90
Journal of Marketing
Vol. 73 (September 2009), 90–102
© 2009, American Marketing Association
ISSN: 0022-2429 (print), 1547-7185 (electronic)
Michael Trusov, Randolph E. Bucklin, & Koen Pauwels
Effects of Word-of-Mouth Versus
Traditional Marketing: Findings from
an Internet Social Networking Site
The authors study the effect of word-of-mouth (WOM) marketing on member growth at an Internet social networking
site and compare it with traditional marketing vehicles. Because social network sites record the electronic invitations
from existing members, outbound WOM can be precisely tracked. Along with traditional marketing, WOM can then
be linked to the number of new members subsequently joining the site (sign-ups). Because of the endogeneity
among WOM, new sign-ups, and traditional marketing activity, the authors employ a vector autoregressive (VAR)
modeling approach. Estimates from the VAR model show that WOM referrals have substantially longer carryover
effects than traditional marketing actions and produce substantially higher response elasticities. Based on revenue
from advertising impressions served to a new member, the monetary value of a WOM referral can be calculated;
this yields an upper-bound estimate for the financial incentives the firm might offer to stimulate WOM.
Keywords: word-of-mouth marketing, Internet, social networks, vector autoregression
Michael Trusov is Assistant Professor of Marketing, Robert H. Smith
School of Business, University of Maryland (e-mail: mtrusov@rhsmith.
umd.edu). Randolph E. Bucklin is Peter W. Mullin Professor, Anderson
School of Management, University of California, Los Angeles (e-mail:
rbucklin@anderson.ucla.edu). Koen Pauwels is an associate professor,
Ozyegin University, Istanbul, and Associate Professor of Business
Administration, Tuck School of Business, Dartmouth College (e-mail:
koen.pauwels@ozyegin.edu.tr and koen.h.pauwels@dartmouth.edu). The
authors thank the three anonymous JM reviewers and participants of the
2006 Marketing Dynamics Conference and the 2007 DMEF Research
Summit for helpful comments. The authors are also grateful to the anony-
mous collaborating firm for providing the data used in this study. Katherine
N. Lemon served as guest editor for this article.
Word-of-mouth (WOM) marketing has recentlyattracted a great deal of attention among practi-tioners. For example, several books tout WOM as
a viable alternative to traditional marketing communication
tools. One calls it the world’s most effective, yet least
understood marketing strategy (Misner 1999). Marketers
are particularly interested in better understanding WOM
because traditional forms of communication appear to be
losing effectiveness (Nail 2005). For example, one survey
shows that consumer attitudes toward advertising plum-
meted between September 2002 and June 2004. Nail (2005)
reports that 40% fewer people agree that advertisements are
a good way to learn about new products, 59% fewer people
report that they buy products because of their advertise-
ments, and 49% fewer people find that advertisements are
entertaining.
Word-of-mouth communication strategies are appealing
because they combine the prospect of overcoming con-
sumer resistance with significantly lower costs and fast
delivery—especially through technology, such as the Inter-
net. Unfortunately, empirical evidence is currently scant
regarding the relative effectiveness of WOM marketing in
increasing firm performance over time. This raises the need
to study how firms can measure the effects of WOM com-
munications and how WOM compares with other forms of
marketing communication.
Word-of-mouth marketing is a particularly prominent
feature on the Internet. The Internet provides numerous
venues for consumers to share their views, preferences, or
experiences with others, as well as opportunities for firms
to take advantage of WOM marketing. As one commentator
stated, “Instead of tossing away millions of dollars on
Superbowl advertisements, fledgling dot-com companies
are trying to catch attention through much cheaper market-
ing strategies such as blogging and [WOM] campaigns”
(Whitman 2006, p. B3A). Thus, it is important to under-
stand whether WOM is truly effective and, if so, how its
impact compares with traditional marketing activities.
One of the fastest-growing arenas of the World Wide
Web is the space of so-called social networking sites. A
social networking site is typically initiated by a small group
of founders who send out invitations to join the site to the
members of their own personal networks. In turn, new
members send invitations to their networks, and so on.
Thus, invitations (i.e., WOM referrals) have been the fore-
most driving force for sites to acquire new members. As
social networking sites mature, they may begin to increase
their use of traditional marketing tools. Therefore, manage-
ment may begin to question the relative effectiveness of
WOM at this stage.
The objective of this research is to develop and estimate
a model that captures the dynamic relationships among new
member acquisition, WOM referrals, and traditional mar-
keting activities. In doing so, we offer several contributions.
First, we are among the first to link observed WOM directly
to new customer acquisition. Second, we show how to

Word-of-Mouth Versus Traditional Marketing / 91
incorporate both the direct effects and the indirect effects of
WOM and traditional marketing actions (e.g., a marketing
action increases WOM activity, which in turn increases new
member acquisition). We empirically demonstrate, for our
data set, the endogeneity among new member sign-ups and
these marketing variables. This highlights the need to
account for these indirect effects to avoid biased estimates
for both WOM and traditional marketing effects. Third, we
quantify and contrast the immediate and long-term elas-
ticities of WOM and traditional marketing actions. In par-
ticular, we document strong carryover effects for WOM in
our data. Finally, we attach an estimated monetary value to
each WOM referral, providing an upper bound to the finan-
cial incentive management might consider offering for
WOM referrals. Indeed, the practice of seeding or stimulat-
ing WOM has grown rapidly, but quantifying the effective-
ness of this activity remains difficult (e.g., Godes and May-
zlin 2004).
We organize the remainder of this article as follows: We
begin by summarizing previous research to help put our
contributions in perspective. We then describe our modeling
approach. Next, we present our empirical analysis of the
data from a collaborating Internet social networking site
and offer implications for theory and managers. In particu-
lar, we find that WOM referrals strongly affect new cus-
tomer acquisitions and have significantly longer carryover
than traditional forms of marketing used by the firm (21
days versus 3 to 7 days). We estimate a long-term elasticity
for WOM of .53—approximately 20–30 times higher than
the elasticities for traditional marketing.
Research Background
To help put the intended contribution of this study in con-
text, we briefly review previous empirical research on the
effectiveness of WOM marketing. In Table 1, we present a
comparison chart of selected prior work. As the table
shows, researchers have used a variety of means to capture,
infer, or measure WOM. The table also outlines findings for
the effect of WOM on customer acquisition, comparisons
with traditional marketing, and incorporation of indirect
effects.
The earliest study on the effectiveness of WOM is sur-
vey based (Katz and Lazarsfeld 1955) and was followed by
more than 70 marketing studies, most of them also inferring
WOM from self-reports in surveys (Godes and Mayzlin
2004; Money, Gilly, and Graham 1998). Researchers have
examined the conditions under which consumers are likely
to rely on others’ opinions to make a purchase decision, the
motivations for different people to spread the word about a
product, and the variation in strength of people’s influence
on their peers in WOM communications. Moreover, cus-
tomers who self-report being acquired through WOM add
more long-term value to the firm than customers acquired
through traditional marketing channels (Villanueva, Yoo,
and Hanssens 2008).
Social contagion models (e.g., Coleman et al. 1966)
offer an alternative perspective, typically inferring WOM/
network effects from adoption behavior over time. Although
a social contagion interpretation of diffusion patterns is
intuitively appealing, recent studies have pointed out that
such inferences can be due to misattribution. For example,
when Van den Bulte and Lilien (2001) reestimated Coleman
and colleagues’ (1966) social contagion model for physi-
cian adoption of tetracycline, they found that the contagion
effects disappeared when marketing actions were included
in the model. This raises the question whether WOM effects
would have been significant in the model had there been
data available on the actual transmission of information
from one physician to another.
Both of these research approaches do not observe actual
WOM but infer it from self-reports or adoption. Examining
WOM on the Internet can help address this limitation by
offering an easy way to track online interactions. Godes and
Mayzlin (2004) suggest that online conversations (e.g.,
Usenet posts) can offer an easy and cost-effective way to
measure WOM. In an application to new television shows,
they link the volume and dispersion of conversations across
different Usenet groups to offline show ratings. Chevalier
and Mayzlin (2006) use book reviews posted by customers
at Amazon.com and Barnesandnoble.com online stores as a
proxy for WOM. They find that though most reviews were
positive, an improvement in a book’s reviews led to an
increase in relative sales at the site, and the impact of a
negative review was greater than the impact of a positive
one. In contrast, Liu (2006) shows that both negative and
positive WOM increase performance (box office revenue).
Although the foregoing three studies observe the post-
ing of reviews (i.e., sending WOM), they do not directly
observe the reception of WOM. In contrast, De Bruyn and
Lilien (2008) observe the reactions of 1100 recipients after
they received an unsolicited e-mail invitation from one of
their acquaintances to participate in a survey. They find that
the characteristics of the social tie influenced recipients’
behaviors but had varied effects at different stages of the
decision-making process. They also report that tie strength
exclusively facilitated awareness, perceptual affinity trig-
gered recipients’ interest, and demographic similarity had a
negative influence on each stage of the decision-making
process. However, this study does not compare the effec-
tiveness of WOM with that of traditional marketing actions,
nor does it quantify the monetary value of WOM to the
company.
The current article differs from these studies in both
research objective and application. A key research objective
in this study is to compare the effects of observed WOM
referrals with those of traditional marketing efforts. Quanti-
fying the full effects of WOM referrals and marketing
requires us (1) to account for the potential endogeneity
among these communication mechanisms and (2) to
account for their potential permanent effects on customer
acquisition. First, WOM may be endogenous because it not
only influences new customer acquisition but also is itself
affected by the number of new customers. Likewise, tradi-
tional marketing activities may stimulate WOM; they
should be credited for this indirect effect and the possible
direct effect on customer acquisition. Second, all these
communication mechanisms may have permanent effects
on customer acquisition. For example, WOM may be
passed along beyond its originally intended audience and