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Spreading the word through likes on Facebook. Author: Kunal Swani and George Milne, Isenberg School of Management, University of Massachusetts, Amherst, Massachusetts, USA, and Brian P. Brown Marketing Department, VCU School of Business,
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Spreading the word throughlikes on Facebook Author: KunalSwani and George Milne, Isenberg School of Management, University of Massachusetts, Amherst, Massachusetts, USA, and Brian P. Brown Marketing Department, VCU School of Business, Richmond, Virginia, USA Evaluating the message strategy effectiveness of Fortune 500 companies Teacher: 苑守慈 Presentation: Chih-Teng(Eric) Huang
Agenda • Introduction • Online WOM in social media • WOM on Facebook • Theoretical background and hypotheses development • Method • Results • Discussion and implications • Future research and limitations
Introduction • “Research is needed to understand how different consumer groups respond to different communications activities WOM marketingfor different categories and markets”, including B2B and B2C.
Introduction • Three types of message strategies based prior literature within Facebook accounts are evaluated: • (1) the use of corporate brand names; • (2) the use of emotional content; and • (3) the use/non-use of direct calls to purchase (a “hard sell” promotional approach).
Online WOM in social media • Online WOM, is defined as: • [. . .] any positive or negative statement made by potential, actual, or former customers about product or company, which is made available to a multitude of people and institutions via internet (Hennig-Thurau et al., 2004, p. 39).
Online WOM in social media • One of the most popular electronic forms of communication is one-click social plugins. • One-click social plugins differ from other online WOM forms (e.g. ratings, reviews, blogs, and emails), as users can simply share relevant content with their network of friends with one-click via a myriad of electronic devices. • Furthermore, the act of using one-click social plugins is a low cognition process compared to other deliberate social plugins(e.g. comments and blogs) which require high cognition. Thus, one-click social plugin encourage more frequent WOM .
WOM on Facebook • Levi Strauss & Company experienced a 40 percent increase in traffic to its web site. • American Eagle Outfitters found that Facebook-referred visitors spent an average of 57 percent more than those not referred by Facebook after including a Like button next to every product. • For marketers, increased liking could be impactful since a single like is estimated to generate at least $8 in revenues, and nearly one-fourth of customers indicate that they would buy the brand that their friends liked.
Theoretical background and hypotheses development • Social network theory has been used to study the relationship between strong and weak ties among the individuals (Granovetter, 1973; Brown and Reingen, 1987; Dwyer, 2007; Abrantes et al., 2013). • Strong ties are more influential than weak ones; however, weak ties seem to be more relevant during the diffusion process (Lo´pez and Sicilia, 2013). WHY?
Theoretical background and hypotheses development • Scholars found that satisfaction, loyalty, qualityand commitment to be the key drivers of WOM. Furthermore, WOM has positive outcomes such as sales, ROI, brandawareness, and customer life time value (Feng and Papatla, 2011; Stephen and Galak, 2009; Trusov et al., 2009).
Theoretical background and hypotheses development • Individuals will try to build their social identity or self-presentation by relating themselves to the brand. Hence the use of brand names in social media message becomes critical. Furthermore, the use emotional content in the brand messages may motivate individuals to express their feeling by engaging with the message.
B2B vs B2C • In B2B contexts, product offerings tend to be more technical and functional, and buyers therefore utilize a more formal, and generally longer, group buying process. • Furthermore, both buyers and sellers seek to establish long-term, collaborative relationshipsin an effort to customize solutions and mitigate risk, unlike typical end-consumers.
B2B VS B2C • A more emotional appeal should be used for a value-expressive product and a more rational appeal for a more utilitarian (technical and functional) product. In B2B contexts, offerings are more utilitarian whereas in B2C contexts, offerings are more value-expressive. • Accordingly, emotional message appeals/content tends to be most effective in consumer marketing communications.
Theoretical background and hypotheses development • H1. The relationship between a corporate brand namemessage strategy and number of likes for a message is moderated by Facebook account characteristics (B2B/B2C) such that the use of corporate brand name(s) in a message generates relatively more likes for B2B company accounts compared with B2C company accounts. • H2. The relationship between an emotional content message strategy and number of likes for a message is moderated by Facebook account characteristics (B2B/B2C) such that the use of emotional content in a message generates relatively more likes in B2C company accounts than in B2B company accounts.
Theoretical background and hypotheses development • H3. The relationship between a direct call to purchase message strategy and number of likes for a message is moderated by Facebook account characteristics (B2B/B2C) such that the use of direct calls to purchase in a message generates relatively more likes in B2C company accounts than in B2B company accounts. • H4. The relationship between a corporate brand name strategy and number of likes for a message is moderated by Facebook account characteristics (product/service) such that the use of corporate brand names in a message generates relatively more likes in service company accounts than in a product company accounts.
Theoretical background and hypotheses development • H5. The relationship between an emotional content strategy and number of likes for a message is moderated by Facebook account characteristics (product/service) such that the use of emotional content in a message generates relatively more likes in service company accounts than in product company accounts. • H6. The relationship between use of direct calls to purchase and number of likes for a message is not moderated by Facebook account characteristics (product/service).
Method - data • Our data is drawn from 280 Fortune 500 companies’ Facebook wall posts. This list was based on Barnes (2010). Given that some companies have multiple Facebook accounts, we actually followed 303 accounts. These 303 accounts were tracked for one week (March 29, 2011-April 4, 2011), resulting in 1,146 unique company wall posts from 195 Facebook accounts that were active during this time period. HOW?
Method – control variables • We added message time and fanbase variables in our model to control for time and fan effects. Message time is operationalized as the time when the message was sent out to the time when the data was archived. The number of likes for a message will be influenced by the message time. We anticipate a positive relationship between message time and message likes. As the message time increases so should message likes. Furthermore, fanbases are expected to have a positive influence on message likes. We expect that accounts with larger fanbases will have more likes for their messages.
Method – Model • The dependent variable for our analysis was the number (counts) of Likes for a message and the messages were nested within Facebook accounts justifying the use of HLM analysis. We used a random coefficient Level 2 HLM Poisson model with messages (Level 1) nested in Facebook accounts (Level 2) to test our hypotheses. Because of the skewed distribution of message Likes, we ran a Poisson distribution with an equal exposure rate with message time (transformed as square root) as the Level 1 covariate and fanbase (transformed as natural log) as the Level 2 covariate. Refer to Appendix 2 for model specifications.
Discussion and implications • The inclusion of emotional sentiments in message posts is particularly effectiveat generating likes for B2C-service accounts and B2B accounts. • Messages that combineacorporate brand name andanemotional appeal appear to be the most effective message strategy for B2B Facebook accounts.
Discussion and implications • We believe that the buyers are more likely to process social media content under low involvement/attentionconditions which signifies the importance and use of brand emotions. • Communicating emotional brand values may enhance the potential for value creation, foster buyer supplier relationship and be a means of developing a sustainable differential advantage.
Future research and limitations • First, our findings are not necessarily generalizable to small businesses and specific industries because of our database of Fortune 500 accounts. • Second, the message strategies used in our study are limited. Future studies should investigate message strategies that involve the use of functional content, videos and images, and product brand names. • Third, the data for analysis consisted of one week of message posts. Hence, it is unlikely that our analysis captured changes in message strategies that might be evident over time.
Future research and limitations • Furthermore, the results in terms of magnitude might have changed as the number of fans and social media users is generally increasing at an exponential rate. • Finally, we did not consider the level of user involvement/attention when processing social media messages. Future research should study the level of involvement to understand how different customers of different markets and offering types process information when using social media.
