University of Groningen
Effects of Traditional Advertising and Social Messages on Brand-Building Metrics and
Customer Acquisition
De Vries, Lisette ; Gensler, Sonja; Leeflang, Pieter
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Journal of Marketing
DOI:
10.1509/jm.15.0178
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De Vries, L., Gensler, S., & Leeflang, P. (2017). Effects of Traditional Advertising and Social Messages on
Brand-Building Metrics and Customer Acquisition.
Journal of Marketing
,
81
(5), 1-15.
https://doi.org/10.1509/jm.15.0178
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Lisette de Vries, Sonja Gensler, & Peter S.H. Leeflang
Effects of Traditional Advertising and
Social Messages on Brand-Building
Metrics and Customer Acquisition
This study examines the relative effectiveness of traditional advertising, impressions generated through firm-to-
consumer (F2C) messages on Facebook, and the volume and valence of consumer-to-consumer (C2C) messages on
Twitter and web forums for brand-building and customer acquisition efforts. The authors apply vector autoregressive
modeling to a unique data set from a European telecom firm. This modeling approach allows them to consider the
interrelations among traditional advertising, F2C impressions, and volume and valence of C2C social messages. The
results show that traditional advertising is most effective for both brand building and customer acquisition. Impressions
generated through F2C social messages complement tradi tional advertising efforts. Thus, thoroughly orchestrating
traditional advertising and a firm’s social media activities may improve a firm’s performance with respect to building
the brand and encouraging customer acquisition. Moreover, firms can stimulate the volume and valence of C2C
messages through traditional advertising that in turn influences br and building and acquisition. These findings can
help managers leverage the different types of messages more adequately.
Keywords: traditional advertising, social media, brand building, customer acquisition, vector autoregressive modeling
Online Supplement: http://dx.doi.org/10.1509/jm.15.0178
E
very year, U.S. firms invest approximately $130 billion
in traditional advertising (e.g., television, radio, print,
and outdoor) to build their brands and increase sales
(eMarketer 2014). Yet empirical evidence has suggested that
firms are gradually shifting their traditional advertising in-
vestments to, for example, social media to pursue similar
objectives (eMarketer 2016; H udson et al. 2016; Statista
2016). Many firms have established a social media presence
by operating pages on social networking sites such as Face-
book. Firms post messages on these pages to interact wit h
consumers by exploiting the n etwork stru cture and to ulti-
mately build the brand and stimulate sales (De Vries, Gensler,
and Leeflang 2012). W e call these posts firm-to-consume r
(F2C) social messages.
To leverage these messages, managers need to know how
effective F2C social messages are for building the brand and
influencing consumer behavior. Previous research has shown
that F2C social messages have a positive effect on existing
customers’ expenditures (e.g., Goh, Heng, and Lin 2013;
Kumar et al. 2016). However, we lack knowledge about the
effectiveness of firms’ social media activities in comparison to
their traditional advertising investments. Moreover, we know
little about potential complementary effects of F2C social
messages and traditional advertising (Kumar et al. 2016). Such
knowledge is, however, critical for managers to leverage and
orchestrate traditional advertising and F2C social messages
effectively (Chen and Xie 2008; Edelman 2010). Furthermore,
previous studies have focused on the impact of F2C social
messages on existing customers’ behavior but have not in-
vestigated the potential impact on new customer acquisition.
In addition to a firm’s own efforts to build the brand and
affect consumer behavior, it is well known that messages
initiated by consumers influence other consumers (e.g., Babi
´
c
Rosario et al. 2016; Hennig-Thurau, Wiertz, and Feldhaus
2015; You, Vadakkepatt, and Joshi 2015; Zhu and Zhang
2010). Such messages can be product reviews as well as
messages posted on forums, microblogs (e.g., Twitter), brand
communities, and other social media sites. We call messages
that are initiated by consumers and targeted to other con-
sumers consumer-to-consumer (C2C) social messages. Man-
agers need a clear understanding of the effects of C2C social
messages on the brand and consumer behavior relative to the
impac t o f their o w n effort s. M o re ov er , m an a ger s need t o
know whether their own communication activities affect C2C
social messages because this woul d allow them to exert some
influence on what consumers say about the brand. Previous
studies that compare traditional advertising and C2C social
messages have indicated that C2C social messages can be
more effective for increasing sales and customer acquisi-
tion (e.g., Trusov, Bucklin, and Pauwels 2009). Moreover,
these studies have suggested that traditional advert ising and
Lisette de Vries, Store Support BV, Amsterdam (e-mail: lisettede_vries@
hotmail.com). Sonja Gensler (corresponding author), Marketing Center
M¨unster, University of M¨unster (e-mail: s.gensler@uni-muenster.de). Peter
S.H. Leeflang is Frank M. Bass Distinguished Professor of Marketing,
University of Groningen, and Honorary Professor, Aston Business School,
Aston University (e-mail: p.s.h.leeflang@rug.nl). The authors are listed in
alphabetical order. The authors thank Nielsen and an anonymous telecom
firm for providing data, and the JM review team for constructive feedback.
Special thanks go to Thorsten Wiesel for his valuable feedback and sug-
gestions. Praveen Kopalle served as area editor for this article.
© 2017, American Marketing Association Journal of Marketing
ISSN: 0022-2429 (print) Vol. 81 (September 2017), 1–15
1547-7185 (electronic) DOI: 10.1509/jm.15.01781
consumer messages are complements (Fossen and Schweidel
2017; Gopinath, Thomas, and Krishnamurthi 2014). Yet few
studies have considered C2C and F2C social messages jointly,
and the findings of these studies with respect to the effec-
tiveness of these messages are mixed (Goh, Heng, and Lin
2013; Kumar et al. 2013). To date, no empirical research has
considered traditional advertising, F2C social messages, and
C2C social messages simultaneously to compare th e effec-
tiveness of the different types of messages. Thus, we also have
little knowledge about the interrelations among the different
messages, though there is no doubt that such interrelations are
likely to exist (Hewett et al. 2016).
The aim of this study is to close this gap in the literature by
examining the relative effectiveness of traditional advertising,
F2C social messages, and C2C social messages for both brand
building and customer acquisition over time, and to study the
interrelations among the different messages. We focus on
customer acquisition because it is a critical performance mea-
sure that has just recently received more attention (Katsikeas
et al. 2016). By considering customer acquisition (i.e., number
of new customers), we are able to study the behavioral outcomes
of traditional advertising, F2C social messages, and C2C social
messages. By a ccounti ng for brand -buildi ng metrics ( i.e.,
consumers’ brand awareness, consideration, and preference),
we can examine both indirect and direct effects of the dif-
ferent messages on customer acquisition (Bruce, Peters, and
Naik 2012).
We collected a unique data set from a European telecom
firm (which maintains contractual relationships with con-
sumers) and Nielsen that contained weekly data on traditional
advertising, F2C social messages, and C2C social messages
over 119 weeks. We also have weekly information about
brand-building metrics and customer acquisition. The tradi-
tional advertising measure comprises the firm’s joint expen-
ditures on television, radio, print, and outdoor advertising.
The n umber of impressions of firm-initiated messages on
Facebook based on likes, comments, and shares of the firm’s
original messages represent F2C social messages. We there-
fore use the term F2C impressions when describing and dis-
cussing the results of the empirical study. The impressions
provide information about the spreading of a firm’smessage.
We consider Facebook because it is the firm’s main social
media platform to communicate with consumers. Consumer-to-
consumer social messages include the number (C2C volume)
and valence (C2C valence) of messages initiated by consumers
about the firm on Twitter and th e most popular forums in the
country where the focal firm operates. We do not consider online
reviews because the content of the reviews is mostly about
phones and less about the specific services offered by the focal
firm. By taking C2C social messages on Twitter and forums
into account, we cover the majority of C2C social messages
about the focal firm.
To elicit the effectiveness of traditional advertising, F2C
impressions, and C2C social messages (C2C volume and C2C
valence), we use vector autoregressive (VAR) modeling. This
methodology allows us to determine the relative effectiveness
of traditional advertising, F2C impressions, and C2C social
messages by computing their elasticities for the brand-building
metrics and customer acquisition on the basis of impulse
response function (IRF) analyses (e.g., Dinner, Van Heerde,
and Neslin 2014). In addition, the VAR model approach enables
us to examine the in terrelations among traditional advertising,
F2C impressions, and C2C social messages (Hewett et al. 2016).
With our work, we contribute to the extant literature in
several ways. First, we consider traditional advertising, im-
pressions generated through F2C social messages, and C2C
social messages simultaneously and compare their effec-
tiveness. Second, we elaborate on the complementary effects
of and interrelations among traditional advertisin g, F2C
impressions, and C2C social messages. Third, we take both
brand-building and behavioral metrics into account to assess
the effectiveness of the different messages over time. Using
brand-building and behavioral metrics allows us to address
current calls to consid er multipl e performance metrics at
different levels to derive more insightful managerial impli-
cations (Katsikeas et al. 2016). Accordingly, our study is more
comprehensive than previous studies and allows for richer
insights that help managers to orchestrate t he different
messages effectively.
The results show that the different messages are effective
in building a brand and enhancing customer acquisition. With
respect to building a brand, traditional advertising is most
effective in creating awareness and consideration. However,
C2C valence is most effective in spurring preference. Tra-
ditional advertising is again mos t effective in enhancin g
customer acquisition, followed by F2C imp ressions an d C2C
volume. The results suggest that the firm’ssocialmedia
activities complement its traditional advertising efforts. In
addition, traditional advertising enhances the volume and
valence of C2C social messages, which in turn spur con-
sumers’ preference and acquisition. Given the effectiveness
of tradi tional a dvertising, managers should carefully trade
off its effectiveness and costs (i.e., efficiency) when maki ng
marketing investment decisions.
In the next section, we elaborate on previous research
related to our study and highlight the need for an empirical
study that addresses the gap in research. Then, we describe our
data and introduce the modeling approach. Subsequently, we
present and elaborate on the empirical findings. Finally, we
conclude with a discussion of the study’s implications, lim-
itations, and research opportunities.
Previous Research on the
Effectiveness of Traditional
Advertising, F2C Social Messages,
and C2C Social Messages
The effectiveness of traditional advertising, F2C, and C2C
social messages can be assessed by examining their impact
on brand-building and behavioral outcomes. Brand aware-
ness, consideration, and preference are three commonly
used metrics to evaluate the effects on brand building (e.g.,
Draganska, Hartmann, and Stanglein 2014; Srinivasan,
Vanhuele, and Pauwels 2010). Recent studies have dem-
onstrated the brand-building and sales capabilities of a single
type of message—traditional advertising (e.g., Sethuraman,
Tellis, and Briesch 2011; Srinivasan, Vanhuele, and Pauwels
2 / Journal of Marketing, September 2017
2010), C2C social messages (e.g., Hennig-Thurau, Wiertz,
and Feldhaus 2015), and F2C social messages (e.g., Goh,
Heng, and Lin 2013; Hutter et al. 2013; Kumar et al. 2016;
Rishika et al. 2013). Yet research considering more than just
one type of message is scarce, as we illustrate in Table 1.
Some studies compare the effectiveness of traditional
advertising and C2C social messa ges (Table 1). No te that
these studies also contain other forms of C2C social messages
than the ones we consider. The results of these studies indicate
that C2C messages are more effective than traditional
advertising at generating sales for m icrolending loa ns
(Stephen and Galak 2012) and acquiring customers for a web
hosting service (Villanueva, Yoo, and Hanssens 2008) or
a social network (Trusov, Bucklin, and Pauwels 2009).
Moreover, C2C social messages and traditional advertising
work as complements for enhancing sales of cell phone
introductions (Gopinath, Thomas, and Krishnamurthi 2014)
and movies (Bruce, Foutz, and Kolsarici 2012; Onishi and
Manchanda 2012). Overall, these studies suggest that C2C
social messages may be more effective than traditional ad-
vertising in stimulating sales and acquisitions. However, we
lack knowledge on the relative effectiveness of traditional
advertising and C2C social messages to b uild a brand.
Very few studies that consider F2C social messages take
other messages into account (Table 1). Comparing F2C and
C2C social messages, Goh, Heng, and Lin (2013) find that
C2C social messages are more effective than F2C social
messages for evoking apparel purchases.
1
Kumar et al. (2013)
show that F2C social messages lead to substantially more
C2C social messages, which, in turn, affect sales of an ice
cream store. The study shows the viral capacities of F2C social
messages and that different types of social messages can
enhance one another. Kumar et al. (2016) find that F2C social
messages have positive effects on retail sales, even when
controlling for traditional advertising. Overall, the studies on
F2C social messages provide scattered insights into the
relative effectiveness of these messages on behavioral out-
comes and do not provide any insights into the relative effects
on brand building.
The discussion of previous studies shows that there are
two major gaps in the literature: (1) no simultaneous as-
sessment of the relative effectiveness of traditional adver-
tising, F2C social messages, and C2C social messages and
(2) a lack of knowledge of the effects of these messages on
brand-building metrics. Yet it is important to consider tra-
ditional advertising, F2C social messages, and C2C social
messages jointly because the different messages are omni-
present today and are likely to affect consumers simulta-
neously. Moreover, the different messages are part of the
“echoverse,” that is, the communications environment of a
firm (Hewett et al. 2016). Thus, we need to acknowledge that
the different message types might influence one another. For
example, a recent study by Fossen and Schweidel (2017)
suggests that traditional advertising positively affects the
volume of C2C social messages about the advertised brand.
Firms generally do not have much influence on what con-
sumers talk about online (C2C social messages), but if
traditional advertising affects C2C social messages, firms
actually do have a tool to influence these messages indirectly.
Firms might plan their F2C social messages in accord with
their traditional advertising activities or vice versa. Moreover,
F2C social messages might stimulate consumers to talk about
the brand on other social media sites (e.g., Kumar et al. 2013).
Because previous studies have considered only a limited set of
messages, we lack insights into the interrelations among the
different messages. Knowledge about these interrelations,
however, enables managers to exert greater influence on the
echoverse and, finally, on critical performance metrics.
Table 1 also shows that current studies have considered only
behavioral performance measures, thereby simply treating in-
tervening processes as a “black box” (Srinivasan, Vanhuele, and
Pauwels 2010). Accounting for brand-building metrics, how-
ever, allows for exami ning both indirect and dir ect effec ts
of messages on customer acqui sition (Bruce, Peters, and
Naik 2012). Considering brand-building metrics alongside
behavioral metrics helps managers better understand the
full effects of the differe nt messa ges.
TABLE 1
Overview on Studies Considering More Than One Type of Message
Authors
Traditional
Advertising C2C F2C
Brand-Building
Metrics Sales Acquisition
Bruce, Foutz, and Kolsarici 2012 + Online reviews +
Fossen and Schweidel 2017 + Twitter
Gopinath, Thomas, and Krishnamurthi 2014 + Forum +
Onishi and Manchanda 2012 + Blog +
Stephen and Galak 2012 + Blog, community +
Trusov, Bucklin, and Pauwels 2009 + WOM referrals +
Villanueva, Yoo, and Hanssens 2008 + WOM referrals +
Goh, Heng, and Lin 2013 Facebook community ++
Kumar et al. 2013 WOM +++
Kumar et al. 2016 +++
This study + Microblog, forums ++ +
Notes: The plus signs indicate that the study considered the specific variable.
1
Rishika et al. (2013) consider both firm and consumer messages
in a firm-initiated social media community, but they aggregate the
messages and, thus, do not distinguish between the two types of
messages.
Traditional Advertising and Social Messages on Brand Building / 3
Because previous studies have provided only scattered
insights into the relative effectiveness of the different mes-
sages, it is difficult to form expectations beforehand. Thus,
we refrain from formulating propositions. We rather provide
empirical insights into the relative effectiveness of the dif-
ferent message types (i.e., traditional advertising, F2C social
messages, and C2C social messages) on brand-building and
behavioral outcomes and the interrelations among these
messages.
Empirical Application
Data
We use contractual data on customer acquisition from a
European telecom firm related to its activities in one European
country. Moreover, we obtained data from the firm’s social
listening tool on C2C social messages and data from its
Facebook page to measure F2C impressions. We combine
these data with Nielsen data on traditional advertising and
complement all data with survey panel data from an external
company on brand-building metrics. The data period ranges
from week 30 in 2011 to week 44 in 2013, with all data reported
on a weekly basis. Table 2 contains a detailed overview of all
variables, their descriptions, measures, and sources.
The focal brand was one of the top five telecom providers
in the market of mobile subscription plans in the specific
country at the time of the study. There were f our main
competitors, which, t ogether with the focal brand, had a
combined market share of approximately 80%. However, the
focal brand was not the largest of these five brands because
of its specific target group, which comprises young adults
between 16 and 30 years old—a target group that is connected
through social media and uses online media actively (Statista
2014). We have information from the survey panel that
approximately 80% of the target group had a Facebook
account and that about 60% logged in to their account daily.
At the time of the study, the firm had the largest Facebook
page in the country with respect to the number of “brand fans”
(on average, 100,000 consumers). The firm actively used
traditional advertising, and the average number of weekly
impressions was approximately 436,881.
2
Traditional advertising. We use joint gross media ex-
penditures on TV, print, radio, and out-of-home to measure
traditional advertising investments (Table 2). Nielsen does not
directly observe how much firms actually spend on traditional
advertising through TV, print, radio, and out-of-home because
firms are reluctant to provide this information. Therefore,
Nielsen measures advertising expenditures indirectly, using
public and national television channels, and provides data
about commercials according to their gross rating point tariffs
(i.e., excluding discounts and price negotiations).
F2C impressions. We use t he weekly number of viral
impressions of the firm’s posts on Facebook (Table 2). This
number considers impressions of the focal firm’spostson
Facebook when consu mers like, comm ent on, or share the
messages with each other. We consider vi ral impressions
because they reflect the spreading activity through the network:
those impressions might be particularly effective for building
a brand and generating acquisitions.
The focal brand’ s original F2C messages contain pro-
motional messages about phones, subscriptions, or ser vice
offers of the focal firm but also information unrelated to
the category such as recommendations for going out and
sweepstakes. In general, F2C social messages are positive,
but shared F2C social messages may have different content
and may differ in vale nce fro m the original message if
consumers comment negatively. We do not have infor-
mation about the valence of shared F2C social messages,
but previous research has shown that the share of n egative
comments to firms’ postsisrathersmall(DeVries,Gensler,
and Leeflang 2012). We do not consider any consumer-
initiated conversations about the firm on Facebook. Such
messages woul d be C2C soci al messag es accord ing to our
definitions, and the focal firm has no information about C2C
social messages posted on Facebook.
C2C social messages. We measure the volume (i.e.,
number) and valence of messages initiated by consumers on
forums and Twitter, whereby Twitter accounts for the largest
part. Thus, we consider specific types of C2C social messages.
Yet Twitter and the most popular forums capture the majority
of C2C social messages about the focal firm according to
conversations with the man agement. The number of C2 C
social messages reflects the chance of consumers seeing these
messages ( i.e., the more C2C social messages are posted,
the greater the likelihood that consumers will see them).
The valence of C2C social messages echoes the sentiment i n
the marketplace and is the difference in shares of positive
and negative messages (Table 2). The values for the valence
measure range between -1and+1, where -1(+1) indicates that
no positive (negative) but only negative (positive) messages are
posted in a certain week. If valence is equal to zero, there are as
many positive as negative messages posted.
Brand-building metrics and customer acquisition. A
third-party organization gathereddataondifferentbrand-
building metrics related to the brand: unaided brand aware-
ness, consideration, and preference (Table 2). The share of
consumers who mention the focal brand spontaneously as a
brand operating in the specific industry measures unaided
brand awareness. Brand consideration is the share of con-
sumers who would consider the focal brand for a given
purchase occasion. Brand preference is the share of consumers
who prefer the focal brand to competing brands. Each week,
this organization interviews 130 target consumers (i.e., young
adults), producing an accumulated 15,470 interviews (some
consumers might be interviewed more than o nce) over
119 weeks. The samp le is not random but targeted and
weighted. Over the weeks, the demographic characteristics of
the panel members remain the same. Previous studies con-
sidering brand-building metrics used similar samples (Bruce,
Peters, and Naik 2012; Srinivasan, Vanhuele, and Pauwels
2010). Customer acquisition is the number of newly acquired
customers per week (Table 2).
2
We derived the number of impressions from the ad spending and
the cost per thousand impressions.
4 / Journal of Marketing, September 2017
