choosing sides in social media

7/27/2019 Choosing Sides in Social Media

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CHOOSING SIDES IN SOCIAL MEDIA

Sales-related updates versus non-sales related updates by companies on social media,

and its influence on the customers willingness to participate

Ruud Peeters

ANR: 872915

Master Thesis

Communication and Information Sciences

Specialization: Business Communication and Digital Media

School of Humanities

Tilburg University, Tilburg

Supervisor: Dr. A. Alishahi

Co-supervisor: Dr. S. Milan

June, 2013


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Master Thesis | Communication & Information Sciences | Ruud Peeters2

Preface

In order to complete the master course Communication & Information Sciences, I was

expected to write a thesis about one of the topics that the school provided. My choice

involved the Dynamics Of Web 2.0 topic, which I narrowed down to content updates bycompanies on social media for this study.

I would like to thank everybody who participated in the online survey and had a share in the

successful completion of this thesis. Many thanks to Dr. A. Alishahi (supervisor), Dr. S.

Milan (co-supervisor) and Dr. M. Antheunis (for discussing the theoretical framework and

sharing her insight on the topic).

Furthermore, I would like to thank my family and friends for their support.

Tilburg, June 2013


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Abstract

This study builds on previous research of social media usage by youngsters. We researched

the influence of sales-related content updates (called SR) by companies on Facebook and

Twitter on the customers willingness to participate (called WTPar), versus the influence ofnon-sales-related content updates (called NSR). Furthermore, we looked at the differences

between hedonic products and utilitarian products in regard to the customers WTPar. The

study was conducted via an online questionnaire, where the participants were randomly

assigned to one of the four conditions of this study.

A 2x2x2 factorial experimental design was used to test the proposed hypotheses. For

Hypothesis 1, it was hypothesized that SR content updates by companies are less desired by

the customer, therefore lowering their WTPar. Even though the WTPar score in the SR

conditions was lower than the WTPar score in the NSR conditions, this difference was not

significant. Hypothesis 2 stated that content updates on Facebook versus content updates on

Twitter equally impact the customers WTPar. The results of the study showed that this was

indeed the case. Hypothesis 3, however, was rejected. It was predicted that content updates

containing hedonic products would result in a higher consumers WTPar compared to

utilitarian products. Results showed that this was not the case.

Two of the independent variables were between-subject: (1) the source of the content update

(Facebook/Twitter) and (2) the type of content update (SR/NSR). The third variable was

merged with the two independent variables, according to its within-subject design: hedonic

versus utilitarian products.

The participants indicated that they are willing to follow a company on social media and think

that it is helpful. However, when asked to respond or participate in a content update placed by

a company, the results were different: a low WTPar score throughout all the conditions.

Furthermore, participants indicated that after seeing an update they were (1) unlikely to

involve with the brand in the future and were (2) unlikely to purchase the displayed product.

These results were the same for all four conditions, showing a trend that was similar to the

low WTPar scores. Despite these low scores, participants of the questionnaire generally

displayed positive feelings about the brands and thought the products were of sufficient

quality, especially in the NSR conditions.


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Table of contents

1. Introduction 6

2. Theoretical Framework 8

2.1. The dynamics of Web 2.0 and social media 8

2.2. The changed interaction between companies and customers 9

2.3. Motivations for using the internet 11

2.4. Social media neutrality, sociality and privacy 12

2.5. The Honeycomb framework 13

2.6. The 4C Model of social media strategy 15

2.7. Willingness to participate (WTPar) 17

2.8. The hedonic versus utilitarian model 17

2.9. Facebook 17

2.10. Twitter 18

2.11. Research question and hypothesis 19

2.11.1. Introduction 19

2.11.2. Research question 20

2.11.3. Hypothesis 1 20

2.11.4. Hypothesis 2 21

2.11.5 Hypothesis 3 21

3. Method 22

3.1. Design 22

3.2. Stimuli 23


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3.3. Procedure 24

3.4. Target group 24

3.5. Participants 26

3.6. Measurements 27

4. Results 29

4.1. General attitude towards social media posts 29

4.2. Connection with the company 30

4.3. Product attitude 30

4.4. Hypothesis testing 31

5. Discussion 36

5.1. Limitations and future research 36

5.2. Implications and a look at the future of social media 37

6. Conclusion 39

7. References 41

8. Appendices 47

Appendix I. Online questionnaire 47

Appendix II. Graphics 89


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1. Introduction

We now live in a world where people have the opportunity to communicate, connect,

collaborate and express in a way that was deemed impossible in the 20 th century. There has

been a major shift in terms of using the internet as an individual; the internet user is now incontrol and is no longer dependant (Everson, Gundlach & Miller, 2013). According to

Forrester Research (Ghelfi, 2010), 71% of internet users below the age of 21 are creating

content for the Web (e.g. videos, blogs and websites). Almost three-quarters (70%) are users

of social networking sites. The majority of these users (61%) are active posters of comments

on published content. A survey by Bernoff (2010) showed that 60% of all adults (as a general

demographic) admitted that they maintain profiles on social media and visit these media on a

regular basis.

A core characteristic of this study is Web 2.0, which is the umbrella term for the

sharing, linking, collaborating and inclusion of user-generated content (Thackeray, Neiger &

Hanson, 2007). It means that users are in control of the content (OReilly, 2005); the term

originated in 2005, when the dot-com companies collapsed. Its predecessor Web 1.0

centralized one-way communication through static web pages. The users of these pages were

only able to absorb information. With the rise of Web 2.0, users became able to both produce

and share information (Everson et al., 2013). The ability to share is especially interesting

regarding content updates on social media (see section 2.2 for an extensive discussion).

For increased profits, customer satisfaction and brand loyalty, Palmatier, Dant, Grewal

and Evans (2006) stated that it is increasingly important to generate effective company-

customer relationships. Chen, Fay and Wang (2011) characterized Facebook and Twitter as

core venues for companies and brands. These two social media provide the possibility for

sales, online customer relationships and management for companies, and provide a platform

to publish personal evaluations of products, brands and services for the customer. Therefore,

Facebook and Twitter will be used in this study. Furthermore, research by Mollen and Wilson

(2010) showed that online interactions with a brand create greater cognitive processing,

heightened relevance and emotional experiences. The advertising effectiveness is therefore

greater (Calder, Malthouse & Schadel, 2009).

This study aims to answer the question what kind of content update yields the best

results for companies; sales-related content updates (called SR from here) are compared to

non-sales-related content updates (called NSR from here) via the two mediums Facebook and

Twitter. Content updates are defined as new posts on Facebook and Twitter that contain either


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SR or NSR related content, for example a discount (SR) or information about the product

(NSR). The content updates in this study are placed on the Facebook or Twitter pages of non-

existing brands, which were made up specifically for this study.

The structure of this study is as follows. First, we explore the underlying theories and models

(chapter 2) and formulate our research question and hypothesis. After that, we report on the

methodology (chapter 3). The results of the study are placed in chapter 4, and are discussed

and reflected upon in chapter 5. Finally, we draw a conclusion in chapter 6.


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2. Theoretical framework

2.1. The dynamics of Web 2.0 and social media

The line between entertainment and marketing communication on social media has become

thin during recent years (Grigorovici & Constantin, 2004). Social media generates millions of

dollars in revenue and advertising. However, little is known about why people join and

participate in these social media sites, which allow users to create their own space for creating

content (Gangadharbatla, 2008). Social media are online platforms and applications that offer

the possibility of interaction, collaboration and content sharing (Richter & Koch, 2007). These

media can be further divided in microblogging, podcasts, pictures, video, social bookmarking,

weblogs and social blogs (Kim, A.J. & Ko, E., 2012). Social media can create possibilities forcompanies who find themselves in the position to use advertising and marketing. Research by

Kim and Ko (2012) has shown that integrated online marketing is especially attractive

because of the low effort and cost compared to traditional marketing. A core characteristic of

social media is to what extent it enables companies and customers to connect, communicate

and engage. This concept of customer engagement was described by Brodie, Hollebeek, Juric

and Ilic (2011, p. 253) as creating an interactive experience and value co-creation within

marketing relationships.

The definition of marketing has changed over time, among other reasons by the rise of

Web 2.0 technology (Thackeray et al., 2007). Although many people still define marketing as

promotional tactics such as billboards and commercials, marketing is still a part of the

complete social media strategy (Thackeray et al., 2007; 2008). With the increase in

technology and online environments in Web 2.0, marketers have an increased potential of

reaching customers via their own online profiles. The customer value has become increasingly

important, and companies that represent themselves online have to factor in the value of these

customers and their online behavior (Kim & Ko, 2012).

To explore the (non-)sales nature of content updates, one first has to understand

marketing promotion. Kotler and Keller (2007) provided three purposes for marketing

promotion: it can be used (1) to increase the awareness of the product, (2) to persuade people

to buy the product and (3) to let the customer know that the product is still available.

Research by Belch and Belch (2007) has shown that marketers have been using Web

2.0 technologies to form an interactive marketing strategy and online promotion tactics. This

includes pop-ups and unders, banner advertising, paid search results and so forth. Rainie


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(2007) states that although Web 2.0 is becoming increasingly popular for the general

population younger people take particular interest in the possibilities of social media.

Besides the changes in the Web 2.0 environment, social media has also lead to a change in the

way companies and customers communicate and interact.

2.2. The changed interaction between companies and customers

Currently, social media sites are very diverse in terms of their function, scope and purpose

(Kietzman, Hermkens, McCarthy & Silvestre, 2011). Some networks are aimed at the general

masses, like Facebook. Other networks have a more professional nature, such as LinkedIn.

The sharing of videos and photos is provided by social networks such as Youtube and Flickr.

Because Web 2.0 is customer-driven and based, the (micro) blogging services such as Twitter

and Wordpress become more widespread as well. The customer is able to voice their public

opinion without restrictions here, and can offer real-time updates regarding the information

they encounter.

Research by Madway (2010) shows that a total of 145 million Twitter users send an

average of 90 million tweets per day. No exact numbers of the present (2013) are known, but

one can imagine the amount of Twitter users and tweets have only increased since 2010.

Because of these developments, the role of the customer is increasingly important for

companies that want to settle on social media (Kietzman et al., 2011). People talk about

companies online, whether they want it or not. Both participating in this conversation and

ignoring it could have a great impact on the brand. The business editor for the BBC, Tim

Weber, stated in 2010 that These days, one witty tweet, one clever blog post, one devastating

video - forwarded to hundreds of friends at the click of a mouse - can snowball and kill a

product or damage a companys share price.(Kietzman et al., 2011).

Besides involving the customer, social media is also a great tool for viral and buzz

marketing(Thackeray et al., 2008). This form of marketing encourages the customer to share

a message and pass along marketing information. When companies create content to publish

on their social media platforms, viral marketingcan be a powerful tool. Because of the speed

that users can share information within their network nowadays, a precise content update can

yield great marketing results (Thackeray et al., 2008). As the technology of Web 2.0 goes

through a continues change, companies need to be creative in their promotional efforts on

social media and devise a strategy which yields the best results regarding customer

satisfaction and theirwillingness to participate (see section 2.7 for more discussion).


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Customers want companies to listen to them, help them when they have issues and respond to

them (Kietzman et al., 2011). The experiences and preferences of the customer regarding a

brand are increasingly dependent on Web 2.0 dynamics like peer reviews, social networks,

blogs, tagging, online forums and referrals by friends (see Figure 1).

Figure 1. Factors influencing the decision-making process in an information-based

marketplace. Adapted from Kotler (2003) and Constantinides (2004); retrieved from

Constantinides & Fountain (2007).

Social media are especially suited to reach and engage young customers (Shankar, Inman,

Mantrala, Kelley & Rizley, 2011), or digital natives (Prensky, 2005; see section 3.4).

However, companies are still seeking the best way to use social media and are trying to

understand the extent to which Facebook and Twitter can play a role in involving the

customer (Parent, Plangger & Bal, 2011). Although research on this field is increasing, there

is still a continuous need for investigation of customer behavior in regard to social media and

online brand engagement, particularly among younger customers (Rohm, Milne & Kaltcheva,


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2012). Therefore, this research will be focused on digital natives. To find out how the target

group of this study uses the internet, we explore the motivations for internet usage in the next

section.

2.3. Motivations for using the internet

How is internet used, and what are the corresponding motivations? Together with Hotwired,

Wired Magazines internet website, and based on the association probes drawn from the

cognitive psychology literature (Szalay & Deese, 1978; Friedmann & Fox, 1989), Staffard,

Staffard and Schkade (2001) created a survey to discover the motivations for using the

internet, including questions such as Using single, easy-to-understand terms, what do you

use the Web for?. In total, 98 respondents answered the questions and filled in a total of 179

terms.The top 15 results of this survey can be seen in Table 1.

Table 1:Motivational inventory; Top 15 motivations of internet usage(Staffard et al., 2001)

Item Overall frequency

of response

Information

Email

Research

News

Software

Chatting

Entertainment

Communication

Fun

Access

Work

People

Web sites

Speed

Updates

114

49

45

41

31

24

24

23

20

17

15

13

12

12

12

Based on the information of Table 1, we can conclude people mainly use the internet for NSR

content, like News, Chatting and Entertainment. E-mail, Software, Information and Research


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can be allocated to both SR and NSR updates, as it depends on the context. Although this is

no hard evidence that SR updates have a lower impact on the customers WTPar compared to

NSR updates, it allows us to gain insight in the motivations of internet users. Before we

analyze the background of Facebook and Twitter, we first take look at the role of sociality,

neutrality and privacy regarding social media.

2.4. Social media neutrality, sociality and privacy

We know that social media sites are a part of Web 2.0. However, it is also important to note

that social media are not neutral, because the networks within social media function

differently. Companies like Facebook and Twitter provide people with new ways of

connecting, curating and consuming, but differ in doing so. The neutrality of these networks is

one of the most important debates of our time, because it deals with important issues like the

freedom to innovate, the freedom to listen, and the freedom to speak. Social media like

Facebook and Twitter have an extensive infrastructure, with a wide variety of applications

and content. In psychical networks, the values are gained in the psychical layer. However,

social media operates on our social layer, our connections with others. This allows companies

to accumulate value because we contribute in the form of our online presence. The value of

the network lies in its size. Therefore, the network becomes more attractive as it grows. Both

Twitter and Facebook have built an extensive network, and this monopoly becomes

increasingly larger as Facebook and Twitter become an ever larger part of our lives.

The three primary characteristics, or the main reasons for joining social media

networks, are: (1) identity, (2) relationship and (3) community (Leenes, 2010). Identity

involves playing a certain role on social media, information that is given (consciously) and

information that is given off (unconsciously). Maintaining and personalizing a Facebook or

Twitter profile is a part of this identity construction. The second characteristic, relationship,

allows users of Facebook and Twitter to attract and invite others to a persons network. They

can become a Friend on Facebook, or a Follower on Twitter. The third characteristic that

draws users to social media is community. This characteristic revolves around doing things

together as a community and sharing opinions, thoughts and ideas. Within these three

characteristics, sociality and privacy play an increasingly important role. Sociality on the one

hand means that a person chooses a rich social online life and takes privacy consequences for

granted. Privacy on the other hand raises a set of issues that most people would rather not

have (Leenes, 2010). The most important issue of privacy in social media seems to be theinvisibility of audiences. Many users put extensive personal data in their online profile, but do


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not limit others access to this information. This can lead to serious privacy risks (Leenes,

2010). Privacy and sociality are important terms regarding the usage of internet and the online

relation between companies and customers, especially since social media are rapidly growing.

Bigger social media networks are attractive for both potential users and advertisers and the

interaction between these two groups via online profiles.

2.5. The Honeycomb framework

Although many companies seem to acknowledge the possibilities of social media, not all of

them know how to devise a correct strategy, thereby often ignoring or wrongly treating

creative customers (Berthon, Pitt, McCarthy & Kates, 2007). Another problem regarding

companies on social media is that they often lack understanding of the term social media and

the various services it can provide (Kaplan & Haenlein, 2010). This study aims to clarify the

role of SR and NSR content updates by companies on Facebook and Twitter. To aid this

exploration, the Honeycomb framework and the 4 Cs Model by Kietzman et al. (2011) are

used. The Honeycomb framework is build around seven functional blocks of social media:

Identity, Conversations, Sharing, Presence, Relationships, Reputation and Groups. Kietzman

et al. (2011) state that these blocks do not have to be present in every medium, but instead

allow us to gain insight in the functionality and constructs of certain social media.

Table 2: Social media functionality (Kietzman et al., 2011).

Building block Definition

Identity The extent to which users reveal themselves.

Conversation The extent to which users communicate with each other.

Sharing The extent to which users exchange, distribute and receive content.

Presence The extent to which users know if others are available.

Relationships The extent to which users relate to each other.

Reputation The extent to which users know the social standing of others

Groups The extent to which users are ordered or form communities.

Table 2 explains the functionality of the social media blocks. In Figure 2, the implications of

these functionalities regarding a companys position on social media are displayed.


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Figure 2. Implications of the functionality (Kietzman et al., 2011)

In this research, Facebook and Twitter will be compared. An increasing number of companies

create Twitter accounts and have a fanpage on Facebook. This removes the restrictions of

time and place between the company and the customer and leads to an interactive two-way

and direct communication, compared to the Web 1.0 era, where one-way communication was

the leading way of communication (Kim & Ko, 2012).

To understand their functionality within social media, the Honeycomb model is

applied to Twitter and Facebook (see Figure 3). Jansen et al. (2009) analyzed a Twitter

database of 150000 tweets. A large percentage contained some feeling or expressions, both

positive and negative, towards a brand. When we look at Figure 3, we can see that Twitter

differs from Facebook in its essential honeycomb blocks (Kietzman et al., 2011). While

Facebook is mainly focused onRelationships, Twitter revolves aroundPresence. The darkest

sections are the most important for that particular medium. The partially colored sections are

second in importance. However, this does not mean that the white blocks are unimportant.


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Figure 3. The Honeycomb framework of Twitter and Facebook (Kietzman et al., 2011)

Although the Honeycomb model is a great way to explore the building blocks of social media,

it merely provides insight for companies and lacks a social media guideline. For their

research, Kietzman et al. (2011) also used the 4C model.

2.6. The 4C Model of social media strategy

The 4C Model provides a guideline for companies with regard to a social media strategy:

Cognize, Congruity, Curate and Chase. The 4C model explains how companies have to

monitor, understand and respond to social media activities.

Cognize

Cognize is derived from recognize. This first C states that companies should first understand

the social media landscape via the Honeycomb model, as it provides important information

for understanding the customer. In addition, companies should find out if conversations about

the company are being held, and if so, where. Not only should the company explore their own

landscape, but also that of their competitors, to determine how active they are and how their

social media strategy is shaped.


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Congruity

The second C, Congruity, is based on the harmony of social media activity. It states that

companies should devise a strategy that is similar to their goals and mission statement. By

applying the Honeycomb model, the company can focus the particular building blocks which

are most important (see Figure 2). In this phase, the company chooses which path to take. A

few possibilities of such strategies are to raise brand awareness, increase sales or to increase

brand loyalty. Another important factor of congruity is the realization that companies are not

in control of social media (Kietzman et al., 2011). Instead, it is the customer that voices their

opinion and beliefs, and it is up to the company to react and respond to these conversations. In

addition, the mix between social media and traditional media plays an important role. If the

total marketing strategy is not integrated, the audience is likely to get lost. The last important

factor of congruity is using the Honeycomb framework to gain trust of the key influencers of

a certain medium.

Curate

This C revolves around finding the right curator for the social media strategy, who devises a

strategy for the amount of content updates and decides the time at which they are posted.

Armano (2009) states that the company should identify employees that care about online

conversation and have the ability to listen. Furthermore, these employees have to be capable

of creating content updates that are emotionally appropriate for the community. Another

important aspect of Curate is the ability to create mash-ups. This is a mixture of media that

is already published online, such as content or research. The key goal of Curate is solving

customer issues and thereby developing a relationship that improves brand loyalty (Kietzman

et al., 2011).

Chase

The last C, Chase, is the most time-consuming one. It revolves around chasing information

for new content updates and adapting/updating the strategy for the (near) future. In this phase,

the company can analyze the results of the first 3 Cs, and reflect on these. This stage also

involves observing the developments of new social media, like the recently released Google+.

This phase has become more manageable since the release of Google Analytics, Google

Alerts, Tweetdeck and more. These applications allow the company to gain easy insight in

their social media data. Perhaps the most important factor of this phase is the speed ofreaction to negative company news, even as small as a tweet (Kietzman et al., 2011).


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2.7. Willingness to participate

The model of a customers willingness to participate (called WTPar from here) was created

by Parent et al. (2011). This new concept model is based on a previous strategy, called

willingness to pay, representing the premium price customers were willing to pay for goods or

services. This strategy revolved around the idea that customers felt there were no substitutes

available for a certain product. However, with the rise of Web 2.0 and social media, users of

social media have gained control over marketing efforts (Parent et al., 2011). Customers have

developed a new kind of brand loyalty and prefer personal conversations with companies over

faceless and impersonal marketing. This new affinity with brands has been assembled in the

term WTPar, the customers willingness to participate with the brand. The current study tests

the foundations of this model against the sales nature of content updates by companies. In

other words, what is the influence of (N)SR content updates on the customers WTPar?

2.8 The hedonic versus utilitarian model

For this study, we also chose to incorporate different product types in the content updates:

hedonic and utilitarian products (van Aart, 2011). Utilitarian brands are brands that are

characterized by a functional character. The products of this brand are useful and they solve a

problem, for example thirst (milk). However, hedonic brands/products have a more luxurious

character, for example milk with a tropical taste or chocolate mousse versus normal yoghurt

(Rossiter and Percy, 1997). Utilitarian brands provide certain needs for living, but the

customer has no fun in using the product, for example detergent. Hedonic brands can offer the

same products as utilitarian brands, but are more about luxury, image, lifestyle and bonding

with the brand. Because these brand categories differ from each other, customers could also

react differently to certain content updates. See section 2.11 (Hypothesis 3) for an extensive

discussion.

2.9. Facebook

Facebook opened its registration to organizations in April 2006. Within 2 weeks, more than

4000 organizations joined the network (Facebook, 2008). Facebook is a formatted Web page

where users can enter a lot of personal information, such as birthdays, hometown,

relationships, pictures and studies. Within this social network, users can send friend requests

to people, which allows them to enter their network. These relationships are called Friends,

and range from extremely close to simply being connected (Boyd, 2006). In addition to theirown profile, Facebook users have a Wall. IfFriends post something on Facebook, the


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message will appear on the Wall of their network (Walther, Van Der Heide, Kim, Westerman

& Stephanie Tong, 2008). Furthermore, users can Share posts done by others, orLike them,

both of which makes the message appear on the Wall of their network. For companies, this

means that the right content update can trigger a snowball effect, because the (potential)

customers are forwarding the marketing message via a Like or a Share.

Although research on the field of social networking is increasing, little is known about

how organizations use social media to establish relationships with customers and stakeholders

(Walthers et al., 2009). Up to 25% of all page views on the Internet are Facebook interactions

(Blodget, 2009). A recent publication by Facebookthe fourth quarter of 2012 taught us

that Facebook has 618 million daily users, that 587 Likes per second are distributed, and that

20% of all websites has integrated a Like-button on their homepage. People that Like websites

have 2.4 times as many friends on Facebook as people that dont (Facebook, 2013;

Dutchcowboys, 2013). The users and perceptions of Facebook have changed over time

(Lampe, Ellison & Steinfield, 2008). In 2006, Facebook users were mainly confirming offline

networks instead of actively broadening their online network. Since 2006, Facebook has

added and removed features that influenced the experience of the Facebook user, and

therefore potential customers for a company.

2.10. Twitter

Twitter is one of the microblogging services of social media. Users can post updates on their

profile regarding their hobbies, interests, findings, opinions and attitudes. These updates are

called Tweets, and contain a maximum of 140 characters. The Twitter medium can be reached

via the website itself, a mobile phone, e-mail or via instant messaging (Jansen, Zhang, Sobel,

& Chowdury, 2009).

A Twitter user can decide who to follow and only those updates will appear in their

timeline. All the data on Twitter is stored in an archive. This makes large scale analysis

possible. Twitter data is accessible for everybody with internet; it does not limit Tweets to

registered users. The main mechanism for information sharing via Twitter is retweeting,

which means forwarding the tweet written by another user (Suh, Hong, Pirolli & Chi, 2010).

Despite the high amount of shared information on Twitter, it is still unclear what sort of

information spreads more widely than others. Research by Suh et al. (2010) has shown that

URLs, #hashtags, the number of followers and followees, and the age of the account can

increase the chance of a retweet.


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Little research has been done on the area of Twitter use for marketing purposes. The

study done by Jansen et al. (2009) analyzed 150000 tweets for opinions, sentiments and

comments andas a resultshowed that people mainly use Twitter for providing or seeking

brand information. Furthermore, around 1/5 of the total tweets mentioned an organization or

brand (19%). Finally, 20% of the tweets contained an opinion about a brand, be it positive

(52%) or negative (33%). Research by Anderson (1998) showed similar results. Customers

that are very negative or very positive about a product are more likely to express their

opinions and feelings. Because of its large potential for (viral) marketing, Twitter has

attracted a lot of attention from companies, mainly due to its huge reach. A part of these

companies use Twitter for SR content updates (like the advertising of products), while other

companies mainly use Twitter for NSR content updates, like interaction and Custumer

Relationship Management (Asur & Huberman, 2010).

Both Facebook and Twitter offer a way for users to receive marketer communications

in their information stream. The task is for marketers to post content updates to which

customers can respond (Smith, Fischer & Yongjian, 2012). Facebook users can Like a brand

and Like or Share their content updates, while Twitter users canFollow their brand and

Retweet, Favorite or Reply to the content updates of the company. The study of Smith et

al. (2012) explained the importance of brand sentiment, which is a popular measure for

marketers to measure the success of their social media marketing. The sentiment that

customers have with a brand can either be positive, negative, neutral or unclear. Now that the

various models and the medium backgrounds have been discussed, we continue by stating our

research question and formulating our hypothesis.

2.11. Research question and hypothesis

2.11.1. Introduction

While there have been studies that examine various aspects of social media in general, none

have attempted to research the specific influence of SR content updates on the customer and

their WTPar, when compared to NSR content updates. Leading up to our research question,

we analyze the research done by Rohm, Milne and Kaltcheva (2012) and van Aart (2011).

Two schemes have been made in order to clarify the differences between SR content updates

and NSR content updates. The first scheme is an analysis of companies on social media in

seven categories: (1) Retailers, (2) Online services, (3) Media brands, (4) Luxury, (5) Fast-

moving customer goods brands, (6) Sports & lifestyle and (7) Restaurants. This categorization


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was made by Rohm et al., (2012). Another scheme used by Rohm et al. (2012) is used to

clarify SR content updates versus NSR content updates (see Table 3).

Table 3. Content categories

SR updates NSR updates

Product information

Incentives and promotions

Feelings of exclusivity

Branded content

Purchase-related interactions

Fun and entertainment

The extent of two-way interaction

Customer service

Privacy and trust

Fresh and timely information

It can be argued that all content updates by companies are SR. If not directly SR, the content

still contributes to brand engagement and loyalty, therefore possibly increasing sales later on.

However, the two terms do differ for this study. Companies that post SR updates use web

stores, hyperlinks, multimedia catalogues, discounts, offers, Share & Win posts, etcetera. In

short, the customer uses the content to make a (direct) purchase. NSR content updates are

mainly about establishing and strengthening brand identity and customer-company

relationship. NSR updates are meant to draw the customers attention to new products and

services, or to provide the customer with entertainment, fresh, timely content and trust.

2.11.2. Research question

The ability for companies to create content updates which can be Shared and Liked by

their customers thereby forwarding the marketing message to their own network is

increasingly important (Kietzman et al., 2011). The main research question of this study is

formulated as follows:

RQ: What is the influence of SR content updates by companies on Facebook and Twitter on

the customers WTPar, versus the influence of NSR content updates?

2.11.3. Hypothesis 1 (SR content updates versus NSR content updates)

Based on the survey by Staffard et al. (2001) which states that internet is mainly used for

Information, E-mail, Research, News and Software (see section 2.3)it is hypothesized that


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SR content updates by companies are less desired by the customer, therefore lowering their

WTPar. Hypothesis 1 is formulated as follows:

H1: SR content updates by companies will result in a lower WTPar in comparison to NSR

content updates.

2.11.4. Hypothesis 2 (Facebook versus Twitter)

Besides SR content updates versus NSR content updates, the two mediums Facebook and

Twitter are also compared. Based on the term brand sentiment, and according to Smith et al.

(2012), Twitter is associated with content that could typically be categorized as neutral

(information, parts of somebodys life), negative (complaints about a brand) and positive

(reviews and opinions about a brand). Facebook is a bit less neutral, although the two

mediums are not too different. Facebook is mainly driven by either positive or negative brand

perceptions and experiences, but also by neutral content like questions. Because the two

mediumsalthough being used in a different wayboth have positive, negative and neutral

content (Smith et al., 2012), it is hypothesized that the two social media Facebook and Twitter

equally impact the customers WTPar. Hypothesis 2 is formulated as follows:

H2: Content updates on Facebook versus content updates on Twitter equally impact the

customers WTPar.

2.11.5. Hypothesis 3 (hedonic products versus utilitarian products)

In section 2.8, we discussed the differences between hedonic and utilitarian products.

Because these brand categories differ from each other, one of the product types could result in

a higher WTPar than the other product type. It is hypothesized that hedonic products, because

of their relation to image and brand connection, will result in a higher customers WTPar

compared to utilitarian products. Hypothesis 3 is formulated as follows:

H3: Content updates containing hedonic products will result in a higher consumers WTPar

compared to utilitarian products.


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3. Method

The main goal of this study was to research what the influence of certain content updates by

companies on Facebookand Twitter is on the customers WTPar. The study further analyzed

other factors like product attitude after being exposed to a SR or NSR content update, or theparticipants general attitude towards social media posts. By researching this, we could gain

better understanding in the behavior of customers towards content updates on Facebook and

Twitter, and would be able to adapt a companys social media strategy according to these

findings.

3.1. Design

In this study, a 2x2x2 factorial experimental design was used to test the proposed hypotheses.

Two of the independent variables were between-subject experiment conditions: (1) the source

of the content update (Facebook/Twitter) and (2) the type of content update (SR/NSR). The

third condition was merged with the two independent variables, according to its within-

subject design: hedonic versus utilitarian products. We will further discuss these variables in

section 3.2: Stimuli. This study has a between-subject experimental design, meaning that

participants were exposed to one of the four versions of the survey (see Table 4).

Table 4. Online survey conditions

Condition Source of content update Type of content update

1 Facebook SR

2 Twitter SR

3 Facebook NSR

4 Twitter NSR

The online survey was centralized around content updates by companies. Nowadays, many

companies have their own Facebook page or a Twitter account. Therefore, this study is

focused on these two mediums only. For the purpose of this study, we chose three product

domains to focus on: (1) clothes, (2) household products and (3) food. Because we measure

the features of the content update material, and not the feeling towards the brand, we decided

to set up one non-existing brand per category; a brand that the participant can therefore not

know (see Table 5). By doing so, we avoid that the feelings and personal preferences of a


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participant towards a certain brand -for example Apple versus Windows- could lead to

different interpretations or wrong answers.

Table 5.Brands that placed content updates

Category Brand

Food After Dinner Desserts

Clothing Cambo Clothing

Household products Kitchen Kings

3.2. Stimuli

To simulate the natural environment of Facebook and Twitter, each of these brands were

assigned a separate and unique Facebook and Twitter page, specifically created for this study.

To avoid preferences towards a certain brand, no logos were made. Instead, the companies

had a profile picture that was the same throughout all of the conditions: a black background

with the name of the company written in white (font: Impact). The text of all content updates

were also the same. This way, we prevented or at least lowered- the influence of external

factors on the participant.

Figure 4. Logos/profile pictures of the non-existing brands

The placement of a content update would appear in the natural Timeline setting of a Facebook

or Twitter user. The images used in the survey were screenshots of the content update within

the timeline of the researcher, Ruud Peeters. The survey was centralized around three

variables: content type, medium and product type.


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Variable 1: content type

The first variable was content type, which consisted of SR updates and NSR updates.

Condition 1 and 2 were SR updates and condition 3 and 4 were NSR updates. The SR updates

consisted of online ordering/delivery, sale for one week and a webshop discount. The NSR

updates consisted of nutrition information, product tips and free repair service.

Variable 2: medium

The second variable was medium. Condition 1 and 3 were Facebook content updates and

condition 2 and 4 were Twitter content updates.

Variable 3: product type

The third variable was the product type. Within the different categories and brands, two types

of products were placed as a content update: hedonic and utilitarian products. For the food

category, this meant comparing chocolate mousse (hedonic) and normal yoghurt (utilitarian).

In the clothing category, designer beach bags (hedonic) were compared with hiking shoes

(utilitarian). Last, the household category compared a juicer (hedonic) with a cooking pan

(utilitarian).

3.3. Procedure

The survey was distributed between the 2nd of May and the 12th of May 2013, and was closed

on the 13th of May. There were two restrictions for people that wanted to participate: they had

to be between 20 and 34 years old (according to the digital natives target group), and had to

study Higher Education or University education, either in the present or having done so in the

past. There were no further restrictions.

Participants were mainly gathered on Facebook and Twitter (because of these

mediums mass potential), but also via e-mail, LinkedIn and personal Whatsapp requests. The

anonymous survey link that was generated by Qualtrics was pasted in these requests to

participate. On Facebook, the request was posted on my personal timeline. Furthermore, the

request was posted in the group for Masterstudents of Communication & Information

Sciences. On Twitter, I posted a tweet on my personal account, as well as requesting the TiU

Studystore account to retweet this message; a call for help that was answered. Besides the TiU

Studystore, several followers also retweetedthe following call for participants:


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Help mij met afstuderen! HBO/Uni student (of geweest)? En tussen de 20 en 34 jaar? Vul de

survey in! https://tucis.qualtrics.com/SE/?SID=SV_5gn7RZEO0TLBa8l || RT please! #UvT

#TiU

Four days after the initial launch of the survey (May 6th), a reminder was send to the same

channels as before. These reminders contained an anonymous survey link that was generated

by Qualtrics, the same link as before.This link automatically assigned the participants to one

of the four random conditions. The introduction, general questions and ending were the same

for all the participants. Via a Qualtrics account, that was obtained via a Tilburg University

license, the online questionnaire was developed and recorded. Since this was a Tilburg

University account, the style of the school was used as a layout. This was already available

within Qualtrics, so it was not necessary to personally design it. The complete survey can be

found in appendix I. It consisted of five blocks.

The first block was a short introduction to welcome the participant. After this part, the

participant was randomly (and evenly) distributed in one of the four conditions. This block

was the core of the survey. After this part, the participants answered questions about their

general attitude towards social media posts (block 3) and demographics (block 4). The last

block consisted of an ending, where the participant was thanked for their participation. Each

version of the questionnaire contained the same set of questions. The only difference between

the versions were the images of the updates (SR versus NSR updates and Facebook versus

Twitter) and the related questions (for example I would Retweet this post versus I would

Like this post). The general questions about social media attitude, demographics and the

statements about a certain update that was not medium-related, were the same throughout the

four conditions. In the introduction, the participant was welcomed, and was asked if they

owned a personal Facebook or Twitter account (depending on the condition). When

answering no, they skipped the usage questions and were placed at the first content update of

the corresponding condition. Lastly, participants were asked for their gender, age (20-34) and

education (Higher Education or University Education). After this, participants were thanked

for their participation. Several things were measured with this survey: the familiarity and

usage of the medium (block 1), the WTPar (block 2 and block 3), product attitude (block 2),

general attitude towards social media posts (block 3), connection with the companies (block

3) and demographics (block 4).


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3.4. Target group

The target group of this study were digital natives. This generation was born between 1980

and 1994 and been assigned the name The Net Generation (Tapscott, 1998) and digital

natives (Prensky, 2001). This group ranging from 20 to 34 years old- possesses familiarity

with and reliance on ICT. Digital natives are immersed in technology. As Prensky (2001a, p.

1) stated, they are surrounded by and using computers, videogames, digital music players,

video cams, cell phones, and all the other toys and tools of the digital age.

3.5. Participants

The questionnaire was available online from the 2nd

of May to the 12th

of May (2013). In

total, there were 285 participants that filled out the questionnaire. However, 132 participants

did not fully complete the questionnaire and were therefore excluded from the analysis. This

resulted in a total of 163 participants that fully completed the survey, 87 male (53.4%) and 76

female (46,6%). The age of the participants ranged from 20 to 34, with an average age of

23.67 (SD: 2.49). The majority of the participants have a University education (63.8%). This

means that they were currently studying at a university or have completed a university study

in the past (Bachelor or Master). The remaining 36.2% of the participants were currently

studying or have completed an HBO education.

The participants were randomly assigned to one of the four versions of the online

survey. This resulted in 45 participants for condition 1, 41 participants for condition 2, 40

participants for condition 3 and 37 participants for condition 4. The participants were asked

about social media-related subjects before seeing the content updates. For example, they were

asked if they had a Facebook and/or Twitter account, depending on the condition, and the

amount in which they use these accounts.

In both the Facebook and Twitter conditions, a high amount of people indicated that

they owned an account. In the Facebook conditions, a total of 83 out of 85 (97,7%) said to

own a personal account, and 94,7% indicated that they use this account on a daily basis. Also,

89,5% of the participants has liked a company or brand on Facebook. In the Twitter

conditions, the percentages are slightly lower: 58 of the 78 participants (74,4%) owned a

personal Twitter account. The usage of the accounts varies a lot, since the two highest

percentages are complete opposites: some participants indicated to use their account on a

daily basis (29,5%), while other participants use their account less than once a month

(20,5%). A small majority of the participants in the Twitter conditions follow a


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company/brand via Twitter (51,1%); this is notably different from the percentage in the

Facebook conditions (89,5%).

3.6. Measurements

WTPar

The perceived WTPar of the customer was measured by three items and a total of six images

per condition. Participants were asked to indicate their agreement, on a 6-point Likert scale,

with the following statements: I would Retweet this post, I would Reply to this post, and

I would Favorite this post for the Twitter conditions, and I would Like this post, I would

Comment on this post and I would Share this post for the Facebook conditions.

Product attitude

After being exposed to the image of the content update, and the WTPar related statements,

participants were asked to express their feelings towards the brand/product. The measurement

of product attitude was based on the marketing handbook by Bruner (2009) and on several

studies (Baker, Honea, & Russell, 2004; Tybout, Sternthal, Malaviya, Bakamitsos & Park,

2005): I have positive feelings towards [brand]. and [Brand] delivers products of low

quality.

General attitude towards social media posts

The general attitude towards social media posts was measured with four items: In general, I

ignore the posts by companies on social media, I do not mind seeing posts by companies on

my personal timeline., In general, I think following companies on social media is helpful.

and Whenever I decide to Follow or Like a company, I worry about spam -related

content. Participants were asked to indicate their agreement on a 6-point Likert scale.

Connection with companies on social media

The connection with companies on social media was measured with three items: In general, I

am willing to respond to a company's post on social media, In general, I am willing to

follow companies on social media and I usually take several factors into account before

Following or Liking a company. Participants were asked to indicate their agreement on a

6-point Likert scale.


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Purchase intention

The measurement of purchase intention the likelihood that a participant would buy the

product after seeing the content updatewas measured with one item: After seeing the post,

would you be likely or unlikely to purchase the product?. Answers were given on a 2-point

scale: likely or unlikely. Despite being incorporated in the survey, these stimuli served as a

distraction variable and were therefore not included in the analysis.

Brand involvement

The measurement of brand involvementthe likelihood that a participant would involve with

the brand in the future after seeing the content updatewas measured with one item: After

seeing the post, would you be likely or unlikely to involve with the brand in the future?.

Answers were given on a 2-point scale: likely or unlikely. Despite being incorporated in

the survey, these stimuli served as a distraction variable and were therefore not included in the

analysis.


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4. Results

In this chapter, the results of the data analysis are reported. First, we report on the general

attitude towards social media posts, connection with the companies and product attitude. After

this, we report on the customers WTParscores and test the hypotheses.

4.1 General attitude towards social media posts

The general attitude towards social media posts was measured by four items on a 6-point

scale. The higher the score, the more positive the participant was about the statement. Three

of these items showed a relatively low score compared to the median (3.5) and therefore

showed a negative trend; 74,2% of the participants indicated that they ignore the posts made

by companies on social media (M: 2.63, SD: 1.30), 69,3% worries about seeing posts bycompanies on their personal timeline (M: 2.86, SD: 1.30) and 71,2% worries about spam-

related content when Following or Liking a company (M: 2.83, SD: 1.38). The only

exception is the helpfulness of following companies on social media. The majority of the

participants (65.0%) agrees it is helpful to follow companies on social media (M: 3.72, SD:

1.21). A new variable was formed by joining the fourgeneral attitude items, which naturally

resulted in a negative trend overall (M: 3.01, SD: 0.91).

Figure 5.

2.632.86

3.72 3.82

In general, I ignore the

posts by companies on

social media

I do not mind seeing

posts by companies on

my personal timeline

In general, I think

following companies on

social media is helpful

Wheniver I decide to

'Follow' or 'Like' a

company, I worry about

spam-related content

General attitude towards social media posts

(6-point scale)

Mean


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4.2 Connection with the company

The participants connection with the company showed a similar negative trend. All three of

the measured items resulted in a score that was lower than the median of 3.5 on a 6-point

scale. The majority of the participants (84,7%) indicated that they are not willing to respond

to a companys post on social media (M: 2.26, SD: 1.16). Furthermore, 76,7% of the

participants take several factors into account before Following or Liking a company (M:

2.66, SD: 1.30). A slight majority of the participants (52,1%), however, indicated that they are

willing to follow companies on social media. This result is related to the positive score given

to the question of helpfulness in following companies on social media, which was asked in

the previous section. A new variable was formed by joining the three connection with the

company items, which lead to a negative trend overall (M: 2.76, SD: 0.82).

Figure 6.

4.3 Product attitude

The total score for product attitude on a 6-point Likert scale was surprisingly high (M:3.94,

SD:0.58), especially considering the low scores of WTPar, brand involvement, general

attitude and connection with the company. This means that the content updates in general did

not result in negative feelings towards a brand, and that the participants thought the company

delivered products of sufficient quality. This trend showed a higher (more positive) score in

the NSR conditions (M:4.07, SD:0.60) than in the SR conditions (M:3.82, SD:0.53).

2.26

3.36

2.66

In general, I am willing to

respond to a company's post on

social media

In general, I am willing to follow

companies on social media

I usually take several factors into

account before Following or

Liking a company

Connection with the company (6-point scale)

Mean


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Figure 7.

4.4 Hypothesis testing

4.4.1 Hypothesis 1

The first hypothesis proposes that the customers WTPar is lower in the SR conditions,

compared to the customers WTPar in the NSR conditions:

H1: SR content updates by companies will result in a lower WTPar in comparison to NSR

content updates.

To test whether SR content updates will result in a lower WTPar in comparison to NSR

content updates, we calculated the mean of the WTPar scores. The same was done for the

NSR conditions. An independent t-test was conducted to analyze whether the customers

WTPar was lower in the SR conditions. The assumptions of the independent t-test needed to

be checked. Levenes test indicated equal variances (p=.393), so degrees of freedom were not

adjusted. Based on the survey by Staffard (2001) which states that internet is mainly used

for Information, E-mail, Research, News and Software (see section 1.3)it was hypothesized

that SR content updates by companies were less desired by the customer, therefore lowering

their WTPar. Results showed that the mean WTPar of the SR conditions was 1.45 (SD:0.66),

and was indeed lower than the mean WTPar score of 1.58 (SD:0.68) in the NSR conditions.

However, this difference was not significant (t(161)=-1.25, p=.214). Therefore, it can be

3.81 3.83

4.114.06

3.94

Condition 1 Condition 2 Condition 3 Condition 4 Total

Product attitude (6-point scale)

Mean


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concluded that the WTPar of the SR conditions is not lower than the WTPar of the NSR

conditions.

Figure 8.

4.4.2 Hypothesis 2

The second hypothesis proposes that Facebook and Twitter equally impact the customers

WTPar. This was expected because the two mediumsalthough being used in a different way

both contain positive, negative and neutral content (Smith et al., 2012).

H2: Content updates on Facebook versus content updates on Twitter equally impact the

customers WTPar.

To test whether Facebook content updates will result in a equal WTPar in comparison to

Twitter content updates, we calculated the mean of the WTPar scores. The same was done for

the Twitter conditions. This lead to an overall WTPar score that was representative for the

medium. An independent t-test was conducted to analyze whether the customers WTPar was

equal in both mediums. Levenes test indicated equal variances (p=.249), so degrees of

freedom were not adjusted. Results showed that the mean WTPar of the Facebook conditions

was 1.55 (SD:0.71). Although this was higher than the mean WTPar score of 1.47 (SD:0.63)

1.45

1.58

SR updates NSR updates

Hypothesis 1: WTPar score of SRversus NSR updates (6-point scale)

Mean


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in the Twitter conditions, the difference was not significant (t(161)=0.73 p=.469). Therefore,

it can be concluded that Facebook and Twitter equally impact the customers WTPar.

Figure 9.

4.4.3. Hypothesis 3The third hypothesis based on the hedonic vs. utilitarian model by van Aart (2011)

proposes that hedonic products, because of their relation to image and brand connection, will

result in a higher customers WTPar compared to utilitarian products. Because these brand

categories differ from each other, customers also react differently to certain content updates.

Hypothesis 3 was formulated as follows:

H3: Content updates containing hedonic products will result in a higher consumers WTPar

compared to utilitarian products.

To test whether this is the case, we made pairs per condition, comparing the three utilitarian

updates with the three hedonic products via a paired samples t-test. The only significant

difference between these two categories can be found in condition one (t(44)=3.93, p


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Figure 10.

The only other condition that showed a trend was the Twitter/Sales condition (condition 3).

The hedonic updates resulted in a higher WTPar score (M:1.58, SD:0.79) than the WTPar

score of utilitarian updates (M:1.46, SD:0.73). However, this difference is not significant

(t(41)=1.53, p=.13).

Figure 11.

1.49

1.29

Facebook/Hedonic/Sales Facebook/Utilitarian/Sales

Condition 1: WTPar score of hedonic versus

utilitarian products (6-point scale)

Mean

1.58

1.47

Twitter/Hedonic/Sales Twitter/Utilitarian/Sales



Mean


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Because we had four conditions that compared hedonic and utilitarian content updates, and

only one of these conditions showed a significant difference, we can reject hypothesis 3:

content updates containing hedonic products will not result in a higher consumers WTPar

compared to utilitarian products. Below are the two conditions that did not show a significant

difference of trend when comparing WTPar scores.

Figure 12.

Figure 13.

1.68

1.69

Facebook/Hedonic/Non-Sales Facebook/Utilitarian/Non-Sales



Mean

1.38

1.45

Twitter/Hedonic/Non-Sales Twitter/Utilitarian/Non-Sales



Mean


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5. Discussion

The main aim of this study was to research the influence of SR content updates versus NSR

content updates by companies on Facebook and Twitter. Influence referred to the customers

willingness to participate, called WTPar in this study. This was measured on a 6-point scaleby summing the scores of several items, for example I would Retweet this post.

Furthermore, we measured product attitude, connection with the company and general attitude

towards social media posts. Brand involvement and purchase intention were also part of the

study, but the resulting scores were not used in the analysis. An online questionnaire was

conducted to gather the data and to answer the research question. In the following paragraphs,

the limitations, future research and implications will be discussed.

5.1. Limitations and future research

Although this study aimed to answer some important questions, there were also some

limitations. First, more participantseven though the number of participants was sufficient to

generalize the findings- would have been better. Also, all the participants lived in The

Netherlands. In future research, this study could be extended to other countries or continents

as well. Second, we used three product categories: food, clothing and household products.

Although the amount of different product categories was sufficient, only one brand per

category was tested (i.e. After Dinner Desserts, Cambo Clothing and Kitchen Kings). The

amount of (different) products for each brand, or the amount of brands per category, could

have been extended. It could be that posts about other products or brands have a different

impact on a customers WTPar.

Third, this study investigated single content updates (screenshots). This might be in

conflict with the natural environments of Facebook and Twitter, where updates are

surrounded by several other posts, information, images, commercials, advertisements and

more. Also, this study made up brands to avoid a certain sentiment of the participant. This

could be in conflict with the online environment of Facebook and Twitter. After all, people do

not Like or Follow companies that they do not care about, or are quick to undo so after a

few displeasing updates.

Fourth, this study was limited to Facebook and Twitter. Even though these are among

the most-used social mediums by both companies and customers, users are not limited to

them. Other large communities like Instagram, Pinterest, Google+ and Digg were not taken

into consideration. To gain further insight, this study could be tested in a more extended social


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media environment. Within Facebook and Twitter, the study could be extended by involving

existingbrands and gathering real data. For example, how many sales-related updates lead to

an actual increase in sales? This kind of data was not available in this study.

The products of the content updates could also influence the resulting scores when

looking at gender, age or education. We could have tried harder to pick gender-neutral

products, because, for example, males could be less interested in beach bags than women,

which would result in a lower WTPar score. However, this was not tested in this study and

could therefore be part of a research in the future.

In addition, this study had no pretests. Therefore, we do not know if the name of the

brands or the product category choices influenced the answers of the participants. It could be

that the brand After Dinner Desserts was more closely related to hedonic than utilitarian

products, which could influence the answers given in the survey. In future studies with a

larger timeframe, this could be tested before the survey.

Last, the measurement of WTPar was specifically designed for this study, and was not

entirely based on previous scientific research, because of lack thereof. The comparison

between Facebook WTPar (which consisted of Like, Share and Comment) and Twitter WTPar

(which consisted of Favorite, Retweet and Reply) was therefore not entirely justified. There

are no models available that express the values of each of these actions. For this study, the

three items of Facebook and the three items of Twitter were therefore equated in WTPar

value.

5.2. Implications and a look at the future of social media

Since social media plays such an important role in todays society, an increasing amount of

companies wonder what the best way of establishing in this ever-changing environment is.

Although many social media experts have their ideas on how to devise a correct social media

strategy regarding company updates, few of them have scientific proof to back up their

claims. They base their advice mainly on trial-and-error experiences and personal (non-

scientific) research. Customers are now in control, so it is important for companies to know

how they should interact with them. Since many companies now own a Twitter account

and/or a Facebook fanpage, new chances as well as new dangers arise. The chance to build

and maintain customer relationships and brand engagement in a way that was impossible 20

years ago, but also the danger of losing a customer because of all the wrong marketing

messages.An increasing amount of research on this field is being conducted, but social mediaare subject to change as well. It might be possible that Facebook, or even Twitter, will not


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exist in its current form in a few years from now. As technology advances, more and more

options become available. Think of the Google Glass for example: a pair of glasses combined

with a Smartphone.

Considering the growth of people that use Twitter and Facebook on a daily basis,

combined with the results of this study, we assume that the impact of these two mediums

keeps growing in the future. Because of these developments, it is increasingly important for

companies to monitor what people have to say about their brand. People talk about brands,

whether they want it or not. The type of content updates play a crucial part in this. A company

on social media can either be a one-way sales channel, or a two-way interaction medium

where the company can meet and talk to customers for a relatively low cost.

Based on the theoretical research, we advice companies to invest time and money in

their online environment and do not underestimate the impact of online content on the

customer. Based on the results of this study, we also advice companies to use social media for

a mixture of sales and non-sales content updates, since there is no scientific proof that one is

better than the other. It depends on the company if they should use Twitter or Facebook, but

having a professional environment on both mediums is generally better, since it could help in

forwarding a marketing message. Even though the results of this study show that participants

were not very willing to respond or react to a companys update on Facebook or Twitter, this

should not discourage companies to invest time and money in their social media environment.


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6. Conclusion

Social media like Facebook and Twitter become more apparent in todays networking society.

Therefore, this study sought evidence as to what kind of content update would be the most

rewarding in regard to the customers WTPar, because this would result in a better socialmedia (and) marketing strategy. The interest for conducting this study emerged because of the

practical implications and its importance for companies worldwide. Many people Follow

companies on Twitter or Like the company on Facebook, and are thereby confronted with

the updates of these companies on a daily basis. The goal of this study was to research if the

customer reacts differently to SR updates in relation to NSR updates (in terms of WTPar).

We first aimed at identifying the differences in WTPar scores between SR updates and

NSR updates. We did this by creating four conditions within the survey, two SR and two

NSR. The participant was randomly appointed to one of these conditions. Our research

question was as follows:

RQ: What is the influence of SR content updates by companies on Facebook and Twitter on

the customers WTPar, versus the influence of NSR content updates?

Even though the WTPar scores in the SR conditions were lower than the WTPar scores in the

NSR conditions, the difference was not significant. The results show a more negative trend

for SR conditions than for NSR conditions. It is important to state that the WTPar scores were

generally low throughout all the conditions. From these results, we can conclude that the

participants were not very willing to respond or react to a companys update on Facebook or

Twitter.

Second, we aimed at identifying the differences in WTPar between the two mediums,

Facebook and Twitter. The WTPar scores were low in both the Facebook and the Twitter

conditions, with no significant difference between the two mediums. Thirdly, we analyzed the

differences in WTPar scores between hedonic and utilitarian products. The results only

showed a significant difference in the Facebook/Sales condition, hedonic products resulted in

a higher WTPar score than utilitarian products. However, this was only the case in one of the

four conditions. The WTPar scores of the other three conditions didnt differ for hedonic and

utilitarian updates.

The general attitude towards social media posts and the customers connection with

the company also showed low results, with the exception of two statements. Findings show


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that participants are willing to follow companies on social media and think that following

companies on social media is helpful. Despite the low WTPar scores, the product attitude was

generally positive, and resulted in a more positive trend for the NSR conditions compared to

the SR conditions.

The findings of this study contribute to the research of social media marketing, and

show that SR updates show a more negative trend in WTPar than NSR updates. This study

also shows that people are generally positive about following a brand on social media,

because it can be helpful.


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Lampe, C., Ellison, N

choosing sides in social media

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