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The effect of social media and advertising activities
on affiliate marketing
Rainer Olbrich, Carsten D. Schultz* and
Patrick M. Bormann
University of Hagen,
Universitätsstraβe 11,
58097 Hagen, Germany
Abstract: The study uses data from a service company to analyse if social
media and advertising activities affect affiliate marketing results. The dataset
spans a six month period, registering 611,081 ad impressions, 15,082 clicks,
and 2,672 social media messages. The results from affiliates using social media
are analysed and then compared to the results of affiliates not using social
media. The study adds to the affiliate marketing literature by analysing the used
ad media, commission amount, length of partnership, and business focus as
campaign variables. Further, it adds to the multichannel literature:
microblogging social media activities of affiliates positively affect the number
of ad impressions and to a lesser extent the number of affiliate leads. As social
media activities of affiliates affect the results of the affiliate marketing
campaign, merchants may include social media data to get a more detailed
picture of affiliate activities and performances.
Keywords: advertising; ad impressions; affiliate marketing; business focus;
clicks; commission amount; leads; length of partnership; microblogging;
multichannel advertising; social media; social media messages; social media
reach.
Reference to this paper should be made as follows: Olbrich, R., Schultz, C.D.
and Bormann, P.M. (2019) ‘The effect of social media and advertising
activities on affiliate marketing’, Int. J. Internet Marketing and Advertising,
Vol. 13, No. 1, pp.47–72.
Biographical notes: Rainer Olbrich is a Professor of Marketing at the
University of Hagen, Germany. He completed his doctoral thesis in 1992 at the
Department of Marketing, University of Münster, where he also finished his
postdoctoral thesis. Since 1997, he has been holding the Chair of Marketing at
the University of Hagen. He has worked as a consultant for various companies
and organisations. His research interests include consumer goods marketing,
retail marketing, and online marketing. He has published a number of books in
these areas and his papers have appeared in various academic journals.
Carsten D. Schultz is a Postdoctoral Researcher at the Chair of Marketing in the
Faculty of Business Administration and Economics, University of Hagen,
Germany, where he completed his doctoral thesis in 2012. He studied business
information systems at the University of Essen, Germany, and computer
science at the University of Skövde, Sweden. His research interests focus on
,48 R. Olbrich et al.
electronic commerce and online marketing and include online consumer
behaviour, affiliate marketing, search engine advertising, and social media
marketing. He also advises companies on strategies and activities in these
areas.
Patrick M. Bormann is a doctoral candidate at the Chair of Marketing in the
Faculty of Business Administration and Economics, University of Hagen,
Germany. He studied management and economics at the University of
Wuppertal, Germany. His research interests include affiliate marketing, social
media marketing, consumer behaviour, electronic commerce, and video games.
1 Introduction
Affiliate marketing refers to an online relationship between the so-called merchant and
the affiliate, where the merchant pays the affiliate a commission to redirect potential
consumers to the merchant’s website (Libai et al., 2003). Merchants can be
manufacturers of products, service providers, or retailers. Merchants employ the help of
affiliates to expand their reach on the target (online) audience (Sarkar et al., 1998).
Affiliates are intermediaries who provide content for consumers. For merchants, affiliates
provide branding and selling functions and come in a variety of categories. Individuals
may use digital advertisements, such as banners and sponsored links, on their websites to
promote the merchant’s products or services (Duffy, 2004, 2005). Other business models
include, for example, blogs, communities and price comparison sites that redirect
consumers to the merchant’s website (Fox and Wareham, 2010; Prussakov, 2011).
Affiliates receive a commission depending on consumer actions predefined by the
merchant (Libai et al., 2003; Sarkar et al., 1998). Merchants may pay their affiliates for a
simple redirect of a consumer, such as a click-out to their online shop (Olbrich and
Holsing, 2011), for a lead, such as requesting further information about a service
(Cartellieri et al., 1997; Olbrich et al., 2016), or for a sale buying a product or service
(Lee and Lee, 2012). Moreover, merchants may organise their affiliates themselves or
employ affiliate networks that provide access to affiliates and additional services, such as
performance tracking and financial services (Fox and Wareham, 2010).
Even though affiliate marketing is one potential online channel (Anderl et al., 2016;
Klapdor et al., 2015), research on affiliate marketing is limited to specific topics, for
example, trust building (Gregori et al., 2014; Haq, 2012), differences across product
categories (Brear and Barnes, 2008; Papatla and Bhatnagar, 2002; Lee and Lee, 2012),
control and contract design (Fox and Wareham, 2010; Gilliland and Rudd, 2013), and
fraudulent behaviour (Edelman, 2009; Edelman and Brandi, 2015; Miehling et al., 2010).
The present study advances research on affiliate marketing by addressing the interaction
between affiliate marketing and social media.
Merchants can generally draw on internal and external information to evaluate their
affiliate marketing activities, such as assessing advertisements and partnering affiliates.
Examples of internal information are direct performance measures, such as impressions,
leads, and advertising spending. Merchants may also consider external information from
, The effect of social media and advertising activities on affiliate marketing 49
other sources that in comparison to internal information are generally not so readily
available. Mariussen et al. (2012) mention social media activities as one particular
external source of interest.
In contrast to affiliate marketing, social media has become the subject of increasing
research interest. Researchers have analysed various types of social media, such as blogs
(e.g., Gopinath et al., 2013; Onishi and Manchanda, 2012), microblogs (e.g., Tirunillai
and Tellis, 2012; Rui et al., 2013; Zhang et al., 2011), user-generated product rating and
review websites (e.g., Chevalier and Mayzlin, 2006; Phang et al., 2013), social shopping
communities (e.g., Holsing and Schultz, 2013; Olbrich and Holsing, 2011), and social
networking sites (e.g., de Vries et al., 2012; Katona et al., 2011). Moreover, research has
compared multiple types of social media (e.g., Dhar and Chang, 2009; Oh et al., 2017;
Schweidel and Moe, 2014; Smith et al., 2012) and considered the combination of
traditional and social media (e.g., Kumar et al., 2016; Onishi and Manchanda, 2012;
Stephen and Galak, 2012; Yu et al., 2013) as well as online and social media (Anderl
et al., 2016; Klapdor et al., 2015). However, the use of social media in affiliate marketing
has not been analysed. Following the proposition to consider social media as an external
information source (Mariussen et al., 2012), the present paper addresses this particular
research gap.
Specifically, we analyse the effect of social media activities on an affiliate marketing
campaign. The study is based on data from a service company. The social media and
affiliate marketing activities are recorded for a six month period and span 133 affiliate
partners registering 611,081 ad impressions, 15,082 clicks, and 2,672 social media
messages received by 20,541 followers. The study contributes in three main ways to the
literature.
Firstly, the research model includes key factors of an affiliate marketing campaign
that affect the campaign results, such as advertising media used, commission amount,
length of partnership, and business focus. These factors add to the understanding of
affiliate marketing success. Ad media, commission amount, and business focus
significantly affect the results of the affiliate-merchant relationship. The results for length
of partnership warrant further clarification.
Secondly, the analysis provides insights into the multichannel use of social media and
affiliate marketing. In particular, we analyse the effect of microblogging activities on the
affiliate marketing performance. The results demonstrate that microblogging social media
activities significantly affect the number of impressions and to a lesser extent the number
of leads. Social media activities appear to create some level of priming that positively
affects the likelihood to engage with the merchant.
Thirdly, the present paper contributes to the stream of literature discussing social
media as an information source. Our results indicate the use of social media as an
external information source to provide a more detailed picture of an affiliate’s behaviour
and performance.
The remainder of the paper is organised as follows. The next section discusses related
research on affiliate marketing and the multichannel literature in social media. Also, the
hypotheses and research model are derived. Afterwards, the data are presented and
analysed. The empirical results are subsequently discussed before the paper concludes
with the limitations and directions for further research.
