SPREADING THE WORD
THROUGH
LIKES ON FACEBOOK
EVALUATING THE MESSAGE STRATEGY
EFFECTIVENESS OF FORTUNE 500 COMPANIES
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,
Richmond, Virginia, USA
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
marketing for 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, oneclick 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.
WOM ON FACEBOOK
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, quality and
commitment to be the key drivers of WOM. Furthermore,
WOM has positive outcomes such as sales, ROI, brand
awareness, 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 longterm, collaborative relationships in an effort to
customize solutions and mitigate risk, unlike typical endconsumers.
B2B VS B2C
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 valueexpressive.
Accordingly, emotional message appeals/content tends to be
most effective in consumer marketing communications.
PRODUCT VS
SERVICE ACCOUNTS
THEORETICAL BACKGROUND AND
HYPOTHESES DEVELOPMENT
H1. The relationship between a corporate brand name
message 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 – CONTENT ANALYSIS
METHOD –
DESCRIPTIVE STATISTICS
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.
RESULTS
RESULTS
RESULTS
RESULTS
RESULTS
RESULTS
DISCUSSION AND IMPLICATIONS
The inclusion of emotional sentiments in message
posts is particularly effective at generating likes for B2C-service
accounts and B2B accounts.
corporate brand name and
an emotional appeal appear to be the most effective
Messages that combine a
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/attention
conditions 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.