e-mail marketing in e-commerce start-ups
TRANSCRIPT
E-mail Marketing in e-commerce Start-ups
Vrije Universiteit Amsterdam & Universiteit
van Amsterdam
Author: Bram G J van Pul
Student number: UVA 10114351 & VU 2140616
Study: MSc Entrepreneurship
Supervisor: Dr. W. van der Aa
Date: 1 December 2015
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Abstract
E-mail marketing is increasingly recognised as an effective internet marketing tool. This study
examines the practice of e-mail marketing in the context of resource-limited e-commerce start-ups. By
analysing existing literature on the subject the characteristics and the consequential challenges of new
ventures are addressed. From the challenges start-ups face, it can be concluded that new ventures need
to be innovative, creative and especially cost saving in their marketing activities. Generally speaking,
start-ups cannot use the expensive traditional marketing channels because of its high price tags.
Therefore, the alternative marketing channel e-mail marketing is studied and further analysed. In
collaboration with a lead generation company based in Amsterdam a sample of 27 e-commerce start-
ups was constructed. From 39 e-mail marketing campaigns of those companies the open rates and
click-through rates were collected to conduct further research on. In addition to measuring the
performance of several e-mail marketing campaigns, the newsletters of those companies were
collected and content analysed.
In addition to determining the usefulness of e-mail marketing for new ventures, the most important
executional tactics in e-mail marketing were identified and further investigated. By conducting a
Pearson correlation analysis, the influence of the executional tactics on the collected response rates
was tested.
Final conclusion
Keywords: Start-ups, New ventures, E-commerce, Internet marketing, E-marketing, E-mail
marketing, Executional tactics, Open rate, Click-through rate
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Table of Contents
1. Introduction .......................................................................................................................... 5
1.1 Motivation ................................................................................................................................... 5
1.2 Problem statement ...................................................................................................................... 6
1.2.1 Scientific relevance ............................................................................................................... 8
1.2.2 Social relevance ..................................................................................................................... 8
1.3 Outline of the research ............................................................................................................... 9
2. Theoretical Framework ..................................................................................................... 10
2.1 Characteristics of new ventures .............................................................................................. 10
2.2 Challenges in new ventures ...................................................................................................... 11
2.2.1 The liability of newness ...................................................................................................... 11
2.2.2 The liability of smallness .................................................................................................... 12
2.2.3 Uncertainty .......................................................................................................................... 13
2.3 Internet marketing ................................................................................................................... 15
2.3.1 Internet marketing defined .................................................................................................. 15
2.3.2 Drivers and barriers ............................................................................................................. 16
2.4 E-mail marketing ...................................................................................................................... 18
2.4.1 E-mail marketing defined .................................................................................................... 18
2.4.2 E-mail marketing purposes .................................................................................................. 18
2.4.3 Permission marketing .......................................................................................................... 19
2.4.4 Response in e-mail marketing ............................................................................................. 20
2.4.5 Advantages .......................................................................................................................... 22
2.4.6 Disadvantages...................................................................................................................... 23
2.5 The conceptual framework ...................................................................................................... 24
2.5.1 The e-mail subject line ........................................................................................................ 26
2.5.2 The creative design of the e-mail content ........................................................................... 26
2.5.3 Personalisation .................................................................................................................... 28
2.5.4 Frequency and timing .......................................................................................................... 28
2.5.5 Permission ........................................................................................................................... 28
2.5.6 Response ............................................................................................................................. 28
3. Methods ............................................................................................................................... 30
3.1 Research Design ........................................................................................................................ 30
3.2 Operationalization .................................................................................................................... 30
3.3 Data collection ........................................................................................................................... 31
3.3.1 The sample .......................................................................................................................... 31
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3.4 Data analysis ............................................................................................................................. 32
4. Results ................................................................................................................................. 33
4.1 The response .............................................................................................................................. 33
4.1.1 The open rate ....................................................................................................................... 33
4.1.2 The click-through rate ......................................................................................................... 34
4.2 The e-mail subject line ............................................................................................................. 34
4.2.1 The subject matter ............................................................................................................... 34
4.2.2 The e-mail sender ................................................................................................................ 35
4.3 The creative design of the e-mail content ............................................................................... 35
4.3.1 The e-mail headline ............................................................................................................. 36
4.3.2 The e-mail length ................................................................................................................ 36
4.3.3 The use of colours ............................................................................................................... 36
4.3.4 The use of images ................................................................................................................ 37
4.3.5 The use of animation ........................................................................................................... 37
4.3.6 The use of interactive features............................................................................................. 37
4.3.7 The use of hyperlinks .......................................................................................................... 38
4.3.8 The brand logo .................................................................................................................... 38
4.4 The e-mail frequency ................................................................................................................ 38
4.5 Personalisation .......................................................................................................................... 39
5. Discussion............................................................................................................................ 40
5.1 The response .............................................................................................................................. 40
5.2 The e-mail subject line ............................................................................................................. 41
5.3 The creative design of the e-mail content ............................................................................... 42
5.4 The e-mail frequency ................................................................................................................ 43
5.5 Personalisation .......................................................................................................................... 43
6. Conclusion .......................................................................................................................... 45
6.1 Conclusions................................................................................................................................ 45
6.2 Limitations ................................................................................................................................ 45
6.3 Future research ......................................................................................................................... 46
7. Recommendations .............................................................................................................. 47
8. References ........................................................................................................................... 49
9. Appendices .......................................................................................................................... 53
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1. Introduction
1.1 Motivation
According to Heart of business (2015) Electronic commerce, commonly known as e-commerce, refers
to the buying and selling of products or services over electronic systems such as the Internet and other
computer networks. However, the term may refer to more than just the buying and selling products
online. It also includes the entire online process of developing, marketing, selling, delivering,
servicing and paying for products and services.
The emergence of e-commerce has created a new model for doing business that affects all aspects of
the marketing mix. A particularly important aspect of this new business paradigm is its impact on
marketing channels. E-commerce presents business marketers with profound opportunities, including
reduced costs, access to new market segments, and the ability to provide information worldwide on a
continuous basis (Webb, 2002).
The marketing mix has persisted now for over 40 years as the 4P’s of Product, Price, Place and
Promotion. However, in the post dot-com boom, marketing managers are learning to cope with a
whole host of new marketing elements that have emerged from the on-line world of the Internet
(Kalyanam, K., and McIntyre, S., 2002).
According to Dhillon (2013), internet marketing is also referred to as online marketing or e-
Marketing. This is known as the definition of marketing that uses the Internet. More completely
defined E-marketing is a term that refers to use of the Internet/Web and related information
technologies to conduct marketing activities (Krishnamurthy, 2006). Implementation of E-marketing
can change the shape of business all over the world. Because of the rapid proliferation of the Internet,
the World Wide Web (WWW) and electronic communication has created new and fast growing
electronic channels for marketing. Internet marketing methods include search engine marketing,
display advertising, e-mail marketing, affiliate marketing, interactive advertising, blog marketing, and
viral marketing (Dhillon, J. S., 2013). Different types of modern marketing like Internet marketing, e-
mail marketing, and online advertising all drive businesses to be successful (Salehi, M., Mirzaei, H.,
Aghaei, M., & Abyari, M., 2012). Furthermore, internet Marketing has become an important tool for
creating, trust, commitment and loyalty for various brands of products and services across the globe
(Dhillon, J. S., 2013).
According to Niall (2000) one of the most effective forms of Internet-based direct marketing is the
use of personalised e-mails. E-mail marketing is a form of direct marketing which uses electronic mail
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as a means of communicating commercial or fundraising messages to an audience. In its broadest
sense, every e-mail sent to a potential or current customer could be considered e-mail marketing
(Dhillon, J. S., 2013). The advantages of e-mail marketing have been recognised by various authors.
Niall (2000) describes e-mail marketing as one of the most effective online marketing tools because
of its high response rate. Given a database of prospects and customers e-mail messages can be highly
targeted (Kalyanam, K., & McIntyre, S., 2002). Jackson and DeCormier (1999) recognised that e-mail
provided marketers with communication that permitted relationship building and real-time interaction
with customers. Furthermore, Wreden (1999) described e-mail marketing as the 'Internet's killer
application' because of the precision with which e-mail can be tailored, targeted and tracked. And
according to Pavlov, O. V., Melville, N., & Plice, R. K. (2008) E-mail marketing provides twice the
return on investment (ROI) relative to other forms of online marketing: $57.25 for each dollar spent
versus $22.52 (Direct Marketing Association).
Marketing is considered to be of utmost importance for the success of new ventures (Gruber, M.,
2004). According to Hills, G. E., Hultman, C. M., & Miles, M. P., (2008) marketing from the
perspective of an entrepreneur is not just one of the functions of the business that must be carried out
such as accounting, finance, or HRM; but is often considered by entrepreneurs as the core function of
the firm. Therefore, the marketing of a start-up can determine its success or its failure. The results off
the research conducted by Hills et. al., (2008) clearly indicates that entrepreneurs engage in marketing
in ways that deviate from administratively focused marketing, which dominates mainstream
marketing theory. New forms of marketing have presented an opportunity for small businesses to
grow in a dramatic and dynamic way (Eid, R., & El-Gohary, H., 2013). Therefore, according to
Kraus, S., Harms, R., & Fink, M. (2009) an entrepreneurial approach to marketing would use
innovative communication channels (e.g. Internet, mobile marketing) or use classical channels in an
innovative way with new content, and would be ahead of the competition in doing this.
1.2 Problem statement
The aim of this research is to explore and describe the practice of e-mail marketing in the context of a
resource-limited e-commerce start-up while measuring the performance of several e-mail marketing
campaigns of different companies. The goal is to discover whether there is a fit between the use of e-
mail marketing and resource-limited e-commerce start-ups or not. The results of former research on
entrepreneurial marketing by (Hills et al. 2008) clearly indicates that entrepreneurs engage in
marketing in ways that deviate from administratively focused marketing, which dominates
mainstream marketing theory. New ventures usually start off as relatively small organizations with
only a handful of employees and are usually very limited in their financial resources. Although some
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new ventures are able to acquire venture capital and thus alleviate problems associated with resource
scarcity, the majority of new firms have problems in raising capital. Next to resource scarcity start-
ups struggle with several other limitations and challenges, this results in different choices for
marketing strategy then traditional firms use to market their products (Gruber, M., 2004).
Previous research has established marketing as one of the most important functions for the success of
the launch and development of start-ups (Hirisch, 1992). Furthermore, marketing is also recognized as
one the main challenges for start-ups due to the unique characteristics and inherent limitations of
start-ups. Research on start-ups has also argued that resource-limited organizations often cannot use
costly traditional marketing tools and should instead implement more unsophisticated and personal
marketing tools (Kraus et al., 2010). However, consensus on what this type of marketing tool is has
not been reached. Some former research has been conducted on e-mail marketing, entrepreneurial
marketing and marketing in start-ups but there is very few researches that have been conducted on the
specific use of e-mail marketing by start-ups. In this research, I will try to discover the opportunities
and the usefulness in e-mail marketing for start-ups by conducting a research on data from several e-
mail marketing campaigns of multiple start-ups. To guide this research, the following research
questions are constructed and will be answered gradually:
Research question:
What is the effect of e-mail marketing use on the marketing success of e-commerce start-ups?
Sub-questions:
What are the main challenges and limitations of a start-up that influences their marketing?
What is Internet marketing? What is e-mail marketing? And what are the Advantages and
disadvantages of e-mail marketing?
What are the key executional tactics influencing the response to e-mail marketing?
How is the performance of e-mail marketing campaigns measured, and how well is this performance
for e-commerce start-ups?
How can the response of consumers be optimized for e-mail marketing campaigns of e-commerce
start-ups when using e-mail marketing on opt-in databases?
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1.2.1 Scientific relevance
This research contributes by researching a relatively new marketing channel and the combined
principle of e-mail marketing with the marketing success of resource-limited e-commerce start-ups.
Despite the challenge presented to existing paradigms, the mainstream academic literature has largely
ignored the growing importance of electronic-based marketing strategies (Eid, R., & El-Gohary, H.,
2013). While numerous guides exist on ‘How to do business’ or ‘How to make money’ on the
Internet, there have been few serious academic studies of the topic and little attempt has been made to
develop conceptual frameworks for evaluating the effect of E-marketing on SBEs marketing success
(Eid, R., & El-Gohary, H., 2013). The subjects E-marketing and e-mail marketing have been
addressed by several authors but according to Kalyanam and McIntyre (2002) Further research might
explore normative aspects of the e-Marketing mix and whether certain components are more or less
effective. Moreover, according to Eid and El-Gohary (2013) there is a lack of systematic empirical
evidence regarding marketing activities that are affected by the use of E-marketing in the (SBEs)
context, and their consequent performance outcomes. The recent rush of publications in the area may
give rise to the impression that E-marketing can be applied in any context, yet there is little empirical
evidence to support this (Eid, R., & El-Gohary, H., 2013). Furthermore, Hills et al. (2008) encourage
further research in entrepreneurial marketing and its use and impact on firms in all contexts.
1.2.2 Social relevance
As small business enterprises (SBEs) are considered to be the economic engine leading worldwide
economic development, they have attracted substantial consideration from researchers, academics and
practitioners in the last three decades. A great deal of this interest derives from the belief that
innovation, especially in information technology (IT), is crucially dependent on the potential of
entrepreneurial SBEs (Eid, R., & El-Gohary, H., 2013). According to Dhillon (2013) the internet has
provided the global audience with instant information, broad connections to billions and a
revolutionary form of communication. However, for all of this seemingly effortless access to
consumers, the internet has traditionally been a complex problem for marketers. Numerous
organizations either do not have or maintain an appropriate interactive / internet marketing plan. More
still simply include an isolated online component, typically a banner advertising campaign, in an
overall marketing plan. And those organizations with an interactive marketing plan often face the
challenge of new technology, new opportunities and campaign measurement (Dhillon, J. S., 2013).
Therefore, this research aims to contribute to the knowledge in the fields of E-marketing by focusing
on the use of e-mail marketing by resource-limited e-commerce start-ups.
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1.3 Outline of the research
The data necessary to conduct this research will be gathered at a Lead generation company active in
the Netherlands, Belgium, Poland, Italy, Australia, Germany, France and The United Kingdom. This
company provides clients with opt-in databases with potential customers. The clients consist of
companies that use this data for e-mail marketing and telemarketing campaigns. The focus in this
research will be on the e-mail marketing campaigns of a selection of those companies. As a result of
those campaigns most of the companies use performance measurements to analyse the performance of
these campaigns. This company grants access to a lot of performance data on e-mail marketing
campaigns of businesses active in the e-commerce.
To determine the usefulness of e-mail marketing we look at the customers’ response in e-mail
marketing campaigns of several e-commerce start-ups. Research will be conducted on the
performance data received from clients such as open rates, click through rates, opt-outs and bounce
rates from reports on their e-mail marketing campaigns. The way the performance is actually
measured and rated will be described in depth in the theoretical/methods part of this thesis. Next to
the analysis of the performance data the content of the e-mail marketing campaigns will be analysed
to discover any patterns or elements influencing the response to the campaigns.
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2. Theoretical Framework
The purpose of the following chapter is to provide the reader with the available literature on the
subject. The existing literature on this subject is used to answer the following research questions:
What are the main challenges and limitations of a start-up that influences their marketing?
What is Internet marketing? What is e-mail marketing? And what are the Advantages and
disadvantages of e-mail marketing?
In addition to that the following research questions will be answered partially according to the
findings from the existing literature. Later on in this research these question will be fully answered
when combined with the results from the analysis.
What are the key executional tactics influencing the response to e-mail marketing?
How is the performance of e-mail marketing campaigns measured, and how well is this performance
for e-commerce start-ups?
In the last part of this chapter the conceptual framework is presented, followed by the conceptual
model generated on the basis of the literature.
2.1 Characteristics of new ventures
As mentioned earlier in the introduction when analysing a company’s marketing efforts, a start-up
cannot be treated the same as larger, more established firms. Therefore, in the following section
certain characteristics of new ventures and their competitive environment will be discussed in order to
gain a better understanding of the specific challenges new ventures face in their marketing efforts.
According to Gruber (2004) the most important characteristics of new ventures and their environment
consist of their newness and small size, as well as the inherent uncertainty of the undertaking. These
characteristics of new ventures and their competitive environment contribute to the challenges new
ventures take on in their marketing efforts. These challenges will be discussed and further analysed on
the basis of existing literature on this subject.
First, the liability of newness describes a lack of routines in the firm and a lack of established
relationships with market partners (Aldrich & Auster, 1986, cited in Kraus et al., 2010). In addition to
that new ventures are faced with a lack of trust in their products due to a missing track record or an
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unknown company or brand name and a lack of expertise and experience in marketing (Gruber,
2004). These burdens of new ventures lead to higher failure rates compared to established firms. As
mentioned before, new ventures are challenged to create exchange relationships. Yet they lack the
reputation, legitimacy, and experience of established firms, and must rely on interactions between
strangers (Gruber, 2004).
Secondly, the liability of smallness refers to limited financial and human resources, limited market
power and a small customer base (Carson, 1985, cited in Kraus et al., 2010). Start-ups are usually
small firms with few employees which make them highly dependent on the entrepreneur. Next to that
raising capital is often a great challenge for new ventures. According to Gruber (2004) Resource
scarcity makes small firms vulnerable, as their ability to sustain economic downtrends is limited.
Furthermore, it is also likely that they encounter critical gaps in required skills due to lower skill
diversity and disadvantages when competing with larger firms for employees. The resource-
constrained start-ups must therefore often apply marketing in unsophisticated and personal ways in
order to create the initial profitability (Morris et al., 2002).
According to Gruber (2004) Liabilities of newness and smallness are exacerbated by problems of
uncertainty. Uncertainty is a concept that is central to entrepreneurship, as emphasized by eminent
economists such as Cantillon, Mangoldt, Knight and Keynes (Hebert and Link, 1989; Ekelund and
Hebert, 1990 cited in van Gelderen, M., Frese, M., & Thurik, R. 2000). Since uncertainty is a fact of
economic life, entrepreneurs are needed to arbitrage, to take risks and to innovate (van Dijk and
Thurik, 1998).
2.2 Challenges in new ventures
From the above mentioned characteristics of new ventures it can be deduced that start-ups lack the
reputation, legitimacy, experience and some important resources. Therefore, certain challenges
around the practice of marketing arise. In other words, these limitations of start-ups have distinctive
consequences on the way that the marketing is performed. These challenges and consequences are
further analysed and explained for each characteristic in the following part.
2.2.1 The liability of newness
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According to Gruber (2004) the prime challenges in marketing for new ventures arise from the fact
that the company and its products or services are unknown to potential customers and other parties.
The fact that new ventures are unknown entities often results into a lack of trust. Therefore, start-ups
are challenged to gain the customers trust in their abilities which should eventually result in obtaining
a company identity and building a brand name. Stinchcombe (1965) cited in Zimmerman, M. A., &
Zeitz, G. J. (2002) mentioned that in the search to understand the creation, survival, and growth of
new ventures, legitimacy plays a key role. Zimmerman & Zeitz (2002) argue that legitimacy is a
resource for new ventures. A resource that is as important as other resources, such as capital,
technology, personnel, customer goodwill, and networks. Legitimacy increases the accessibility of
other important resources necessary in order to overcome the liability of newness.
The challenge of gaining exchange relationships addresses more than relationships with customers,
new ventures also lack relationships with other parties such as distributors and suppliers. Constructing
those relationships with potential partners can be very difficult for new ventures. The challenge
regarding those relationships consists of restricted and often costly access to new partners. As such
relationships often serve as critical complementary assets, they represent substantial barriers to market
entry when they cannot be attained (Gruber, 2004).
As a result of the newness of start-ups these firms are challenged to establish internal structures and
processes in marketing by defining new roles and tasks. According to Stinchcombe (1965) cited in
Gruber (2004) this lack of routines in the firm is associated with high costs in time, worry, temporary
inefficiency and conflict. Correspondingly, according to Gruber (2004) young firms lack experience
in marketing, which means errors in marketing planning and execution are more likely. Without the
experience in marketing, this process becomes challenging for new ventures while they cannot draw
on historical data in their marketing planning. Therefore, the marketing style of small enterprises is
said to be more simplistic and ad hoc, based on intuition, with little or no formal structures (Hill &
Wright, 2000 cited in Kraus et al., 2010).
2.2.2 The liability of smallness
As mentioned earlier the liability of smallness mainly refers to limited financial and human resources,
limited market power and a small customer base. Limitations in resources limit the options.
Therefore, the marketing in start-ups faces severe challenges in terms of finance and personnel.
According to Gruber (2004) financial resource scarcity demands a high degree of effectiveness and
efficiency in the marketing efforts of new ventures. Therefore, start-ups must develop imaginative
forms of marketing that are low-cost, but produce a strong impact on the marketplace.
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Furthermore, due to the small number of employees in new ventures, the start-up often lacks critical
skills in marketing. These skills cannot be easily compensated for because of the cost of time and
money. As a consequence, the company is highly dependent on the entrepreneurs’ skills and attitude
towards marketing because of the dominant role of the entrepreneur in new ventures. The strong
reliance on a single entrepreneur may have negative consequences. A study on 100 VC-backed start-
ups from Germany shows that marketing planning that is carried out in a team is significantly more
successful (Gruber, 2005 cited in Kraus et al., 2010).
According to Gruber (2004) apart from resource limitations, smallness is usually associated with
limited market presence and lack of market power. Therefore, often new ventures are not able to
achieve significant economies of scale and scope in marketing. As a result, there is a possibility that
the marketing faces higher costs because of certain parties exerting marketing power to obtain larger
margins from new firms (Gruber, 2004).
2.2.3 Uncertainty
Uncertainty is an inevitable characteristic of new ventures and their environment. The uncertainty and
turbulence faced by many new ventures, in particular those introducing new products or entering
markets in the process of formation, limits the usefulness of existing market data. This requires new
ventures to keep their strategic options open and limits the visibility of marketing best practices or
even the likely dominant design in a new product domain (Lingelbach, D., Patino, A., & Pitta, D. A.,
2012).
First of all, according to Gruber (2004) due to the high degree of uncertainty and turbulence
surrounding innovative solutions in new markets, the predictability of market data is restricted and
only limited information is available for marketing planning. For example, there is no or little
information available about the demand for new products or services. Therefore, important marketing
decisions must be based on vague predictions, which causes mistakes that new ventures mostly cannot
afford to make.
Secondly, due to uncertainty, new ventures should be prepared for several scenarios and are therefore
required to keep their strategic options open. However, due to resource scarcities, new firms have
only limited ability to pursue several strategic options at once. Additionally, a revision of earlier
decisions may possibly disrupt the strategic guidance in marketing which may also cause internal
turbulence (Gruber, 2004).
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Lastly, as a consequence of uncertainty and turbulence there is a large probability that best practices
in marketing have yet to be determined for a specific industry. Correspondingly, it is likely that the
dominant design of an offering has not yet been established in the marketplace (Gruber, 2004). Hence
the marketing planning in a start-up should take a proactive, innovative, risk-taking approach to the
identification and exploitation of opportunities for attracting and retaining profitable customers and an
alternative approach to marketing under conditions of change, complexity, chaos, and contradiction
(Morris et al., 2002).
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2.3 Internet marketing
As addressed in the previous chapters marketing in a small firm differs from marketing in larger
firms. According to Carson et al., (1995) cited in Gilmore, A., Gallagher, D., & Henry, S. (2007) it is
considered to be more intuitive, competency based, revolving around networking and operating under
financial and human resource/time constraints. With the evolvement of the Internet the way of doing
business has changed and the Internet has lowered the barriers of entry for many business industries.
According to Chittenden, L., & Rettie, R. (2003) any way to communicate that is easier, cheaper or
quicker always has high appeal, the Internet offers all three. The Internet has lowered the transaction
and distribution costs, made communication easier, has waved of the time and place limitations and
provided firms with information to understand the needs of customers. Moreover, the Internet has
created new opportunities for marketers. Companies are developing sophisticated and modern e-
marketing tools. The Internet has become a challenge for marketers and even a complex problem in
marketing. According to Dhillon (2013) numerous organisations either do not have or maintain an
appropriate Internet marketing plan. Those organisations with an Internet marketing plan often face
the challenge of new technology, new opportunities and campaign measurement. This chapter is
meant to gain better knowledge about the terms Internet marketing and in particular e-mail marketing.
Internet marketing will be explained and the drivers and barriers for implementation of Internet
marketing will be discussed. The focus of this study will be on e-mail marketing hence the second
part of this chapter will elaborate further on this subject.
2.3.1 Internet marketing defined
The terms E-marketing, E-commerce, E-business and Internet marketing are often used as terms with
equal meaning with different wording, which is not correct. The definition E-marketing includes
using the internet and its related technologies and features such as the world wide web, web
presences, e-mails, real-time communication, and delayed and mixed time communication to help
achieve marketing objectives in conjunction with other marketing communication tools (Gilmore et
al., 2007). Or according to Chaffey & Smith (2008) cited in Yasmin, A., Tasneem, S., & Fatema, K.
(2015) digital marketing, electronic marketing, e-marketing and internet marketing are all similar
terms which, simply put, refer to “marketing online, whether via websites, online ads, opt-in e-mails,
interactive kiosks, interactive TV or mobiles”. But E-marketing has broader scope, internet marketing
just refers to internet things like world wide web and electronic mail, while E-marketing includes all
the above mentioned. On the other hand, E-Business and E-commerce have even broader scope in
comparison to E-marketing (Dehkordi, G. J., Rezvani, S., Rahman, M. S., Fouladivanda, F., & Jouya,
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S. F. (2012). As mentioned in the introduction according to Heart of business (2015) Electronic
commerce, commonly known as e-commerce, refers to the buying and selling of products or services
over electronic systems such as the Internet and other computer networks. Former literature about E-
commerce shows the advantages of the Internet as a platform to sell the product. This can be
classified into three major functions: As a channel for communicating, as a channel for doing
transactions and as a channel for distributing (Dehkordi et al., 2012). In this study the emphasis will
be on the Internet as a channel for communicating and in particular as a channel for promotion,
customer acquisition and customer retention.
A start-ups marketing activities can be divided in two basic dimensions: Pre-sales activities and After-
sales activities. A number of authors mentioned by Eid & El-Gohary (2013) have paid attention to the
consequences of the adoption of E-marketing on SBEs pre-sales activities. These consequences
include faster discovery of customer needs, greater customisation of products, faster communication
with customers and faster adaptability of customer needs. Other authors have argued that many after-
sales marketing activities such as providing better service quality, developing new products, good
customer relationship and increased customer satisfaction might be influenced by the use of E-
marketing (Eid & El-Gohary, 2013).
2.3.2 Drivers and barriers
The interactive nature of Internet media, both in terms of instant response, and in eliciting response at
all, are both unique qualities of internet marketing (Dhillon, 2013). Several opportunities for start-ups
arise from those qualities which otherwise wouldn’t be available to them. Moreover, the Internet has
improved efficiency in the development and richness of the content of marketing activities (Gilmore
et al., 2007). In the former literature about Internet marketing several drivers and barriers to Internet
adoption amongst SMEs have been identified by Gilmore et al. (2007).
The drivers to Internet marketing adoption activities can be divided into pro-active and reactive
drivers. Pro-active reasons include the chance to eliminate competitive disadvantages of SMEs in
peripheral areas, the chance to lower operating and marketing costs, the opportunity to promote their
company better and enrich their overall marketing communications mix. Other reasons include the
enthusiasm from management, the chance to increase sales or preform market research (Jeffcoate et
al., 2002; Downie, 2002; Dann & Dann, 2001; Poon & Swatman, 1997 cited in Gilmore et al., 2007).
The reactive reasons include increased competition from local competitors as well as larger firms,
shrinkage in domestic markets, the fear of competitive disadvantage, as well as simply jumping on the
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bandwagon (Kardaras & Papathanassiou, 2000; Premkumar & Roberts, 1999; Ching & Ellis, 2004
cited in Gilmore et al., 2007).
The Barriers to Internet marketing adoption for SMEs include the impact of the generic SME
characteristics on business activity, practical implementation and maintenance issues and
organisational obstacles (Gilmore et al., 2007). As mentioned in the previous chapter these generic
characteristics consist of financial constraints, human resource issues and the problem of a lack of
specialist skills or know-how of marketing on the web. The problem with practical implementation
and maintenance issues is the creation of a web presence and its maintenance is very costly for SMEs
(Hormozi & Harding, 1998 cited in Gilmore et al., 2007). The cost and challenges depend on the size
of the website, how often it needs updating and if the company should buy the hardware and software
to create themselves or should they contract professionals to provide the services. Next to the
implementation and maintenance issues another problem appears in its cost effectiveness. A recent
study found that many SMEs complained that whilst they had received many online enquiries, very
few of these had actually turned into completed orders (Ching & Ellis, 2004 cited in Gilmore et al.,
2007).
18
2.4 E-mail marketing
Despite its importance for e-commerce, the e-mail marketing literature is limited, apparent, and has
academically been studied only using indirect attitudinal measures instead of direct focus on
behavioural effectiveness and economic competitiveness (Sigurdsson, Menon, Sigurdarson,
Kristjansson, & Foxall, 2013). In this chapter the most important literature on the subject is analysed
and further elaborated on to identify the most important characteristics, purposes, advantages and
disadvantages of e-mail marketing. Furthermore, permission marketing, the key executional tactics
influencing the response on e-mail marketing and response measurement are being discussed.
2.4.1 E-mail marketing defined
According to Pepper and Rodger (2000) cited in Ali, Z., Ejaz, S., Aleem, A., Saeed, M. U., Tahir, F.
A., & Kashif, M. (2015) e-mail marketing is the most useful term of electronic marketing. Forrester
also describes e-mail marketing as one of the most effective online marketing tools because of its high
response rate. According to Niall (2000) cited in Rettie, R., Grandcolas, U., & Payne, V., (2005) e-
mail is the fastest-growing communications technology in history. From only two million e-mail
accounts in 1985, this grew to 891.1 million e-mail accounts at the beginning of 2001. Worldwide e-
mail use continues to grow at a healthy pace. According to the E-mail Statistics Report (2015) in
2015, the number of worldwide e-mail users will be nearly 2.6 billion. By the end of 2019, the
number of worldwide e-mail users will increase to over 2.9 billion. Over one third of the worldwide
population will be using e-mail by the end of 2019. Next to the continuous growth of this number of
users, e-mail has also changed how, with whom and about what people communicate (Chittenden &
Rettie, 2003). In response to this growing channel of communications, marketers have begun to see
that they can replicate offline advertising methods online.
E-mail marketing can be considered as using electronic mail for delivering commercial messages to
customers and potential customers. The basic characteristics of e-mail marketing are low costs,
shorter turnaround (In the time involved to prepare and send the messages, and receive the responses),
high response rates, and customisable campaigns (Rettie et al., 2005).
2.4.2 E-mail marketing purposes
19
E-mail marketing is a direct marketing channel through which service quality can be enhanced and,
customer awareness and attention can be increased (Dehkordi et al. 2012). Therefore, e-mail can be
used for various marketing purposes, for example to share information about products and services, to
promote them, to establish brands, to guide customers to web sites, to alert customers, and to tell the
status of orders (Merisavo, M., & Raulas, M., 2004). Marketers today use various e-mail techniques,
such as newsletters, reward programs and community building (Brondmo, 2000; Roberts et al., 2001
cited in Merisavo & Raulas, (2004). Newsletters, as Brondmo (2000) cited in Merisavo and Raulas,
(2004) suggests, “are perhaps the most Common vehicles for establishing ongoing dialogue with
customers, probably because they provide a terrific mechanism for communicating a highly
personalised blend of information, entertainment, and promotions” (Merisavo & Raulas, 2004).
According to a research conducted by Salesforce, state of marketing (2015) 73% of the over 5000
globally interviewed marketers agreed that e-mail marketing is core to their business. E-mail
marketing is widely used for the acquisition of new customers and also seems that e-mail is also
becoming a major tool for customer retention due to the speed and cost benefits. A report by Forrester
Research in August 2001 revealed that almost 90% of the US e-mail marketing was to existing
customers according to Chittenden & Rettie (2003). The research conducted by Chittenden & Rettie
(2003) demonstrated that the effectiveness of e-mail marketing as a marketing tool for customer
retention is much higher compared to the effectiveness for customer acquisition. To be more precise
on a scale from 1 to 5, 1 being not effective and 5 being very effective, customer retention scored 4.5
and customer acquisition scored 2.1. One of the main reasons behind this is the cost difference
between retention and acquisition using e-mail. In a comparison of costs, research conducted by
Chittenden & Rettie (2003) the costs for customer retention is close to 25% of the cost for customer
acquisition. Despite the potential of frequent e-mail marketing for building and maintaining customer
loyalty, it has only recently started to gain importance in corporate marketing and Customer
Relationship Management(CRM) strategies. This is also noted by Reichheld & Schefter (2000) cited
in Merisavo & Raulas (2004), who discuss how marketers should concentrate on retaining rather than
attracting customers on the internet. There is, however, little empirical evidence on how e-mail really
works to retain customers (Merisavo & Raulas, 2004).
E-mail marketing as a marketing tool for sales promotion seems to be very effective as well according
to the research conducted by Chittenden & Rettie, (2003), with a score of 4.4 on the scale of 1 to 5.
2.4.3 Permission marketing
According to Ellis-Chadwick, F., & Doherty, N. F. (2012) permission-based e-mails are in wide use
20
because of widespread consumer complaints about unsolicited e-mails (known as “spam”). The major
incentive for consumers to “opt in” to a firm’s e-mailing list is the prospect of receiving material that
matches their interests, as recipients are more likely to open and read such messages (Ellis-Chadwick
& Doherty, 2012). Opt-in e-mail is a term used when someone is given the option to receive e-mails.
In most cases, this is used for an e-mail that is sent to many people at the same time. Godin (1999)
cited in Rettie et al., (2005) coined the term ‘permission marketing’ which is based on consumers
giving their consent to receive marketing information. Permission marketing ‘offers the consumer an
opportunity to volunteer to be marketed to’ and it is therefore ‘anticipated, personal and relevant’.
Permission marketing improves the targeting and relevance of promotional messages, thus improving
the response and conversion rates (Rettie et al., 2005).
If marketers have a database of individuals who have opted-in to receiving e-mails from their
organisation, then they have access by invitation to a customer communication channel more
powerful and less costly than the letterbox that also has none of the intrusive and unwanted
connotations of the telephone (Chittenden & Rettie, 2003). Consumers and customers treat their inbox
as a personal domain. As long as companies seek permission to send messages, and do not abuse this
privilege, they have the ability to build profile, awareness and, ultimately, a profitable relationship
with that person (Chittenden, & Rettie, 2003).
2.4.4 Response in e-mail marketing
The response process model suggests there are three stages in effective e-mail marketing: getting the
recipient to open the e-mail, holding their interest and persuading them to respond (Chittenden &
Rettie, 2003). In a study conducted by Chittenden & Rettie (2003), the several key factors that
influence the response in e-mail marketing were identified. According to them the response rate
should depend on the e-mail header as shown in the inbox, the e-mail content and the recipient. The e-
mail header more commonly referred to as the e-mail subject line consist of: the subject matter and
the e-mail sender. The creative design of the e-mail content includes; the e-mail headline, the length
of the e-mail, the use of colour and images, the use of animation, the brand logo, the use of hyperlinks
and the use of interactive features (Ellis-Chadwick & Doherty, 2012). The research conducted by
Chittenden & Rettie (2003) identified a significant relationship between response rate and subject
line, e-mail length, incentive and number of images.
According to research conducted by Ellis-Chadwick & Doherty (2012) the frequency and timing of
the send out influences the response. The number of e-mails sent varies by seasonality, for example
13 of the 20 firms sent the largest number of e-mails in the fourth quarter, which includes the
21
Christmas season. One retailer sent the vast majority of marketing e-mails in the evenings and at
weekends, whereas others favoured Friday afternoons. Additionally, the Chittenden’s and Rettie’s
(2003) study found that the colour of the email background seemed to affect the response rates of
email. Research findings suggest that three of their four experimental colours increased response rates
as compared with no colour at all where yellow corresponded to the most responses (Zviran et al.,
2006 cited in Sigurdsson, V., Hinriksson, H., & Menon, R. G. (2015).
In addition, according to Pavlov et al. (2008) customisation is found to be very desirable, but not
easily achievable. Colkin (2001) cited in Sigurdsson et al., (2015) found congruent results, indicating
that when a recipient’s name was added to the subject line, response rate doubled to more than 12%
over non-personalised e-mails. Personalisation consists of selecting products for different recipients,
mentioning the name of the recipient and sending personalised e-mails.
As mentioned before the response rate is positively influenced by permission given by the recipient.
Di Ianni (2000) cited in Sigurdsson et al., (2015) found that e-mail response rates ascend from 10 to
17% when e-mails are sent to a targeted permission-based group rather than untargeted.
The response in e-mail marketing can be measured in several ways. Which measurements a company
uses highly depends on the goal of the e-mail marketing campaign. According to Fassauer, R., &
Werner, A. (2015) the success of e-mail marketing campaigns is measured by a number of key
technical metrics:
- The Open rate is a measure of how many people on an e-mail list open (or view) a particular
e-mail campaign. The open rate is normally expressed as a percentage, and we calculate it as
follows: A 20% open rate would mean that of every 10 e-mails delivered to the inbox, 2 were
actually opened. A high percentage of open rate increases the chance of a successful
marketing campaign (Bawm, Z. L., & Nath, R. P. D., 2014).
- The click-through rate covers all receivers who clicked links in the received e-mails
(Fassauer, R., & Werner, A. 2015). Simply put the click-through rate describes the percentage
of recipient that find a newsletter relevant or intriguing enough to click on it (Regelson, M., &
Fain, D., 2006). E-mail click-through rate, is expressed in percentage, and calculated by
dividing the number of click throughs by the number of tracked messages opened (Bawm, Z.
L., & Nath, R. P. D., 2014).
- The conversion rate describes the percentage of newsletter receivers which reach a predefined
business objective (download, registration, order). It is a key ratio to define the success of an
online marketing campaign, linking the online marketing measurements with the business
goals of a company (Bawm, Z. L., & Nath, R. P. D., 2014).
22
According to the research conducted by Salesforce, the click-through rate, conversion rate and the
open rate are the most used metrics for e-mail marketing success (state of marketing, 2015). From the
over 5000 globally interviewed marketers the most used metric with 47% is the click-through rate, the
second most used metric is the conversion rate with 43% and the third most popular metric is the open
rate with 38%.
2.4.5 Advantages
In addition to the above mentioned characteristics and purposes of e-mail marketing there are plenty
of authors that suggest e-mail marketing can deliver a significantly heightened response as compared
to direct mail. Former literature shows there are several advantages of e-mail marketing over
traditional marketing channels. The main advantage obviously has to do with its favourable price tag
and its convenience. Creating a marketing message via e-mail is easy and everything can be digitally
processed. These low costs and digital processing allows companies to send out huge numbers of e-
mails (Rettie et al., 2005). According to Merisavo & Raulas (2004) the cost of sending a large number
of e-mail messages is marginal as compared with print mail. So sending multiple e-mails to either a
single person, or several people will barely affect the cost whatsoever. Moreover, according to Pavlov
et al., (2008) e-mail marketing provides twice the return on investment (ROI) relative to other forms
of online marketing: $57.25 for each dollar spent versus $22.52 (Direct Marketing Association).
E-mail marketing has the benefits of one-to-one marketing afforded by e-mail. E-mails are personal,
usually requested and, therefore, welcomed (Chittenden & Rettie, 2003). Furthermore, according to
ExactTarget (2010) 94% of the daily e-mail users subscribed to marketing messages. This generally
means that we can assume that these e-mail users want to receive marketing messages via e-mail. So
next to the cost advantage e-mail also offers potential for targeted and personalised communication
(Merisavo & Raulas, 2004). Owing to the precision with which e-mail can be tailored, targeted and
tracked Wreden (1999) cited in Rettie et al., (2005) described e-mail marketing as the 'Internet's killer
application'. E-mail gives marketers the opportunity to customise messages for different customers
and provide contents and promotions that are consistent with their profile (Fariborzi, E., &
Zahedifard, M. 2012). Since this communication can be personalised, e-mail has provided marketers
with communication that permitted relationship building and real-time interaction with customers
(Rettie et al., 2005). This real-time communication features e-mail marketing with the advantages of
faster delivery and easier response compared to traditional marketing channels.
Another benefit of E-mail marketing is the vast amount of tracking tools and statistics that are
available. Many factors of the performance of an e-mail marketing campaign can be monitored and
23
measured easily. Determining which statistics to track and report depends upon the original goal of
your campaign. If for example, the goal of your campaign is to further the branding message of your
organization a possible measurement would be the click-through rate. Which basically means the
recipient clicked on the link in the e-mail message, and thus the recipient was exposed to the brand.
Additionally, it is easy to monitor many more factors such as the number of e-mails sent, the number
of e-mails delivered, the number of e-mails that have been opened and the number of people that
unsubscribed from your campaign (Dhillon, 2013).
2.4.6 Disadvantages
The main disadvantage of e-mail marketing has to do with the deliverability of e-mails. Despite the
lucrative nature of e-mail marketing, consumers are overloaded with information, including both
wanted and unwanted communication (Pavlov et al., 2008). Spam can be defined as the practice of
indiscriminate distribution of messages without permission of the receiver and without consideration
for the messages’ appropriateness (Rettie et al., 2005). Windham (2000) as cited in Rettie et al.,
(2005) believes that unsolicited e-mail is considered an invasion of privacy, and has already become a
serious problem for some customers; spam taints the reputation of e-mail marketing. Currently, many
Internet Service Providers (ISPs) use complex Spam-mail filters which discharge the guarantee that
the e-mail messages will be delivered. Next to the probability that an e-mail will end up in the
recipients’ spam box, there is also the possibility that the recipient will not open an e-mail messages
sent from an unknown e-mail address. Consequently, e-mail marketers are forced to put a lot of effort
in making sure their e-mail messages will be delivered properly.
In relation to this the overload of e-mails, the consequence is that there is so much e-mail which
sometimes makes it difficult for the individual to distinguish between solicited and unsolicited e-mail,
as well as having the time to read through the e-mail.
Although e-mail marketing is known for its low costs, delivering a sophisticated e-mail newsletter
that engages the customer can be costly (Fariborzi, E., & Zahedifard, M. 2012). As can concluded
from the above mentioned, e-mail marketing campaigns need to be well designed and well written.
This may require a company to acquire or train employees with certain skills or even outsource the
whole process. Additionally, a company may also need to invest in the software to manage their e-
mail marketing campaigns.
The last disadvantages consist of the difficulty of displaying the content as intended within the in-box
of different e-mail reading systems. Your subscribers may want a message with "unsecured" items
24
such as colour, graphics and links that not all browsers will support. Finally, your recipient will
instantly close the window or you will have to just settle for the all-text E-mail (Fariborzi, E., &
Zahedifard, M. 2012).
2.5 The conceptual framework
From the above mentioned challenges start-ups face, it can be concluded that new ventures need to be
innovative, creative and especially cost saving in their marketing activities. Generally speaking, start-
ups cannot use the expensive traditional marketing channels because of its high price tags. For that
reason, many start-ups are struggling to gain legitimacy or even brand loyalty. Cost of marketing
plays a pivotal role and generally speaking, start-ups lack the human resources, internal structures and
critical skills in marketing. Next to that start-ups are facing a great amount of uncertainty which limits
them in their ability to make mistakes. One strategic choice in the field of marketing can mean a great
success but could also be fatal to a start-up. Therefore, new ventures need to use marketing channels
which are easy to execute but have a broad range.
Internet marketing refers to marketing activities using features from the internet like the world wide
web and electronic mail. The internet offers a great amount of opportunities in the field of marketing.
The internet offers an easier, cheaper and quicker way of communicating. Moreover, the Internet has
improved efficiency in the development and richness of the content of marketing activities.
As mentioned before many authors describe e-mail marketing as one of the most useful online
marketing tools. In addition to that according to a research conducted by Salesforce, state of
marketing (2015) 73% of the over 5000 globally interviewed marketers agreed that e-mail marketing
is core to their business.
E-mail marketing can be described as using electronic mail for delivering commercial messages to
customers and potential customers. E-mail marketing can be used for various marketing purposes. For
example, to share information about products and services, to promote them, to establish brands, to
guide customers to web sites, to alert customers, and to tell the status of orders (Merisavo, M., &
Raulas, M., 2004). Newsletters, are the most Common vehicles for establishing ongoing dialogue with
customers, because they provide a terrific mechanism for communicating a highly personalised blend
of information, entertainment, and promotions (Merisavo & Raulas, 2004).
Former literature shows there are several advantages of e-mail marketing over traditional marketing
channels. The main advantage obviously has to do with its favourable price tag and its convenience
from digital processing. These low costs and digital processing allow companies to send out huge
25
numbers of e-mails. In addition, e-mail marketing also offers potential for targeted and personalised
communication with customers. E-mail gives marketers the opportunity to customise messages for
different customers and provide contents and promotions that are consistent with their profile
(Fariborzi, E., & Zahedifard, M. 2012). The real-time one-to-one communication features e-mail
marketing with the advantages of faster delivery and easier response compared to traditional
marketing channels. The final advantage arises from the many factors of the performance of an e-mail
marketing campaign that can be monitored and measured easily.
The main disadvantage of e-mail marketing has to do with the deliverability of e-mails. Despite the
lucrative nature of e-mail marketing, consumers are overloaded with information, including both
wanted and unwanted communication (Pavlov et al., 2008). Windham (2000) as cited in Rettie et al.,
(2005) believes that unsolicited e-mail is considered an invasion of privacy, and has already become a
serious problem for some customers; spam taints the reputation of e-mail marketing. In relation to this
the overload of e-mails has the consequence that there is so many e-mail which sometimes makes it
difficult for the individual to distinguish between solicited and unsolicited e-mail. As well, a
depending factor is whether the individual receiving the email has the time to read it. Although e-mail
marketing is known for its low costs, delivering a sophisticated e-mail newsletter that engages the
customer can be costly (Fariborzi, E., & Zahedifard, M. 2012). The last disadvantages consist of the
difficulty of displaying the content as intended within the in-box of different e-mail reading systems.
According to Ellis-Chadwick, F., & Doherty, N. F. (2012) permission-based e-mails are in wide use
because of widespread consumer complaints about unsolicited e-mails (known as “spam”). The major
incentive for consumers to “opt in” to a firm’s e-mailing list is the prospect of receiving material that
matches their interests, as recipients are more likely to open and read such messages (Ellis-Chadwick
& Doherty, 2012). Consumers and customers treat their inbox as a personal domain. As long as
companies seek permission to send messages, and do not abuse this privilege, they have the ability to
build profile, awareness and, ultimately, a profitable relationship with that person (Chittenden, &
Rettie, 2003).
Permission given by the recipient influences the response rate positively. Di Ianni (2000) cited in
Sigurdsson et al., (2015) found that e-mail response rates ascend from 10% to 17% when e-mails are
sent to a targeted permission-based group rather than untargeted. Chittenden & Rettie (2003)
identified several other executional tactics that influence the response in e-mail marketing. These key
executional tactics can be divided in: The e-mail subject line, the creative design of the e-mail
content, the frequency and timing of the send out and the degree of personalisation. This response in
e-mail marketing can be measured in several ways, which measurements a company uses is highly
depended on the goal of the e-mail marketing campaign. According to the research conducted by
Salesforce, state of marketing (2015) the click-through rate, conversion rate and the open rate are the
26
most used metrics for e-mail marketing success.
The key objective for this research is to identify the effect of the use of e-mail marketing campaigns
by e-commerce start-ups on their marketing success. E-mail marketing use consists of the use of
newsletters as an e-mail marketing channel, and the effect will be explained by the above mentioned
measurements for the response on e-mail marketing campaigns. If the response is high, it will have a
positive effect on the marketing success and the other way around. Hence it will not determine the
marketing success of a start-ups on its own. The marketing success of a company can be expressed in
several ways and it can be influenced by many factors. According to Eid & El-Gohary (2013)
marketing success can be expressed as marketing performance and marketing effectiveness. Based on
the literature, it was found that the internet marketing adoption affects many issues that are related to
the marketing performance and effectiveness of the small businesses such as: new sales, new
customers, developing new markets and good customer relationships, improved productivity,
increased market share, increased brand equity, increased productivity. Since, there are so many
factors determining the marketing success, for this study the response will be analysed. The results
will display a positive or negative effect on the marketing success of the firm, but the response will
not determine the marketing success of a start-up.
Hence the dependent variable is the response of recipients on the e-mail marketing campaigns
conducted by the researched companies. The independent variables are the executional tactics
influencing the response on the e-mail marketing campaigns, which can be divided into e-mail subject
line, the creative design of the e-mail content, the degree of personalisation, permission given by the
recipient and frequency and timing.
2.5.1 The e-mail subject line
The subject line in the e-mail is the first point of contact and acts as a trigger to encourage the
message recipient to open the e-mail (Ellis-Chadwick & Doherty, 2012). The e-mail subject line
consists of: the subject matter and the e-mail sender.
2.5.2 The creative design of the e-mail content
27
The creative design of the e-mail content includes the e-mail headline, the length of the e-mail, the
use of colour and images, the use of animation, the brand logo, the use of hyperlinks and the use of
interactive features (Ellis-Chadwick & Doherty, 2012).
The e-mail headline; just like the subject line will contribute to the determination whether a recipient
will further engage in the e-mail.
The e-mail length; consists of the number of pages used to the display the content of the newsletter.
The use of colours; colours can be used in various ways; some newsletters will contain a distinctive
background colour instead of white. Additionally, colours can be used in the brand logo or the text of
the newsletter.
The use of images; in the research conducted by Ellis-Chadwick & Doherty (2012) The vast majority
of marketing e-mails; 91%, included an illustration. In 57% of the e-mails, multiple illustrations of
varying sizes were used, with the body text appearing above, below, or at the side of the illustrations.
In 24% of the e-mails, a catalogue layout was adopted, with multiple illustrations of equal size, and
body text under each. A rarer executional tactic, 11%, was the use of a single large illustration, which
is more suited to print adverts for low involvement products. The remaining 9% of the e-mails used
the traditional letter format, with no illustration.
The use of animation; according to experimental research Sundar & Kalyanaraman (2004) cited in
Ellis-Chadwick & Doherty (2012) animation is the most prominent attention-getting device in web
advertising and is far more effective than static advertising. However, the present study reveals that
only 2% of marketing e-mails used animation, and just one retail firm accounted for this result.
The brand logo; brand logos were used in 99% of the e-mails in this sample used by Ellis-Chadwick
& Doherty (2012). In all these cases the logo was positioned in the top left-hand section of the first
page. All managers interviewed confirmed this to be the most important position on the page.
The use of hyperlinks; according to Ellis-Chadwick & Doherty (2012) the optimal number of
hyperlinks for a marketing e-mail remains unclear. Nevertheless, the largest percentage of e-mails,
65%, have more than 10 links; and 35% have 10 links or fewer.
The use of interactive features; newsletters incorporate many interactive features such as the website
landing page, an unsubscribe link or a store locator. According to the study conducted by Ellis-
Chadwick & Doherty (2012) most popular interactive features are: Website landing page (100%),
Unsubscribe (98%), Order online (54%), Send an e-mail to the company (54%), Interactive customer
services (18%), Store locator (18%), and “Send the e-mail to a friend” (17%). The remaining 19
28
features occur in less than 10% of the e-mails and even a “blogging” invitation appears in one,
recognizing that the sample period ended in early 2007 before blogs became popular.
2.5.3 Personalisation
The degree of personalisation is determined by, for example; mentioning the name of the recipient in
the e-mail, sending messages for special occasions or selecting different products for different
recipients. In the research conducted by Ellis-Chadwick & Doherty (2012) the use and degree of
personalisation varied across companies in the sample. E-mails from 10 of the 20 retail firms, 50%,
used no personalisation.
2.5.4 Frequency and timing
Regarding the variable frequency and timing, they involve the number of e-mails sent in a certain
period and the time of the year the e-mails are sent. The frequency of an e-mail send out can for
example vary from 1 to 7 times a week. Some companies prefer to send their newsletter on a specific
day of the week or for example right before Christmas.
2.5.5 Permission
As mentioned before permission given by the recipient influences the response rate is positively. Di
Ianni (2000) cited in Sigurdsson et al., (2015) found that e-mail response rates ascend from 10% to
17% when e-mails are sent to a targeted permission-based group rather than untargeted. Hence in this
study we will assume that permission influences the response rate positively.
2.5.6 The response
The dependent variable; the response on the marketing campaigns conducted by e-commerce start-ups
is measured and explained by the open rate, the click-through rate and the conversion rate. Figure
2.5.1 displays The conceptual model which shows the variables and their relationships. The depend
29
variable in this model is the response, expressed by the open rate, click-through rate and the
conversion rate. According to this conceptual model the response is influenced by the independent
variables; the e-mail subject line, the creative design of the e-mail content, the frequency and timing,
personalisation and permission.
Figure 2.5.1 Conceptual model
Response
E-mail subject line
The creative design of
the e-mail content
Frequency and
timing
Marketing success
Personalisation
Permission
30
3. Methods
3.1 Research Design
The aim of this research is to identify the success of e-mail marketing campaigns for e-commerce
start-ups. Therefore, the response on the selected e-mail marketing campaigns of the selected
companies were analysed. The analysis is based on the available performance measurements such as
the open rate and the click-through rate of the e-mail marketing campaigns. Furthermore, the
executional tactics influencing the response on those campaigns were analysed. These tactics are
mentioned in the conceptual model of this study. They include: The e-mail subject line, the creative
design of the e-mail content, the frequency and timing, the degree of personalisation and the
permission given by the recipient. The research technique that was used to analyse these tactics is a
content analysis. Note that this study does not address the detailed content of each email message, as a
sophisticated analysis of this material is beyond the scope of this research. Foremost to management
research, content analysis provides a replicable methodology to access deep individual or collective
structures such as values, intentions, attitudes, and cognitions as such, content analysis is applicable to
a broad range of organizational phenomena (Duriau, V. J., Reger, R. K., & Pfarrer, M. D., 2007).
Furthermore, multiple sources of data can serve as inputs to content analysis, both internal and
external to the firm (Jauch, Osborn, & Martin, 1980 cited in Duriau et al., 2007). In their study,
Duriau et al., (2007) found that management researchers using content analysis leveraged the
conceptual and analytical flexibility afforded by the method to yield studies mixing inductive and
deductive approaches based on rigorous quantitative analysis as well as rich qualitative insight.
3.2 Operationalization
In this study, previous section the conceptual model was presented based on the existing literature. To
link theory to practice the conceptual model needed to be operationalised. In order to be assured that
the data from the e-mail marketing campaigns made a contribution and provided an answer to the
research questions the theory was operationalised in an operationalization schematic. This coding
scheme is presented in table 9.2 in the appendix. A coding scheme operationalizes concepts that may
in themselves be amorphous. It establishes categories that are relevant and valid. Relevant means that
they allow for testing the hypotheses. Validity refers to “the extent to which a measuring procedure
31
represents the intended, and only the intended, concept” (Neuendorf, 2002 cited in Marsh, E. E., &
White, M. D., 2006). The below displayed coding scheme is prepared on the basis of the elements
used in the study conducted by Ellis-Chadwick & Doherty (2012). The authors of this study
conducted a research more qualitative of nature, so the presented coding scheme could not be used in
its original form. Nevertheless, all the executional tactics used in e-mail marketing mentioned in this
study are displayed as category in the coding scheme. But then the way the variables are measured
and analysed deviates from the coding scheme used by Ellis-Chadwick & Doherty (2012).
3.3 Data collection
This research was conducted in collaboration with a Dutch company specialised in Lead generation
for e-commerce companies. In addition, the business consulted these companies in the practice of
email marketing. The company provides their clients with opt-in databases of potential clients which
they use to send out their newsletter in combination with their existing database. The companies in the
sample do their send outs exclusively on opt-in databases and as mentioned before according to the
former literature we assume that the variable permission has a positive influence on the response.
Therefore, the variable permission in the conceptual model was not further researched during this
study. The company provided access to the newsletters and data about the performance of the e-mail
marketing campaigns of several e-commerce start-ups in Europe. In addition, several e-commerce
start-ups have been contacted by the researcher himself for the results on their campaigns and their
newsletters. The information shared by these companies needs to be treated as confidential, therefore
the names of the companies will not be mentioned in the report. In the appendix a list with the names
of these companies is attached, for some exceptional readers.
3.3.1 The sample
This study included selecting 27 e-commerce start-ups in Europe. This sample was taken from the
total number of clients available to the company in different industries in several countries in Europe.
These different industries include: travel, daily deal sites and several web shops. The Countries where
the selected companies are located include: The Netherlands, Belgium, Italy, Poland and Australia.
The companies selected for this research were selected on the year they were founded. According to
Brush, (1995) cited in Zahra, S. A., Ireland, R. D., & Hitt, M. A. (2000) new venture firms are defined
as companies six years old or younger. In former research conducted by van Gelderen, M., Frese, M.,
& Thurik, R. (2000) a sample of firm owners with less than 50 employees and who had founded their
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firm during the previous five years was selected. But according to McDougall, P. P., Covin, J. G.,
Robinson, R. B., & Herron, L. (1994) a firm is considered a new venture if it is 8 years old or less.
Considering these different definitions, the companies that were selected during this research were not
older than eight years. Next to the age of the venture, the companies that were selected should at least
have their newsletter available, the open rate and the click-through rate. Except for these criteria the
sample was selected through convenience sampling, all the companies available to the researcher
were selected for this study.
3.4 Data analysis
From the 27 companies used for this study in total 39 newsletter send outs were analysed. The e-mail
marketing campaigns of the selected companies were content analysed on the basis of the provided
coding scheme. Furthermore, the open rates and click-through rates of the respective campaigns were
analysed. The information from the content analysis combined with the corresponding open rates and
click-through rates were reviewed to identify any key patterns in the executional tactics influencing
the response to the e-mail marketing campaigns. The data was imported into SPSS to conduct a
correlation analysis of the variables influencing the response and the open rates and click-through
rates. The purpose of this analysis is to review whether there are any specific elements of a newsletter
that affects the open rates and click-through rates of the e-mail marketing campaigns of start-ups.
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4. Results
The following chapter will present the findings that are related to the research questions three and
four.
What are the key executional tactics influencing the response to e-mail marketing?
How is the performance of e-mail marketing campaigns measured, and how well is this performance
for e-commerce start-ups?
The collected performance indicators and the analysis of the content of the newsletters will be
discussed. In the appendix 9.3 an overview of the results can be found, the other tables in the
appendix provide a detailed insight in the results.
4.1 The response
The dependent variable the response to the marketing campaigns conducted by e-commerce start-ups
is measured and explained by the open rate, the click-through rate and the conversion rate. During the
collection of the data it became clear that only a small percentage of the participating companies were
prepared to share their conversion rates. In addition to that the conversion rate is influenced by many
different external factors that were not available to the researcher. Hence in this study the response is
explained by the open rate and the click-through rate. The open rates and click-through rates of the
selected companies are displayed in table 9.4 in the appendix. The open rates and click-through rates
collected during this study will be compared with a benchmark for e-commerce companies. This
benchmark is deducted from an e-mail marketing metrics benchmark study (2015) conducted by
Silverpop, an IBM company.
4.1.1 The open rate
As mentioned before in the theoretical framework the open rate is a measure of how many people on
an e-mail list open (or view) a particular e-mail campaign. A high percentage of open rate increases
the chance of a successful marketing campaign (Bawm, Z. L., & Nath, R. P. D., 2014). The open rates
of the analysed e-mail marketing campaigns varied from 8,00% to 27,03% with an average open rate
of 18,02%. The average open rate from the benchmark report for the sector e-commerce was 18,3%,
which is consistent with the average open rate from this study. Since there is only a small deviation
from this benchmark it can be said that the open rates from the selected start-ups are relatively similar
to the industry average.
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4.1.2 The click-through rate
The click-through rate covers all receivers who clicked links in the received e-mails (Fassauer, R., &
Werner, A. 2015). Simply put the click-through rate describes the percentage of recipient that find a
newsletter relevant or intriguing enough to click on it (Regelson, M., & Fain, D., 2006). The click-
through rates of the analysed e-mail marketing campaigns varied from 0,10% to 10,00% with an
average click-through rate of 4,25%. The average click-through rate from the benchmark report for
the sector e-commerce was 3,2%, which is lower than the average open rate from the selected
companies for this study. Therefore, it can be said that the average click-through rate from the
selected start-ups is relatively positive. When combining the open rates and click-through rates from
the analysed e-mail marketing campaigns it can be concluded that the response and thus the
performance of the campaigns to the newsletters is relatively high.
4.2 The e-mail subject line
While analysing the subject line of the e-mail marketing campaigns this element was divided in the
subject matter and the e-mail sender. Several options were provided by the coding scheme mentioned
before. In table 9.5 in the appendix the results of the analysis are presented.
4.2.1 The subject matter
In the majority (38,46%) of the e-mail marketing campaigns analysed, the subject matter of the
newsletter was a ‘discount or saving’. In 23,07% of the analysed newsletters the subject matter was an
‘occasional or seasonal promotion’. The subject matter of 17,95% of the newsletters consisted of a
‘bonus offer’. In 10,25% of the studied newsletter the subject matter ‘newsletter’ occurred. The
subject matter of only one of the total number of newsletters was ‘product details’. The subject matter
‘contest’ occurred also in only one of the total amount of newsletters studied. Two newsletters
analysed had other subject matters than the provided options in the coding scheme. One of these other
subject matters consisted of a ‘price comparison’ and the other newsletters subject line was empty.
For further analysis, a Pearson correlation analysis was conducted on the most popular subject
matters. The objective of this analysis was to discover a relationship between the independent variable
subject matter and the associated dependent variables open rate and click-through rate.
The results of this test showed that if the subject matter is a ‘discount’ this has a significant negative
influence on the open rate (r = -.459, n=39, p=0,03 Correlation is significant at the level 0.01 (2-
tailed)). According to the results the subject matter ‘discount’ has no significant effect on the on the
click-through rate. Therefore, it can be said that according to these results choosing the subject matter
‘discount’ will decrease the dependent variable ‘response’.
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The results of the Pearson correlation test show no significant effect of the subject matter ‘occasional
or seasonal promotion’ on the associated open rate. Nevertheless, there seems to be a significant
positive relation between the subject matter ‘occasional or seasonal promotion’ and the click-through
rate (r = .362, n=39, p=0,075 Correlation is significant at the level 0.05 (2-tailed)). According to these
results the subject matter ‘occasional or seasonal promotion’ has no influence on the open rate, but
has a positive influence on the click-through rate. Due to this positive effect the subject matter
‘occasional or seasonal promotion’ seems to influence the dependent variable response positively.
According to the output from the analysis there seems to be a positive relation between the subject
matter ‘bonus offer’ and the open rate (r = .350, n=39, p=0,029 Correlation is significant at the level
0.05 (2-tailed)). Furthermore, there seems to be no significant relation between the subject matter
‘bonus offer’ and the click-through rate. Since there is a positive relation between the subject matter
‘bonus offer’ and the open rate it can be said that putting ‘bonus offer’ in the subject line of the e-mail
may increase the response to the campaign.
The correlation analysis of the subject matter ‘newsletter’ presented no significant influence on the
open rate or click-through rate. And therefore it can be said that choosing newsletter as the subject of
the e-mail will not increase or decrease the response.
4.2.2 The e-mail sender
The vast majority (87,17%) of the e-mails analysed presented ‘only the company name’ as the e-mail
sender. While only 5,13% of the newsletters displayed ‘the company name and the key benefit claim
of the brand’ as the e-mail sender. The other three e-mails presented only ‘the e-mail address
including the company’s name’, ‘the company web address only’ or ‘the company name plus the
word newsletter’ as e-mail sender.
Owing to the fact that almost every newsletter in the sample presented the e-mail sender in the same
way, there is no point in further analysing the results for correlation with the open rates and click-
through rates. As a result of that no conclusions about the influence of the e-mail sender on the
dependent variable response can be drawn.
4.3 The creative design of the e-mail content
On the basis of the provided coding scheme the content of the newsletters was analysed. The creative
design of the content is divided in several different executional tactics, which were al reviewed one by
one. These elements are researched to see how the response of e-mail marketing campaigns can be
influenced by the creative design of the e-mail content. Since the recipient is exposed to the content of
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the e-mail after opening the e-mail, the Pearson correlation analysis will be done exclusively on the
click-through rate. Table 9.6 in the appendix the results of the content analysis are presented.
4.3.1 The e-mail headline
The first executional tactic that was reviewed is the e-mail headline. The e-mail headline, just like the
subject line will contribute to the determination whether a recipient will further engage in the e-mail.
In this study 64,10% of the newsletters analysed used a distinct headline. A Pearson correlation
analysis was conducted to see if having a distinct headline influences the click-through rate of the
sample. However, the results showed no significant relation between this independent variable and the
dependent variable. Thus, according to these results it can be concluded that the response is not
increased or decreased by having a distinct headline in a newsletter.
4.3.2 The e-mail length
The length of the analysed e-mail marketing campaigns varied between one and five pages, with an
average of 2.05 pages. 41,03% of the newsletters were two pages long. The length of 30,77% of the
newsletters was one page and, 23,08% was three pages. Only two newsletters were longer then three
pages. According to the results of the Pearson correlation test there seemed to be no significant
relation between the length of the e-mail and the related click-through rates. Hence, it can be said that
according to the result of this analysis the length of the e-mail does not seem to increase or decrease
the dependent variable response.
4.3.3 The use of colours
To learn about the influence of the use of colours in newsletters the selected newsletters have been
analysed on the use of colours. It appeared that in the vast majority (89,74%) of the analysed
newsletters colours were used. It was also studied what specific colours were used, however owing to
the fact that some campaigns were from the same company these results were not relevant. Some
companies will use a specific colour in the logo or layout and therefore this colour will appear more
often in the results. In this study the correlation analysis presented no significant relation between the
use of colours in the newsletters in this sample and the corresponding click-through rates. Therefore,
according to this analysis the use of colours in newsletters does not influence the response to the e-
mails in a positive or negative way. Nevertheless, since such a high percentage used colours it may be
assumed that the use of colours will positively influence the dependent variable.
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4.3.4 The use of images
The next element of the creative design of the e-mail content that has been studied is the use of
images in newsletters. After analysing the content of the newsletters used for this study it appeared
that a high percentage (87,18%) included images. The way the images were organized in the
newsletter was also analysed on the basis of the provided coding scheme. In 38,46% of the e-mails,
multiple illustrations of varying sizes were used, with the body text appearing above, below, or at the
side of the illustrations. In 38,46% of the e-mails, a catalogue layout was adopted, with multiple
illustrations of equal size, and body text under each. A rarer executional tactic, 12,82% was the use of
a single large illustration, which is more suited to print adverts for low involvement products. The
remaining 10,25% of the e-mails used the traditional letter format, with no illustration.
Since such a high percentage of newsletters included illustrations the results of the Pearson correlation
analysis conducted showed no significant relation between the use of images in newsletters and the
click-through rate. So according to the results no further conclusions on the influence of the use of
images can be drawn. But since such a high percentage of the selected companies use images in their
newsletter it may be assumed that it will have a positive effect on the response to the newsletters.
4.3.5 The use of animation
As explained earlier the study by Ellis-Chadwick & Doherty (2012) revealed that only 2% of the
marketing e-mails used animation, and just one retail firm accounted for this result. For this study the
results were even more clear, none of the companies used animation in their newsletter. For this
reason, this element was not further investigated. Consequently, no conclusions can be drawn on the
influence of the use of animation in newsletters.
4.3.6 The use of interactive features
During this study it appeared that every newsletter was using interactive features. The on forehand
provided coding scheme made the distinction between different interactive features used in marketing
e-mails. The most popular interactive features were: Website landing page (97,44%), Unsubscribe
(100%), Order online (87,17%), Send an e-mail to the company (53,85%), Interactive customer
services (30,77%), Store locator (5,12%), and “Send the e-mail to a friend” (7,69%). These results
show the same pattern as the research conducted earlier by Ellis-Chadwick & Doherty (2012) except
for one type of interactive feature. During this study an additional interactive feature was discovered,
74,36% of the newsletters provided the recipient with a button to visit the social media page of the
company. Owing to the fact that in every single newsletter analysed an interactive feature was present
the assumption can be made that, providing the recipient with an interactive feature will influence the
response positively.
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4.3.7 The use of hyperlinks
According to the former literature the optimal number of hyperlinks for a marketing e-mail remains
unclear. The number of hyperlinks in the newsletters in this study varied from 2 to 46 in this study,
with an average of 18,69 hyperlinks. For further analysis, the number of hyperlinks were classified as,
more than 10 hyperlinks or 10 hyperlinks or less. The largest percentage of e-mails, 66,66%, had
more than 10 links; and 33,33% had 10 links or less. The outcome of the Pearson correlation test
showed that there is a positive significant effect between the number of hyperlinks and the click-
through rate (r = .402, n=39, p=0,011 Correlation is significant at the level 0.05 (2-tailed)).
Accordingly, if the newsletter presented more than 10 hyperlinks, the recipient was more likely to
click on a hyperlink. Therefore, it may be assumed that providing the recipient with more than 10
hyperlinks will increase the dependent variable response.
4.3.8 The brand logo
In 97,44% of the analysed newsletters the brand logo was used, 74,56% positioned the brand logo in
the top left corner of the e-mail. In the other 20,51% of the newsletter the logo was positioned in the
centre at the top of the page and, the remaining two newsletters the position of the logo was different
or the brand logo was not displayed in the e-mail. Since almost every newsletter displayed their brand
logo, no further statistical analysis was conducted and the assumption is made that displaying the logo
of the brand will increase the response to the e-mail marketing campaign.
4.4 The e-mail frequency
The original purpose of this research was to study both executional tactics, the e-mail frequency and
the timing. The frequency involves the number of e-mails sent in a certain period and the timing
consists of the time of the year the e-mails are sent. Due to the short period in which this research was
conducted and the lack of information about the period in which the newsletters were sent, the factor
timing was left out. Nevertheless, the the frequency of the e-mail send outs was analysed and
presented in number of e-mails sent per week. Table 9.7 in the appendix shows the number of e-mails
sent per week for all the analysed e-mail marketing campaigns. The number of e-mails sent per week
varied from one e-mail per week to seven e-mails per week with an average of 3,33 e-mails sent per
week.
A Pearson correlation analysis was conducted to see if there would be a relationship between the
frequency of the newsletters sent and the open rate and click-through rates. Unfortunately, according
to this analysis the e-mail frequency seemed to have no significant effect on the response of the
39
recipient. Therefore, according to these results no further conclusion about the influence on the
dependent variable can be drawn.
4.5 Personalisation
Table 9.8 in the appendix presents the results from the content analysis on the personalisation of the e-
mail marketing campaigns. In 23,07% of the analysed newsletters personalisation was used, so nine of
the thirty-nine e-mail marketing campaigns were personalised. So in 76,93% of the campaigns no
personalisation was used. The extent to which they were personalised was also studied. According to
the provided coding scheme a distinction was made between specific details of the recipient such as
Name and non-specific such as “Dear customer”. In seven from the nine newsletters (77,77%) in
which personalisation was used the name of the recipient was mentioned in the newsletter. In the
other two newsletters (22,23%) non-specific personalisation was used.
The correlation analysis presented no significant relationship between the variable personalisation and
the open rate. Additionally, the results of the correlation analysis with the click-through rate identified
a negative relationship between the variable personalisation and the click-through rate (r = -.333,
n=39, p=0,038 Correlation is significant at the level 0.05 (2-tailed)). Thus, it can be concluded from
the results in this study that personalisation may decrease the dependent variable response.
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5. Discussion
The following chapter will compare the findings of this study with the findings in the existing
literature. Which ultimately will result in answering the on forehand determined research questions
three and four as complete as possible. The research questions three and four are:
What are the key executional tactics influencing the response to e-mail marketing?
How is the performance of e-mail marketing campaigns measured, and how well is this performance
for e-commerce start-ups?
As mentioned earlier the response to the analysed e-mail marketing campaigns for this study is
expressed by the open rate and the click-through rate. To gain a better insight in the performance of
the analysed e-mail marketing campaigns, the results of this research are compared with a benchmark
for the performance rates. The open rates and click-through rates collected during this study are
compared with a benchmark for e-commerce companies. Since, the existing literature on the subject
did not provided a recent benchmark for this study another benchmark was found. This benchmark
was obtained from an e-mail marketing metrics benchmark study (2015) conducted by Silverpop, an
IBM company. Silverpop is a cloud-based digital marketing provider that offers email marketing,
lead-to-revenue management and mobile engagement solutions. For this study the researchers
collected e-mail marketing metrics from 750 companies all over the world. One factor that
distinguishes Silverpop’s annual benchmark survey is that it goes beyond simply reporting statistics to
look at how industry verticals compare on their performances. An overview of the benchmark for the
response rates as compared with the results of this study can be found in appendix 9.9.
The content analysed executional tactics are benchmarked with the results from the study conducted
by Ellis-Chadwick & Doherty (2012). An overview of their results as compared with the results of
this study is presented in appendix 9.10.
5.1 The response
After comparing the response rates with the average response rate in the e-commerce industry it
appeared that the performance of the e-mail marketing campaigns of the selected e-commerce start-
ups was relatively high. The open rate was only a fraction (0,28%) lower than the industry average,
but the click-through rate was 1,05% higher than the benchmark. Therefore, it can be concluded that
e-mail marketing campaigns of the selected e-commerce start-ups for this study performed well.
This was expected from the analysis of the existing literature regarding the marketing needs of
resource limited start-ups. From the literature it became evident that new ventures need to be
innovative, creative and especially cost saving in their marketing activities. E-mail marketing offers
41
the solution for those needs which became clear from the analysis of the existing literature on internet
marketing. According to Chittenden, L., & Rettie, R. (2003) any way to communicate that is easier,
cheaper or quicker always has high appeal, the Internet offers all three. E-mail marketing as a
marketing channel in particular matches those needs with the advantages mentioned earlier. It is
relatively cheap, allows for targeted and personalised communication with customers, features real-
time one-to-one communication and the performance of the campaigns can be monitored and
measured easily.
5.2 The e-mail subject line
As stated in the existing literature, research conducted by Chittende & Rettie (2003) identified a
significant relationship between response rate and the subject line. According to Ellis-Chadwick &
Doherty (2012) the subject line of an e-mail must grab the initial attention of the customer and prompt
him or her to open the e-mail; otherwise, there is no opportunity for sustained attention; the message
can be deleted and never seen again. Therefore, the importance of a well structured subject line is
thoroughly addressed in their study. As mentioned earlier they identified two parts of the subject line
which have the potential to grab attention: (1) sender – is the e-mail from a source in which the
receiver will be interested; and (2) subject – is the receiver interested, intrigued, or motivated by the
subject matter? This division of the subject line is used for this research as well.
The results of the analysis of the subject line of the selected e-mail marketing campaigns were
consistent with the expectations from the existing literature. It appeared that every analysed newsletter
had a distinct subject line. The two most frequently used subject matters in the sample used for this
study were the same as the two most used subject matters from the research conducted by Ellis-
Chadwick & Doherty (2012). It appeared from the Pearson correlation analysis that using some
specific subject matters can have a positive or negative significant effect on the response rate. Not all
of the analysed subject matters showed a significant effect. Nevertheless, since some subject matters
did have a significant effect on the response rates, it can be concluded that the subject matter
influences the response rates.
Regarding the e-mail sender Ellis-Chadwick & Doherty (2012) expected there would be one approach
applied to identify the sender but five alternatives were identified in their study. Based on those
results prior to the analysis for this study it was expected that several approaches would be found.
Nevertheless, the vast majority of the analysed newsletters presented only the company name as the e-
mail sender. The other five alternatives were also present in a small percentage of the analysed
newsletters and no other approaches were identified.
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5.3 The creative design of the e-mail content
From analysing the available literature on this subject it became apparent that the creative design of
the e-mail content influences the response rate. The several different elements mentioned, were
analysed and finally statistically tested for any relationship with the dependent variable. As mentioned
earlier, according to former research conducted on e-mail marketing campaigns all these elements
seem to influence the response rate in some way. However, as a result of the statistical analysis only a
few significant relationships between the independent and dependent variables were discovered.
In the research conducted by Ellis-Chadwick & Doherty, (2012) the vast majority of e-mails in their
sample (76%) employed a distinct headline in addition to and underneath the subject line. A similar
percentage (64,10%) was discovered during this study. However, no significant relationship with the
response rate was found. Since the e-mail headline should link to the subject line of the e-mail and to
the body copy it may be assumed that this executional tactic should influence the response rate.
Unfortunately, no statistical evidence for that was obtained during this study.
In the research conducted by Ellis-Chadwick & Doherty, (2012) the length of e-mails ranged from 1
to 5 pages and the average length was 2.4 pages. Similar results were obtained during this research
with a range from 1 to 5 pages and the average e-mail length was 2.05 pages. In the interviews
conducted by Ellis-Chadwick & Doherty, (2012) two of the nine interviewed managers believed that
length has a negative effect on the response. Nevertheless, after a Pearson correlation analysis in this
study no significant relationship between the e-mail length and the response was discovered.
In the research conducted by Ellis-Chadwick & Doherty (2012) the vast majority of marketing e-
mails, 91%, included an illustration. The results from this research appeared to be similar, 87,18% of
the analysed newsletters contained images. Pictures (illustrations) may be the most powerful way to
attract the attention of a consumer towards a print ad (Rossiter and Bellman, 2005 cited in Ellis-
Chadwick & Doherty, 2012) but pictures alone will not work for an e-mail campaign. Due to the high
percentage of newsletters containing images, the assumption that the use of images will positively
influence the response rate seems to be acceptable.
In order to develop sustained attention or “engagement” with an e-mail message, personalization,
interactive features, and hyperlinks to web pages seem to be the most effective tactics according to
Ellis-Chadwick & Doherty (2012). The e-retailer may elect to include a broad range of interactive
features in order to sustain prospective customers’ attention (Ellis-Chadwick & Doherty, 2012). The
results from this research and the results from the research conducted by Ellis-Chadwick & Doherty
(2012) were consistent regarding the most popular interactive features. In every single newsletter
analysed at least one interactive feature was present. Therefore, the assumption that interactive
features influence the response positively seems to be correct.
43
The results from this research showed that 66,66% of the e-mails had more than 10 hyperlinks. Which
is similar to the results from the research conducted by Ellis-Chadwick & Doherty (2012) they found
that the largest percentage of e-mails, 65%, have more than 10 links; and 35% have 10 links or fewer.
The correlation analysis regarding the number of hyperlinks unveiled that it may be assumed that
providing the recipient with more than 10 hyperlinks will increase the dependent variable response.
Consequently, the assumption that hyperlinks influence the response rate positively seems to be
correct.
Concerning the brand logo, in the study conducted by Ellis-Chadwick & Doherty (2012) Brand logos
were used in 99% of the e-mails in this sample. The results from this research seem to be consistent
with those results since in 97,44% the logo of the brand was used. Due to the fact that no statistical
analysis was conducted and the insufficient attention that is paid to this element in the former
literature, the brand logo seems to be more of a necessity than an executional tactic that seems to
influence the response rate.
5.4 The e-mail frequency
According to the research conducted by Ellis-Chadwick & Doherty (2012) the frequency and timing
of the send out influences the response. Their analysis acknowledged an average e-mail frequency of
2,4 e-mails per month, which are 0,6 e-mails sent per week. This average number of e-mails sent per
week deviates a lot from the results from this study. As a result of the analysis an average of 3,33 e-
mails sent per week was found. After conducting a Pearson correlation analysis no significant effect
on the dependent variable was found. And therefore no conclusions regarding the influence of the
frequency on the response can be drawn. Which was against the expectations from analysing the
existing literature. Since the Frequency of sending e- mails is an important part of building customer
relationships: too many might irritate and too few could lose the recipient’s interest (Ellis-Chadwick
& Doherty, 2012).
5.5 Personalisation
As mentioned before, according to Pavlov et al. (2008) personalisation is found to be desirable to
increase the response on e-mail marketing campaigns. Furthermore, Colkin (2001) cited in
Sigurdsson et al., (2015) found congruent results, indicating that when a recipient’s name was added
to the subject line, response rate doubled to more than 12% over non-personalised e-mails. In the
research conducted by Ellis-Chadwick & Doherty (2012) fifty percent of the analysed firms used
personalisation in their e-mail marketing campaigns. And as a result of the interviews conducted by
them the majority of the managers believed that personalizing e-mails is important because they
expect personalized emails to perform better than non-personalized e- mails.
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The percentage of newsletters in which personalisation was used appeared to be lower than expected,
in only 23,07% personalisation was used. Furthermore, in contrast to the expectations from the
analysed literature the correlation analysis presented no significant relationship between the variable
personalisation and the open rate. Even more striking were the results of the correlation analysis with
the click-through rate, there appeared to be a negative relationship between the variable
personalisation and the click-through rate. Hence, this study can not concur with the expectations of
the existing literature since no proof was found that personalisation is desirable.
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6. Conclusion
6.1 Conclusions
The aim of this research was to explore and describe the practice of e-mail marketing in the context of
a resource-limited e-commerce start-up while measuring the performance of several e-mail marketing
campaigns of different companies. The goal was to discover whether there is a fit between the use of
e-mail marketing and resource-limited e-commerce start-ups or not. In addition, by conducting a
content analysis on the executional tactics in e-mail marketing, this research aimed to provide
recommendations on how e-mail marketing campaigns can be optimized.
From the earlier mentioned and analysed challenges start-ups face, it can be concluded that new
ventures need to be innovative, creative and especially cost saving in their marketing activities.
Generally speaking, start-ups cannot use the expensive traditional marketing channels because of its
high price tags. The internet offers an easier, cheaper and quicker way of communicating. Moreover,
the Internet has improved efficiency in the development and richness of the content of marketing
activities.
As mentioned before many authors describe e-mail marketing as one of the most useful online
marketing tools. The many advantages of e-mail marketing over traditional marketing channels were
addressed and analysed. Due to the fact that e-mail marketing offers many advantages over traditional
marketing channels, e-mail marketing was expected to have a positive effect on the marketing success
of e-commerce start-ups.
The key objective for this research was to identify the effect of the use of e-mail marketing campaigns
by e-commerce start-ups on their marketing success. After analysing the response rates of the e-mail
marketing campaigns of the selected start-ups, the response appeared to be relatively high. Therefore,
it can be concluded that e-mail marketing seems to have a positive effect on the marketing success of
e-commerce start-ups. Furthermore, there seems to be a fit between the use of e-mail marketing and
resource-limited e-commerce start-ups.
6.2 Limitations
As every research this study comes with some limitations. The first limitations for this research has to
do with the sample. For this thesis a sample was selected from the companies available to the
researcher, only 27 companies were selected. This sample was not taken from all existing start-up
companies. Therefore, the sample contained companies with little variation regarding the industry.
Additionally, the majority of the selected companies are located in a few different countries in
Europe. Furthermore, the companies in the sample were already buying opt-in databases to perform
their e-mail marketing on. Therefore, the assumption can be made that those companies were already
experienced with e-mail marketing in some way. As a consequence, it remains uncertain if the results
46
of this research are transferable. According to Saunders et al. (2009), whether this would be the same
in other in other setting is dependent on the external validity.
Secondly, the time period in which this study was conducted was relatively small. As a result, it was
difficult to obtain enough newsletters from different periods of a year. Therefore, no further research
could be done on the timing of the send-outs of the e-mail marketing campaigns.
The third limitation concerns the measurement of the response. In the theoretical framework the
conversion rate appeared to be one of the best measurements for the success of e-mail marketing
campaigns. Unfortunately, the conversion rates of the newsletters from the selected companies were
not available to the researcher. Therefore, conclusion regarding the response are somewhat
incomplete.
Lastly, the nature of this study is quantitative therefore the researcher might miss out on phenomena
occurring because of the focus on theory or hypothesis testing rather than on theory or hypothesis
generation. A qualitative content analysis may provide a more complete image of the phenomenon e-
mail marketing. Additionally, this will provide the opportunity to capture new elements in stead of
researching the elements based on the existing literature.
6.3 Future research
The above mentioned limitations inevitably lead to opportunities for future research. This research
should be repeated with a bigger sample consisting of a wider variation of the industries and countries
the start-ups are active in. This eventually will benefit the transferability and external validity of the
research.
Secondly, the research demonstrated that it may be assumed that e-mail marketing is a successful
marketing channel for e-commerce start-ups. Further research may elaborate on this by studying the
success of e-mail marketing campaigns in terms of how much e-mail marketing can contribute to the
marketing success of e-commerce start-ups.
Furthermore, this study focused on discovering the effect of several executional tactics on the
response rate of the e-mail marketing campaigns. The influence of some executional tactics are
initiated and analysed. Consequently, future research is now required to understand which
combinations of specific executional elements offer the greatest potential for optimizing the
customers’ response to e-mail marketing campaigns.
47
7. Recommendations
As a result of the content analysis of the executional factors combined with the analysed literature on
the subject, several recommendations for the optimization of the response to e-mail marketing
campaigns can be made. Therefore, this sections aims to provide the answer to the fifth research
question as presented earlier;
How can the response of consumers be optimized for e-mail marketing campaigns of e-commerce
start-ups when using e-mail marketing on opt-in databases?
After examining the results of the content analysis on the executional tactics of the e-mail marketing
campaigns some recommendations for optimizing the response may arise. When combining the
results with the existing literature on the subject some concrete recommendations can be made.
Since the subject line of an e-mail must grab the initial attention of the customer and prompt him or
her to open the e-mail, the content of subject line is critical. As a result of the statistical analysis some
subject matter seemed to have influence on the response rate of the campaigns. So, variant testing to
determine which subject line is most effective is advised.
According to former literature the frequency of sending e-mails is an important part of building
customer relationships: too many might irritate and too few could lose the recipient’s interest. The e-
mail frequency is also dependent on the type of company that is sending the e-mail. For example, a
daily deal website should send newsletters on a daily basis. While another company offering a less
broad assortment of products should not send customers the same offers more than once a week. For
those other companies it is advised to test the effect on the response rates by changing the frequency
of the send outs to determine the optimal number of e-mails to send per week.
Personalisation should improve click-through rates, but there is an appropriate level of personalisation
which is dependent upon the stage of the customer relationship and the personal data volunteered by
the customer (Ellis-Chadwick & Doherty, 2012).
Concerning the creative design of the e-mail content, it can be concluded that the use of interactive
features and hyperlinks increase the click-through rate of the newsletter. In order to develop sustained
attention or “engagement” with an e-mail message, personalization, interactive features, and
hyperlinks to web pages seem to be the most effective tactics according to Ellis-Chadwick & Doherty
(2012). Therefore, it is advised to make sure an e-mail marketing campaign includes hyperlinks and
interactive features.
Regarding all executional tactics, one of the advantages of e-mail marketing is the vast amount of
tracking tools and statistics that are available. Many factors of the performance of an e-mail marketing
campaign can be monitored and measured easily. It is impossible to provide a specific plan for the use
48
of the executional tactics in e-mail marketing, since no e-commerce company is the exactly the same.
Therefore, it is advised to test different approaches and keep adjusting the executional tactics to
optimize the customers’ response to the e-mail marketing campaigns.
49
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53
9. Appendices
Appendix 9.1 The conceptual model
Response
E-mail subject line
The creative design of
the e-mail content
Frequency and
timing Marketing success
Degree of
personalisation
Permission
54
Table 9.2 The coding scheme
Category: Dimension: Indicator:
1. The e-mail
subject line
1.1 Subject
matter
a. Discount/saving
b. Product details
c. Newsletter
d. Occasion or
seasonal promotion
e. Teaser
f. Action prompt
g. Sale
h. Contest
i. In-store events
j. Money off
k. Free gift
l. Bonus offer
m. Other
1.2 E-mail
sender
a. Company name
only
b. Company name
plus the word
newsletter
c. E-mail address
including the
company name
d. Company web
address only
e. Company name and
the key benefit
claim of the brand
f. Other
55
2. The creative
designs of the e-
mail content
2.1 E-mail
headline
1. Yes
0. No
2.2 E-mail length Number of pages (ratio)
2.3 Use of
colours
1. Yes
0. No
2.3.1 What
colour?
2.4 Use of
images
1. Yes
0. No
2.4.1 The
number of
images used
a. Multiple images
varying in size
b. Multiple images
same size in
catalogue layout
c. One single large
image
d. Other
2.5 Use of
animation
1. Yes
0. No
56
2.6 The use of
interactive
features
a. Website landing
page
b. Unsubscribe
c. Order online
d. Send an e-mail to
the company
e. Interactive
customer services
f. Store locator
g. Send the e-mail to a
friend
h. Other
2.7 Use of
hyperlinks
Number of hyperlinks
(ratio)
2.8 Brand logo 1. Yes
0. No
2.8.1 Position of
the brand logo
a. Top left
b. Top right
c. Top centre
d. other
3. The degree of
personalisation
3.1
Personalisation
used
1. Yes
0. No
57
3.2 How is the
newsletter
personalised
a. Specific details of the
recipient such as Name
b. Non-specific such as
“Dear customer”
4. Frequency and
timing
Average number e-mails
sent per week (ratio)
Table 9.3 Overview results
1 The e-mail subject line:
1.1 Subject matter: Discount/Saving 38,46% Promotion 23,07% Bonus offer 17,95%
1.2 E-mail sender: Company name only 87,18% Company name and the key benefit claim of the brand 5,13%
2 The creative design of the e-mail
content:
2.1 E-mail headline: Yes 64,10% No 35,90%
2.2 E-mail length: 2 pages 41,03% 1 page 30,77% 3 pages 23,08%
2.3 Use of colours: Yes 89,74% No 10,26%
2.3.1 What colour: Orange 34,29% Blue 34,29% Yellow 28,57%
2.4 The use of images: Yes 87,18% No 12,82%
2.4.1 The number of images used: Multiple images varying in size 42,86% Multiple images same size 42,86% One single large image 14,28%
2.5 The use of animation: No 100%
2.6 The use of interactive features: Unsubscribe 100% Website landing page 97,44% Order online 87,17%
2.7 The use of hyperlinks: >10 66,66% <10 33,33%
2.8 Brand logo: Yes 97,44% No 2,56%
2.8.1 Position of the brand logo: Top left 74,36% Top centre 20,51% Other 2,56%
3 The degree of personalisation:
3.1 Personalisation used: Yes 23,07% No 76,93%
3.2 How is the newsletter personalised: Specific details 77,77% Non-specific details 22,23%
Average: Standard deviation: Median:
4 Frequency and timing: 3,33 per week 1,88 per week 3 per week
5 The response rate:
5.1 Open rate: 18,02% 0,06% 19,45%
5.2 Click-through rate: 4,25% 0,03% 4,40%
Table 9.4 Open rates and Click-through rates per campaign
Open rate: Click-through rate:
Company 1: 12,01% 4,60%
Company 2: 11,65% 3%
Company 3: 14,06% 2,36%
Company 4: 10,59% 2,60%
Company 5: 15% 4,50%
Company 6: 19,50% 0,70%
Company 7: 8,00% 0,10%
Company 8: 12,60% 0,20%
Company 9: 9,20% 0,20%
Company 10: 23,70% 1,10%
Company 11: 21,20% 7,32%
Company 12: 18% 3,00%
Company 13: 15% 4%
Company 14: 8,50% 3,10%
Company 15: 16,25% 4,96%
Company 16: 21% 5,30%
Company 17: 11,09% 2,72%
Company 18: 23,51% 0,62%
Company 19: 24,35% 0,44%
Company 20: 27,03% 0,56%
Company 21: 19,33% 6,40%
Company 22: 25,22% 7,80%
Company 23: 18,32% 7,10%
Company 24: 20% 10%
Company 25: 20% 10%
Company 26: 20% 10%
Company 27: 31% 6%
Company 28: 10,60% 0,30%
Company 29: 22,13% 4,77%
Company 30: 19,45% 4,47%
Company 31: 16,80% 4,20%
60
Company 32: 12,40% 2,60%
Company 33: 20% 3,57%
Company 34: 15,30% 4,53%
Company 35: 22,30% 6,54%
Company 36: 25,23% 8%
Company 37: 21% 6%
Company 38: 19,60% 4,40%
Company 39: 21,70% 7,60%
Table 9.5 The e-mail subject line
Subject matter: E-mail sender:
Company 1: m. a.
Company 2: a. a.
Company 3: m. a.
Company 4: a. a.
Company 5: b. a.
Company 6: l. a.
Company 7: a. a.
Company 8: f. a.
Company 9: a. a.
Company 10: c. a.
Company 11: d. a.
Company 12: a. d
Company 13: c. e.
Company 14: a. a.
Company 15: a. a.
Company 16: l. a.
Company 17: a. a.
Company 18: d. a.
Company 19: l. a.
Company 20: l. a.
Company 21: l. a.
61
Company 22: l. a.
Company 23: l. a.
Company 24: d. a.
Company 25: d. a.
Company 26: d. a.
Company 27: d. a.
Company 28: d. a.
Company 29: h. a.
Company 30: d. a.
Company 31: a. a.
Company 32: a. a.
Company 33: c. c.
Company 34: c. a.
Company 35: d. a.
Company 36: a. a.
Company 37: a. b
Company 38: a. e.
Company 39: a. a.
Table 9.6 The creative design of the e-mail content
headline:
length:
Use of
colours: What colour:
Use of
images:
The number of
images used:
Use of
animation:
Use of
interactive
features: Use of hyperlinks:
Brand
logo:
Position of the
brand logo:
Company 1: 1. 1 page 1. Green/Blue 1. c. 0. a, b, c 16 1. a.
Company 2: 1. 1 page 1.
Yellow/Orange/
Grey 1. a. 0. a, b, c, f, h 3 1. d.
Company 3: 1. 1 page 1.
Yellow/Orange/
Grey 1. c. 0. a, b, h 3 1. a.
Company 4: 1. 2 pages 1.
Blue/Yellow/Gre
en/Red 1. b. 0. a, b, c 40 1. a.
Company 5: 0. 5 pages 1. Red/Grey 1. b. 0. a, b, c 24 1. a.
Company 6: 1. 1 page 1. Orange 1. c. 0. a, b, c, d, e, h 7 1. c.
Company 7: 1. 1 page 1. Orange 1. c. 0. a, b, c, d, e, h 7 1. c.
Company 8: 0. 1 page 1. Orange 1. c. 0. a, b, c,, h 7 1. c.
Company 9: 1. 1 page 1. Orange 0. - 0. a, b, c,, h 8 1. c.
Company 10: 1. 1 page 1. Orange 0. - 0. a, b, c,, h 10 1. a.
Company 11: 1. 3 pages 1. Pink/Green 1. b. 0. a, b, c, d 28 1. a.
Company 12: 1. 2 pages 1. Blue/Green 1. a. 0. a, b, c, d, e, f 26 1. c.
Company 13: 1. 1 page 1. Green/Pink 0. - 0. a, b, d 3 1. a.
Company 14: 0. 1 page 1. Yellow/Blue 1. b. 0. b. 2 1. a.
Company 15: 1. 2 pages 1. Blue 1. a. 0. a, b, c, e, h 16 1. a.
63
Company 16: 1. 2 pages 1. Red 1. a. 0. a, b, c, h 27 1. a.
Company 17: 0. 2 pages 1. Pink 1. b. 0. a, b, c, d, e 24 1. a.
Company 18: 0. 3 pages 1. Blue 1. a. 0. a, b, c, d, h 28 1. a.
Company 19: 0. 3 pages 1. Blue 1. a. 0. a, b, c, d, h 27 1. a.
Company 20: 0. 3 pages 1. Blue 1. a. 0. a, b, c, d, h 26 1. a.
Company 21: 1. 2 pages 1. Blue/Orange 1. a. 0. a, b, c, e, h 44 1. a.
Company 22: 1. 2 pages 1. Blue/Orange 1. b. 0. a, b, c, e, h 11 1. a.
Company 23: 1. 2 pages 1. Blue/Orange 1. a. 0. a, b, c, e, h 20 1. a.
Company 24: 0. 2 pages 1. Grey/Yellow 1. b. 0. a, b, c, d, g, h 14 1. a.
Company 25: 0. 2 pages 1. Grey/Yellow 1. b. 0. a, b, c, d, g, h 14 1. a.
Company 26: 0. 2 pages 1. Grey/Yellow 1. b. 0. a, b, c, d, g, h 14 1. a.
Company 27: 1. 2 pages 1. Blue/Orange 1. b. 0. a, b, c, h 20 1. a.
Company 28: 1. 3 pages 0. - 1. a. 0. a, b, c, h 15 0. -
Company 29: 0. 3 pages 1. Yellow 1. a. 0. a, b, c, h 36 1. a.
Company 30: 1. 3 pages 1. Yellow 1. a. 0. a, b, c, h 29 1. a.
Company 31: 1. 1 page 1. Green 0. - 0. a, b, h 5 1. a.
Company 32: 0. 2 pages 0. Blue/Orange/Red 1. a. 0. a, b, c, d, h 8 1. a.
Company 33: 0. 3 pages 1. Red 0. a. 0. a, b, c, d 21 1. a.
Company 34: 1. 1 page 1. Pink 1. b. 0. a, b, e, h 9 1. c.
Company 35: 1. 2 pages 0. - 1. a. 0. a, b, c,, h 22 1. c.
Company 36: 1. 2 pages 1. Red 1. b. 0. a, b, c, h 5 1. a.
64
Company 37: 0. 2 pages 1. Yellow/Red 1. b. 0. a, b, c, d 31 1. a.
Company 38: 1. 3 pages 0. - 1. b. 0. a, b, c, d, h 33 1. c.
Company 39: 1. 4 pages 1. Pink/Green 1. b. 0. a, b, c, d, h 46 1. a.
Table 9.7 The e-mail frequency
Frequency:
Company 1: 3 per week
Company 2: 2 per week
Company 3: 2 per week
Company 4: 3 per week
Company 5: 7 per week
Company 6: 3 per week
Company 7: 3 per week
Company 8: 3 per week
Company 9: 3 per week
Company 10: 3 per week
Company 11: 7 per week
Company 12: 1 per week
Company 13: 2 per week
Company 14: 3 per week
Company 15: 4 per week
Company 16: 3 per week
Company 17: 2 per week
Company 18: 3 per week
Company 19: 3 per week
Company 20: 3 per week
Company 21: 3 per week
Company 22: 3 per week
Company 23: 3 per week
Company 24: 3 per week
Company 25: 3 per week
Company 26: 3 per week
Company 27: 1 per week
Company 28: 1 per week
Company 29: 1 per week
Company 30: 1 per week
Company 31: 3 per week
66
Company 32: 7 per week
Company 33: 3 per week
Company 34: 7 per week
Company 35: 7 per week
Company 36: 2 per week
Company 37: 2 per week
Company 38: 7 per week
Company 39: 7 per week
Table 9.8 Personalisation
Personalisation used: How is the newsletter personalised:
Company 1: 0. -
Company 2: 0. -
Company 3: 0. -
Company 4: 0. -
Company 5: 0. -
Company 6: 1. a.
Company 7: 0. -
Company 8: 1. a.
Company 9: 0. -
Company 10: 0. -
Company 11: 0. -
Company 12: 1. b.
Company 13: 0. -
Company 14: 0. -
Company 15: 1. a.
Company 16: 1. a.
Company 17: 1. a.
Company 18: 1. a.
Company 19: 0. -
Company 20: 1. a.
67
Company 21: 0. -
Company 22: 0. -
Company 23: 0. -
Company 24: 0. -
Company 25: 0. -
Company 26: 0. -
Company 27: 0. -
Company 28: 0. -
Company 29: 0. -
Company 30: 0. -
Company 31: 0. -
Company 32: 0. -
Company 33: 0. -
Company 34: 1. b.
Company 35: 0. -
Company 36: 0. -
Company 37: 0. -
Company 38: 0. -
Company 39: 0. -
Appendix 9.9 Benchmark open rate & click-through rate
Silverpop benchmark study: This study:
Open rate:
Average: 18,30% 18,02%
Median: 16,10% 19,45%
Click-through rate:
Average: 2,90% 4,25%
Median: 1,80% 4,40%
68
Appendix 9.10 Benchmark executional factors
Ellis-Chadwick & Doherty
(2012): This study:
Frequency &
Timing:
An average e-mail frequency
of 0,6 e-mails sent per week.
An average e-mail frequency
of 3,33 e-mails sent per week.
Email subject
line:
100% of marketing e-mails
use a subject line.
100% of marketing e-mails
use a subject line.
Email headline:
76% of marketing e-mails
have a distinct headline in
addition to the subject line.
64,10% have a distinct
headline in addition to the
subject line.
Length of the
e-mail:
The length of e-mails ranged
from 1 to 5 pages and the
average length was 2.4 pages.
The length ranged from 1 to 5
pages and the average e-mail
length was 2.05 pages.
Brand logo:
99% of marketing e-mails
have a brand logo prominent
in top left hand corner.
In 97,44% of the newsletters
the logo of the brand was
presented, 74,36% in the top
left corner.
Use of images:
Over 90% of marketing e-
mails use illustrations. These
vary from a full-page
illustration to many thumbnail
shots of products.
87,18% of the analysed
newsletters contained images.
Number of
hyperlinks:
99% of marketing e- mails
contain at least one hyperlink
to another web page. 65%
have more than 10 links.
100% of the e-mails
contained at least one
hyperlink. 66,66% of the e-
mails had more than 10
hyperlinks
Interactive
features:
While the e-mails analysed
contain some form of
interactivity, 26 different
types of interactive features
are apparent.
In every single newsletter
analysed at least one
interactive feature was
present.
Animation:
Only 2% of marketing e-mails
use animation.
In none of the analysed
newsletters animation was
used.
Personalisation:
Just over a third, 35 %, of
marketing e-mails are
personalized.
In 23,07% personalisation
was used.
69
Appendix 9.11 The Spss output
The e-mail subject line:
The subject matter (a) Discount 0=No 1=Yes:
Correlations
Discount or
saving Open rate
Discount or
saving
Pearson
Correlation 1 -.459**
Sig. (2-tailed) .003
N 39 39
Open rate Pearson
Correlation -.459** 1
Sig. (2-tailed) .003
N 39 39
**. Correlation is significant at the 0.01 level (2-tailed).
Correlations
Discount or
saving
Click-through
rate
Discount or
saving
Pearson
Correlation 1 -.203
Sig. (2-tailed) .214
N 39 39
Click-through
rate
Pearson
Correlation -.203 1
Sig. (2-tailed) .214
N 39 39
70
The subject matter (d) Occasional or Seasonal promotion 0=No 1=Yes:
Correlations
Promotion Open rate
Promotion Pearson
Correlation 1 .288
Sig. (2-tailed) .075
N 39 39
Open rate Pearson
Correlation .288 1
Sig. (2-tailed) .075
N 39 39
Correlations
Promotion
Click-through
rate
Promotion Pearson
Correlation 1 .362*
Sig. (2-tailed) .023
N 39 39
Click-through
rate
Pearson
Correlation .362* 1
Sig. (2-tailed) .023
N 39 39
*. Correlation is significant at the 0.05 level (2-tailed).
71
The subject matter (l) Bonus offer 0=No 1=Yes:
Correlations
Bonus offer Open rate
Bonus offer Pearson
Correlation 1 .350*
Sig. (2-tailed) .029
N 39 39
Open rate Pearson
Correlation .350* 1
Sig. (2-tailed) .029
N 39 39
*. Correlation is significant at the 0.05 level (2-tailed).
Correlations
Bonus offer
Click-through
rate
Bonus offer Pearson
Correlation 1 -.034
Sig. (2-tailed) .839
N 39 39
Click-through
rate
Pearson
Correlation -.034 1
Sig. (2-tailed) .839
N 39 39
72
The subject matter (c) Newsletter 0=No 1=Yes:
Correlations
Newsletter Open rate
Newsletter Pearson
Correlation 1 .030
Sig. (2-tailed) .857
N 39 39
Open rate Pearson
Correlation .030 1
Sig. (2-tailed) .857
N 39 39
Correlations
Newsletter
Click-through
rate
Newsletter Pearson
Correlation 1 -.112
Sig. (2-tailed) .497
N 39 39
Click-through
rate
Pearson
Correlation -.112 1
Sig. (2-tailed) .497
N 39 39
73
The creative design of the e-mail content:
E-mail headline:
Correlations
headline
Click-through
rate
E-mail headline Pearson
Correlation 1 .007
Sig. (2-tailed) .965
N 39 39
Click-through
rate
Pearson
Correlation .007 1
Sig. (2-tailed) .965
N 39 39
E-mail length:
Correlations
length
Click-through
rate
E-mail length Pearson
Correlation 1 .179
Sig. (2-tailed) .277
N 39 39
Click-through
rate
Pearson
Correlation .179 1
Sig. (2-tailed) .277
N 39 39
74
Use of colours:
Correlations
The use of
colours
Click-through
rate
The use of
colours
Pearson
Correlation 1 .093
Sig. (2-tailed) .573
N 39 39
Click-through
rate
Pearson
Correlation .093 1
Sig. (2-tailed) .573
N 39 39
Use of images:
Correlations
The use of
images
Click-through
rate
The use of
images
Pearson
Correlation 1 .219
Sig. (2-tailed) .180
N 39 39
Click-through
rate
Pearson
Correlation .219 1
Sig. (2-tailed) .180
N 39 39
75
Number of hyperlinks:
Correlations
The number
of hyperlinks
Click-through
rate
The number of
hyperlinks
Pearson
Correlation 1 .402*
Sig. (2-tailed) .011
N 39 39
Click-through
rate
Pearson
Correlation .402* 1
Sig. (2-tailed) .011
N 39 39
*. Correlation is significant at the 0.05 level (2-tailed).
Frequency:
Correlations
The e-mail
frequency Open rate
The e-mail
frequency
Pearson
Correlation 1 -.021
Sig. (2-tailed) .899
N 39 39
Open rate Pearson
Correlation -.021 1
Sig. (2-tailed) .899
N 39 39
76
Correlations
The e-mail
frequency
Click-through
rate
The e-mail
frequency
Pearson
Correlation 1 .176
Sig. (2-tailed) .283
N 39 39
Click-through
rate
Pearson
Correlation .176 1
Sig. (2-tailed) .283
N 39 39
Personalisation:
Correlations
Personalisation Open rate
Personalisation Pearson Correlation 1 .024
Sig. (2-tailed) .886
N 39 39
Open rate Pearson Correlation .024 1
Sig. (2-tailed) .886
N 39 39
77
Correlations
Personalisati
on
Click-through
rate
Personalisation Pearson
Correlation 1 -.333*
Sig. (2-tailed) .038
N 39 39
Click-through
rate
Pearson
Correlation -.333* 1
Sig. (2-tailed) .038
N 39 39
*. Correlation is significant at the 0.05 level (2-tailed).
Appendix 9.12 Example newsletter
Appendix 9.13 The companies in the sample (confidential)
Campaign: Company: Website: Industry: Country: Year founded:
Company 1: Chwilowo.pl Newtone s.c. https://chwilowo.pl/ Financial/online loans Poland 2011
Company 2: Clinic63(Discount) Clinic63 http://clinic63.nl/ Cosmetics The Netherlands 2012
Company 2: Clinic63(welcome)
Company 3: Czaszabawy GRÓL Edyta Sioch http://czaszabawy.pl/ Web shop Poland 2007
Company 4: Esold eSOLD Australia Pty Ltd http://www.esold.com.au Web shop Australia 2010
Company 5: Gloobovoip(5m) GlooboVoIP 10993 s.r.l. http://www.gloobovoip.com/ Travel Italy 2011
Company 5: Gloobovoip(El)
Company 5: Gloobovoip(Re)
Company 5: Gloobovoip(RI)
Company 5: Gloobovoip(wel)
Company 6: Groupdeal GroupDeal B.V. http://www.groupdeal.nl Daily Deal website The Netherlands 2010
Company 7: Massabotique Francesco Massa s.r.l. http://www.massaboutique.com Web shop Italy 2009
Company 8: Olive.pl
Piotr Grochowski Firma Handlowo
Usługowa VMP http://www.olive.pl/ Web shop Poland 2007
Company 9: Polskiepolisy Polskie Polisy sp. z o.o. http://www.polskiepolisy.pl/ Comparison website Poland 2014
Company 10: Pricewise Pricewise BV http://www.pricewise.nl Comparison website The Netherlands 2014
Company 11: Quiselle Quiselle Limpol https://sklep.quiselle.com/ Web shop Poland 2007
Company 12: Sexshop112 Sexshop112 http://sexshop112.pl/ Web shop Poland 2012
Company 13: Soofos 13 Soofos B.V. http://soofos.nl/ Tutoring The Netherlands 2015
Company 13: Soofos 5 Company 13: Soofos 8
Company 14: Ticketcrociere(11) Semplice Viaggi s.r.l. http://www.ticketcrociere.it/ Travel Italy 2008
Company 14: Ticketcrociere(7)
Company 14: Ticketcrociere(9) Company 15: Traveldeal(1) Traveldeal B.V. https://www.traveldeal.nl/ Travel The Netherlands 2015
Company 15: Traveldeal(2) Company 15: Traveldeal(3)
Company 16: Vakantiedeals Strategon BVBA http://vakantiedeals.be/ Travel Belgium 2010
Company 17: Volta Footwear Twentyfourseven S.r.l. http://www.voltafootwear.it/ Web shop Italy 2007
Company 18: Yellowoctopus(book) Activminds Pty Ltd https://www.yellowoctopus.com.au/ Web shop Australia 2007
Company 18: Yellowoctopus(mot)
Company 19: Njoydeals Aljora V.o.F. http://www.njoydeals.nl Daily Deal website The Netherlands 2012
Company 20: zadowolenie Alsen Marketing sp. z o.o. http://www.zadowolenie.pl Web shop Poland 2008
Company 21: menspace M4M M. Piętowski Sp. k. http://menspace.pl/ Web shop Poland 2012
Company 22: Dealdigger Buyou B.V. http://www.dealdigger.be Daily Deal website Belgium 2013
Company 23: Travelbird TravelBird Nederland B.V. http://travelbird.nl Travel The Netherlands 2010
Company 24: weflycheap WeFlyCheap https://www.weflycheap.nl/ Travel The Netherlands 2013
Company 25: Outspot Confinity bvba http://www.outspot.be Daily Deal website Belgium 2009
Company 26: Sixdeals 6Deals BV http://www.sixdeals.nl/ Daily Deal website The Netherlands 2014
Company 27: Voordeelvanger International Trade Concepts B.V http://www.voordeelvanger.nl Daily Deal website The Netherlands 2014
