejected. However, there is moderate correlation between the two variables, and the Pearsons coefficient of 0.385 is significant (p = 0.001, ÃŽÂ ± = 0.05). In the testing of the hypothesis H3b, the R2 value is 0.231, and there is a statistically significant negative linear relationship (standardised coefficient ÃŽÂ ² = -0.480) between the users opinion of the bias-ness of incentive-driven UGC and the difference in the platform types effect on the users related purchasing decisions (p 5 Analysis and Discussion In summary, there is no significant difference between the platform type of online incentive-driven UGC (whether Facebook-related UGC or UGC in the form of online product reviews) in their effects on all of i) the awareness of the sponsoring brand; ii) the users related purchasing decisions of the sponsoring brand, and; iii) the users evaluation of the sponsoring brand. However, there is a significant difference between the platform type of online incentive-driven UGC on the constructs of purchasing decisions and evaluation of the brand when the users general opinion of the bias-ness of incentive-driven UGC is taken into consideration. 5.1 When users general opinion of the biasness of incentive-driven UGC is not considered The results seem to suggest that there is no difference between the efficacy of both incentive-driven Facebook-related UGC and incentive-driven customer product reviews in furthering brand awareness. This may also hint of an overall fairly even amount of exposure that users currently have of both Facebook and websites/blogs. The lack of difference between the efficacy of both Facebook-related UGC and product reviews also seems to extend to the users related purchasing decisions of the sponsoring brand. This also seems to support the view that in fact that the users related purchasing decisions (whether their own or when advising a friend or relatives purchasing decision) had less to do with any type of UGC then the factors that they are directly exposed to when they are in a store or at the point of purchase (Edelman, 2010). Those information such as product placement, stock availability, packaging, pricing and sales interactions, are more crucial in influencing the users related purchasing decisions. Despite that, a user may still put off the purchase if they realise that the actual product is different from what is represented in other promotional materials online or offline (Edelman, 2010). The results also suggest that neither type of incentive-driven UGC, whether on Facebook or in product reviews, has a greater effect than the other in boosting the users opinion of the brand. It seems to reflect that the users acquisition of information in their evaluation of the product is multi-faceted, and does not rest solely on a single platform. 5.2 When users general opinion of the biasness of incentive-driven UGC is considered Of the 68 participants, 45.6% of them agree (36.8%) or strongly agree (8.8%) that online incentive-driven UGC are generally more biased than balanced, while a substantial 30.9 % of them are neutral on this. 41.2% of the surveyed participants also agreed or strongly agreed that extremely biased online UGC has a greater impact on their impression of the brand than moderately biased online UGC, while a significant 35.3% of the group remained neutral. The results suggest that when the user feels more strongly about the biasness of incentive-driven UGC, he has a tendency to trust the product information encapsulated within product reviews more than those reflected on Facebook contributed by other users. This might be possibly due to the more detailed textual information that the typical product review has than the average Facebook post, which tend to be more sporadic in nature. The results also support the findings in a study by McKinsey, that most consumers in the study are observed to have headed directly to Amazon.com, a major online shopping website hosted in multiple countries. There is a wealth of customer reviews on related products on the website, where customers can obtain more detailed product information and conduct their own product comparisons (Edelman, 2010). It is thus not surprising that Amazon.com is found to be one of the top influencers in brand equity, as it is where customers are influenced in both their evaluation of the product and purchasing decisions (Edelman, 2010). 5.3 Limitations and Suggestions for Future Research There are several limitations in this study. One limitation of this study is the small sample group size. Although the Cronbachs alpha in the reliability analysis was more than 0.7 for the data used in testing the hypothesis, a larger number of survey participants would allow for a more representative sample. In addition, the current study only focuses on two main platforms, namely Facebook and product reviews in blogs and websites for the studying of incentive-driven UGC. The inclusion of other platforms, such as the micro-blogging platform Twitter, and LinkedIn, a business networking platform that is gaining prominence for use in marketing companies and brands, might also have possibly shed more light on their respective effects on brand perceptions. Further, there is no specific brand that is used as a case study for this research. Sentiments may be highly mixed when responding to the survey questions as the participants are likely to have in mind different brands as their subjects for analysis. Hence, possible future work as an extension of this study could include a longitudinal study that is focused on representative brands across several product categories to analyse the efficacies of UGC on different product categories. It is also found that differences in culture and language can affect the users actions and behaviours when writing reviews, and in turn, such differences influences the disparity in product ratings creating their own online UGC related to products and brands, which in turn can influence others user perceptions of the brands in concern (Decker Trusov, 2010). Therefore, it would be useful to also study if differences in culture and language of UGC also have an effect on the users perception of brands. 6 Managerial implications The results of the current study have several implications for the marketing manager. Firstly, the lack of a difference in efficacy between Facebook-related UGC and product reviews and an average opinion that is almost neutral that either platform has influenced the user in his awareness of the sponsoring brand, showed that neither platform should be neglected by the manager in the online marketing plan when promoting a product or brand, nor should the manager put an over-emphasis of the marketing budget on these two platforms versus other online marketing mediums. Secondly, the manager may also consider allowing customer reviews on the companys own retail website for its products, if there is one. Such a feature will allow the growth of a virtual community of customers, and will also increase the time that a user spends on the website, thus boosting product sales (Mudambi Schuff, 2010). The social functions available on the retail website provide added value to the customer, and will exert a positive effect on brand equity through a more enhanced customer experience (Kumar Benbasat, 2006). 7 Conclusion