This dissertation examines the comparative effectiveness of social networking and traditional word-of-mouth (WOM) marketing in influencing consumer behavior and firm performance. It highlights the growth of online WOM and its potential advantages over traditional methods, emphasizing the reliability and credibility perceived by consumers. The research includes a literature review, methodology, and analysis, ultimately suggesting that the dynamics of WOM, especially in social networks, play a critical role in shaping marketing strategies.

1. 1
A
DISSERTATION REPORT
ON
“Are Social Networking more persuasive than
Traditional Word of Mouth”
Submitted by
KUMAR GAURAV
In partial fulfillment of the requirement for the degree of
Master of Business Administration
Submitted to
Dr. Anurag Singh
Assistant Professor
FMS-BHU
Faculty of Management Studies
Banaras Hindu University
Roll no Enrolment no Batch
12380MA025 351041 2012-2014

2. 2
DECLARATION
I hereby declare that this project work entitled “Are social networking more
persuasive than traditional word of mouth ” is my original work, carried out under
the guidance of my faculty guide Dr. Anurag Singh has not been submitted to any
other institute/ university or any organization apart from Faculty of Management
Studies Banaras Hindu University.
Kumar Gaurav
(Signature)

3. 3
ACKNOWLEDGEMENT
To acknowledge all the persons who had helped for the fulfillment of the project
is not possible for any researcher but in spite of all that, it becomes a foremost
responsibility of the researcher and also the part of research ethics to
acknowledge those who had played a great role for the completion of the
project.
So in the same sequence at very first, I would like to acknowledge my parents
because of whom I got the existence in the world for the inception and the
conception of this project. Later on I would like to confer the flower of
acknowledgement to Dr. Anurag Singh Sir and other faculty members who
taught me that how to do project through appropriate tools and techniques. And
would also like to thanks my friends who constantly supported me while working
on the project.
Rest all those people who helped me are not only matter of acknowledgement
but also authorized for sharing my success.
Kumar Gaurav
MBA(Marketing) 4th Sem
Roll No. 25

4. CERTIFICATE
, 670 1414
Are social networking more
This is to certify that the research report entitled “
persuasive than traditional word of mouth
supervision by Mr. Kumar Gaurav
2012-2014) of this faculty as a part of his Course Curriculum. This report is his
original work and up to the standard expected of an MBA student of this Faculty.
I recommend the Report be forwarded for evaluation.
mouth” has been prepared under my
a student of MBA (Marketing) IV Sem. (Batch
(Dr. Anurag Singh
Supervisor
Singh)
4

5. 5
CONTENT
 Introduction 5
Word of Mouth
Social Networking
 Literature Review 9
 Objective 18
 Hypothesis 18
 Research Methodology 19
 Data Analysis and Interpretation 20
 Conclusion and Findings 31
 Suggestion 33
 Learning 34
 Limitation 35
 References 36
 Questionnaire 37

6. 6
Introduction
The word of mouth (WOM) industry is experiencing massive growth—since 2004
the Word of Mouth Marketing Association (WOMMA) has grown from3 to 350
corporate members (WOMMA, 2007). This growth is particularly evident in online
and social networking media. Research estimates that while 90% of WOM
conversations take place offline (Keller Berry, 2006), just 15% of consumers
account for one third of WOM conversations in America, and those “Conversation
Catalysts” rely heavily on the Internet as a resource for the information they pass
along to their family and friends (Keller Fay, 2006) Word-of-mouth (WOM)
marketing has recently attracted a great deal of attention among practitioners.
For example, several books tout word-of-mouth as a viable alternative to
traditional marketing communication tools. One calls it “the world’s most
effective, yet least understood marketing strategy” (Misner 1999). Marketers are
particularly interested in better understanding word-of-mouth as traditional forms
of communication appear to be losing effectiveness (Forrester 2005). For
example, one survey showed consumer attitudes toward advertising plummeting
between September 2002 and June 2004. Forrester (2005) reported that 40%
fewer agree that ads are a good way to learn about new products, 59% fewer say
they buy products because of their ads, and49% fewer find ads entertaining.
WOM communication strategies are appealing because they combine the
prospect of overcoming consumer resistance with significantly lower costs and
fast delivery – especially through technology such as the Internet. Unfortunately,
empirical evidence is currently scant regarding the relative effectiveness of WOM
marketing in increasing firm performance over time. This raises the need to study
how firms can measure the effects of word-of-mouth communications and how
WOM compares to other forms of marketing communication. WOM marketing is
a particularly prominent feature on the Internet. The Internet provides numerous
venues for consumers to share their views, preferences, or experiences with
others as well as opportunities for firms to take advantage of WOM marketing. As
one commentator stated, “Instead of tossing away millions of dollars on Super
bowl ads, fledging dot-com companies are trying to catch attention through much
cheaper marketing strategies such as blogging and word-of-mouth campaigns”

7. (Whitman2006). As many of these companies have “grown up” and also begin to
spend significantly on traditional marketing (e.g., the Superbowl 3
One of the fastest growing arenas of the World Wide Web is the space o fso-called
7
social networking sites (e.g., Facebook, MySpace, Friendster, Xanga).
These sites rely up on user-generated content to attract and retain visitors,
obtaining revenue primarily from the sale of online display advertising. They also
accumulate user information that may be valuable for targeted marketing
purposes.
The social network setting offers an appealing context to study word-of-mouth.
The sites provide easy-to-use tools for current users to invite others to join the
network. The electronic recording of these outbound referrals opens a new
window into the effects of WOM, giving researchers an unobtrusive trace of this
often hard-to-study activity. When combined with data that also tracks new
member signups, it becomes possible to model the dynamic relationship between
this form of word-of-mouth and the addition of new members to the social
networking site. These members are, in a real sense, also the “customers” of the
social networking site, as their exposure to advertising while using the site
produces revenue for the firm.
Internet companies commonly employ several types of WOM marketing
activities. The major categories include the following:
1) Viral Marketing – creating entertaining or informative messages designed to
be passed on by each message receiver, analogous to the spread of an
epidemic, often electronically or by email.
2) Referral Programs– creating tools that enable satisfied customers to refer
their family and friends; and 4 Effects of Word-of-Mouth versus Traditional
Marketing
3) Community Marketing – forming or supporting niche communities that are
likely to share interests about a product or brand (such as user groups, fan clubs,
and discussion forums) and providing tools, content, and information to support
those communities.

8. In this project we tried to compare measure the effectiveness of recommendation
made through social networking and traditional WOM. Here social networking
involves the online forum, groups, blogs that contain positive or negative review
of the goods and services. And traditional WOM involves recommendation made
offline. Though traditional WOM is used widely by the consumer while marketing
through social networking is confined to the internet user . But recent research
shows that marketing through social networking is growing very fast.
8

9. Word of Mouth Communication
WOM is a consumer-dominated channel of marketing communication where the
sender is independent of the market. It is therefore perceived to be more reliable,
credible, and trustworthy by consumers compared to firm-initiated
communications.
(Schiffman & Kanuk,1995; Arndt, 1967).
Traditional communications theory considers WOM as having a powerful
influence on behavior, especially on consumers’ information search, evaluation,
and subsequent decision making.
(Cox,1963; Brown & Reingen, 1987; Money, Gilly, &Graham, 1998; G.
Silverman, 2001).
Social Networking
A social network is a group of individuals linked together by different social ties,
ranging from casual acquaintance to work relationships and family ties.
The social network is therefore meant to be a service whose primary
function is to allow or facilitate the organization and management of a map
of a social community.
Social networks are a means but not a medium in the sense of
"intermediary" (as in the mass media) but in the sense of a social tool, social
media.
9

10. Literature Review
In recent years, social networking sites and social media have increased in
popularity, at a global level. For instance, Facebook is said to have more than a
billion active users (as of 2012) since its beginning in 2004
(www.facebook.com). Social networking sites can be described as networks of
friends for social or professional interactions (Trusov, Bucklin, & Pauwels, 2009).
Indeed, online social networks have profoundly changed the propagation of
information by making it incredibly easy to share and digest information on the
internet (Akrimi & Khemakhem, 2012).
The unique aspects of social media and its immense popularity have
revolutionized marketing practices such as advertising and promotion (Hanna,
Rohm, & Crittenden, 2011). Social media has also influenced consumer
behavior from information acquisition to post-purchase behavior such as
dissatisfaction statements or behaviors (Mangold & Faulds, 2009) and patterns
of Internet usage (Ross et al., 2009; Laroche et al., 2012).
Social media is ‘‘a group of internet based applications that builds on the
ideological and technological foundations of Web 2.0, and it allows the creation
and exchange of user-generated content’’ (Kaplan & Haenlein, 2010, p.61).
Social media has many advantages as it helps connect businesses to
consumers, develop relationships and foster those relationships in a timely
manner and at a low cost as Kaplan and Haenlein discovered (2010).
Broadly speaking, word-of-mouth affects consumer behavior through two key
routes (Vanden Bulte and Wuyts 2009). The first is awareness. Word-of-mouth
can inform people that a product or behavior exists (and makeitmore accessible
or top-of-mind). This function is particularly important for new, unknown, or low-risk
products and ideas (Godes and Mayzlin 2009).
Research on the effects of word-of-mouth can be broadly divided into two
categories: quantitative research using field data and more behaviorally based
experimental laboratory research.
10

11. 11
Quantitative Research on Word-of-Mouth Effects
Across a variety of domains, quantitative research finds that word-of-mouth
has a causal impact on individual behavior (e.g., purchase or new
product adoption) and the firm more broadly (e.g., aggregate sales or financial
performance).1Word of mouth has been shown to boost sales of books
(Chevalier and Mayzlin 2006), bath and beauty products (Moe and Trusov
2011), and restaurants (Godes and Mayzlin 2009) and speed the adoption and
diffusion of new pharmaceutical drugs (Iyengar et al 2010).Other work suggests
that word-of-mouth may boost sales of music (Dhar and Chang 2009), movies
(Chintagunta, Gopinath, and Venkataraman 2010; Dellarocas, Zhang, and Awad
2007; Duan, Gu, and Whinston 2008; Liu 2006) and video games(Zhu and
Zhang 2010) and increase microfinance loans (Stephen and Galak 2012),
television show viewership (Godes and Mayzlin 2004), and sign-ups to a social
network website (Trusov, Bucklin, and Pauwels 2009). Some data even
suggests that negative word-of-mouth may hurt stock prices (Luo 2009) and
stock returns (Luo 2007). Most studies that have collected word-of-mouth
content have focused on online word-of-mouth, in part because it is easier to
acquire. Online word-of-mouth includes consumer reviews and blog posts, and
can be decomposed into volume, valence, and variance (Dellarocas and
Narayan 2006; Moe and Trusov 2011). Volume is the number of reviews or
posts that a given item receives, where more postings are usually associated
with increased sales. Valence is the average rating a product receives (e.g., 3.7
out of 5 stars, Dellarocas et al 2007),or the number of reviews of different types
(e.g., 37 1-star reviews, Chevalier and Mayzlin 2006), and more positive reviews
are generally associated with increased sales (though see Berger, Sorensen,
and Rasmussen 2010). Finally, variance is either the statistical variance
(Clemons, Gao, and Hitt 2006) or entropy (Godes and Mayzlin 2004) of the
reviews.
One interestingquestion for future research is when and why different
online word-of-mouth metrics have a stronger impact on (or are more predictive
of) behavior, sales, or other relevant outcomes. Different papers have found
different metrics to be more or less important. Some papers have found
significant effects on both the volume and valence of reviews (Chevalier and

12. Mayzlin 2006; Dellarocas, et al. 2007). Other papers have found either only
effects of review volume (Duan, et al. 2008; Liu 2006) or review valence
(Chintagunta et al. 2010), but not the other. While some of the difference may
be due to the specific modeling framework used, or dependent variable
examined, the distinction between awareness and persuasion may also be
important. Word-of-mouth may be valued or used differently depending the
novelty and risk involved with the thing being adopted (Godes and Mayzlin 2009;
Van den Bulte and Wuyts 2009). For products that are relatively high-risk, or
already quite well-known, the persuasive function of word-of-mouth should be
particularly important. Thus valence should matter: Positive word-of-mouth
should increase choice, while negative word-of-mouth may decrease it. For low-risk
12
or novel products, however, word-of-mouth should also impact behavior
through increasing awareness. Here, volume should matter more than valence,
and even negative word-of-mouth may boost trial (Berger et al. 2010).
Another rich area for behavioral research is the social dynamics of online
reviews. Online review systems are organized in such a way that consumers are
likely to see others’ reviews before they write their own. How does the volume
and valence of existing reviews impact whether (1) consumers write a review
and (2) the nature of the review they write? Consumers might be more (or less)
likely to post their opinion if there are few reviews about a product already, or if
their opinion differs from the prevailing view. Similarly, existing reviews might
generate either assimilation or contrast effects.Indeed, social dynamics may be
part of the reasons that the average product rating tends to decrease as more
ratings arrive (Godes and Silva 2012; Li and Hitt 2008). Consequently,
researchers have pointed out the importance of considering (and explicitly
modeling) how existing reviews impact the arrival of new reviews (Moe and
Trusov 2011; Moe and Schweidel 2012).
Defining the field-
Word of mouth (WOM) is informal advice passed between consumers. It is
usually interactive, swift, and lacking in commercial bias. WOM is a powerful in
Defining the field Word of mouth (WOM) is informal advice passed between
consumers. It is usually interactive, swift, and lacking in commercial bias. WOM
is a powerful influence on consumer behavior. Keaveney(1995)noted that 50%

13. of service provider replacements were found in this way. WOM may be positive
(PWOM), encouraging brand choice, or negative (NWOM), discouraging brand
choice.
Brand purchase probability will be affected by the relative incidence of PWOM
and NWOM about the brand and also by the relative impact of instances of
PWOM and NWOM. Here, we are concerned with the impact of PWOM
compared with NWOM. There is little evidence on this matter, which may relate
to the difficulty of making accurate measurements in this field. Below, we review
this measurement problem.
WOM can affect the adoption of new categories and the choice of brands in
mature categories. In product adoption research, interest falls on the few initial
users of products whose advice to non-users may decide the success or failure
of a new product. In mature categories, which are our research focus, changes
occur mainly as switching between brands and interest falls on users of the
category, who may be a majority of the population when categories such as cell
phones and restaurants are studied. Among users of mature categories, WOM
acts within a framework of acquired consumer beliefs, preferences, habits, and
commercial influences that may constrain or assist response to the advice.
Research on the role of WOM in brand switching is required for three reasons.
First, WOM is often the major reason for brand choice, but we do not yet
understand how PWOM and NWOM contribute to this influence. Second, some
groups are more responsive to WOM than others, and we show how segments
with different probabilities of purchase will respond differently to PWOM and
NWOM. Third, Reichheld's (2003)Net Promoter Score has performed poorly as
predictor of brand/company performance. Our work provides some explanation
for this failure, and our methods may be used to develop a better WOM metric.
Difficultly in studying word of mouth
13

14. Although consumers often attribute their brand choice to WOM, it is difficult to
observe cases where advice affects brand choice since WOM about a specific
category is relatively uncommon and any effect is often delayed. When evidence
is scarce, too much weight may be given to the limited research that is available.
One solitary field study by Arndt (1967)is often cited. Arndt found that NWOM
had twice as much impact on purchase as PWOM. However, he studied only
one brand, and systematic research should be based on all the brands in a
category and should include a range of categories. In addition,although the
category was familiar, Arndt used a new brand aboutwhich there could be few
established beliefs. Without direct evidenceof WOM effect, inferences have
been made from experimental workon the impact of positive and negative
information. It is well established that negative information usually has more
impact on judgment than positive information (Skowronski &Carlston,1989) but
this finding may not extend to the relative impact of PWOM and WOM on brand
choice in familiar categories .Although there is little evidence, it appears that
marketers believe that NWOM has more impact than PWOM. For example,
Assael (2004)states, “Negative word of mouth is more influential than positive
word of mouth” (though this claim may conflate relative incidence and relative
impact). Conventions in media publicity also support the idea that negative
information is more potent. According to the Krol off(1988)principle, negative
copy is four times as persuasive as positive copy.
When direct observation is not feasible, we have to gather evidence on the
relative impact of PWOM and NWOM using indirect methods. One method is to
measure Internet postings about brandsand their subsequent sales performance
(e.g., Godes & Mayzlin,2004). A problem with this method is that there may be
little correspondence between the content of consumer-generated media and
face-to-face advice. One is not necessarily typical of the other,and the large
amount of face-to-face advice is likely to be the dominant influence on
consumption. Keller and Fay (2006)found that 8% of advice was Web mediated,
70% was face-to-face, and 19%was by telephone. For this reason, we did not
14

15. specifically explore the effect of Internet advice, though growth of Internet use is
likely to make this an increasingly important form of WOM. A second method is
to use laboratory experiments to investigate the response to information on
familiar brands. Other techniques that may be used include role-play
experiments and surveys. These methods also present problems. Role-play may
not typify naturally occurring behavior, and the measures of PWOM and NWOM
in surveys may be subject to different degrees of bias that will distort the
estimation of their relative impact. Since no single method can provide
conclusive evidence, we adopt a three-pronged approach designed to build a
persuasive argument about the relative impact of PWOM and NWOM. First,
using both role-play experiments and surveys, we find that PWOM usually has
some what more effect than NWOM. This finding is similar to experimental
evidence that positive and negative information have much the same impact on
attitudes when the brands are familiar (Ahluwalia, Burnkrant, & Unnava, 2000;
Ahluwalia, 2002). Second, we describe how the pre-WOM probability of
purchase (here after referred to as PPP) and other variables contribute to the
impact of WOM. We show that this evidence suggests that PWOM and NWOM
are closely similar behaviors, making it less likely that measures of the two are
subject to strongly differential bias. Third, we explain why PWOM could have
more effect than NWOM if the pre-WOM probability of purchase (PPP) is less
than 0.5, and we find that this is so.
15

16. 16
Behavioral Research on Word-of-MouthEffects
Behavioral research on word-of-mouth has focused on when word-of-mouth
may have a larger impact on behavior and why.2
Most of this work has looked at whenand how word-of-mouth affects the
word-of-mouth recipient.3One important factor is characteristics of the word-of-mouth
source. People tend to listen to more to credible sources, or those that
are more trustworthy or have more expertise (Hovland and Weiss 1951; Petty
and Wegner 1998; Pornpitakpan 2004). Other important factors are the strength
of the tie (i.e., friends vs. acquaintances, or strong vs. weak ties) and their
similarity to the word-of-mouth recipient. Per dose or instance of word-of-mouth,
strong ties may be more impactful because people tend to trust them more and
think they know more about their tastes and interests (Bakshy, et al. 2012;
Brown and Reingen 1987). That said, people have more weak ties, or
acquaintances, so the overall impact of these types of individuals may be larger
(Bakshy, et al. 2012; see Brown and Reingen 1987; Granovetter 1973;
Goldenberg, Libai, and Muller 2001 for related discussions).4Similarly, word-of-mouth
from similar others may have a more positive effect (Brown and Reingen
1987; Forman, Ghose, and Wiesenfeld 2008; also see Naylor, Lamberton, and
Norton 2011) because people think their tastes are similar (Brock 1965). That
said, word-of-mouth from dissimilar others may have benefits because these
individuals have access to different information (Granovetter 1973) and may be
more familiar with alternative ways of thinking (Burt 2004).Consequently,
whether word-of-mouth from strong or weak ties and similar or dissimilar others
is more impactful may depend on the particular situation. Finally, heavy users
seems to have a larger impact on social contagion (Iyengar et al. 2011), but it is
unclear whether this is because they talk more frequently or because they have
higher status and are thus more likely to be listened to (Godes 2011).
Another important factor is the nature of the word-of-mouth itself. Word-of-mouth
varies in its valence: People can recommend a restaurant, say they hated
it, or merely mention that they went there. Recommendations likely have the

17. most positive impact on behavior, but even mentions should have a positive
effect if they increase product awareness or accessibility (see Lynch and Srull
1982; also see Berger, et al. 2010; Nedungadi 1990; Stigler 1961). In terms of
absolute impact, negative word-of-mouth may have a stronger impact than
positive word-of-mouth, in some cases(Basuroy, Chatterjee, and Ravid 2003;
Chevalier and Mayzlin 2006; see Chen and Lurie 2012 for a potential behavioral
explanation) and may be more impactful when the word-of-mouth event
happened further in the past (Smith and Schwarz 2012). Word-of-mouth also
varies in its intensity or depth: People can talk briefly about an experience or
they can go on at length.Longer or more in-depth word-of-mouth discussions
should have a stronger impact on behavior [though this may be mitigated for
online word-of-mouth, see Godes and Mayzlin (2004), as people may not end up
reading an entire post or review]. Along these lines, face-to-face word-of-mouth
may have a stronger impact than online or written word-of-mouth because it
tends to be more engaging and vivid (Herr, Kardes, and Kim 1991).5 Whether
the word-of-mouth is solicited also matters. Solicited advice seems to have a
more positive impact than unsolicited advice (East et al. 2005) and unsolicited
recommendations which go against an individual’s opinion may even lead to
reactance and strengthen the initial opinion (Fitzsimons and Lehmann 2004).
Finally, the level of certainty expressed along with an opinion can also have an
effect, with uncertainty actually being beneficial in some cases (Karmarkar and
Tormala 2010).
The susceptibility of the word-of-mouth recipient is also important (Watts
and Dodds 2007). Just like some people may be more susceptible to catching a
cold or a disease (e.g., because they have a weaker immune system), some
people may be more susceptible to, or prone to be affected by, social influence
(Aral and Walker 2012; Bearden, Netemeyer, and Tell 1989; Godes 2011).
More susceptible individuals, for example, should be more likely to adopt new
products or ideas if they hear about or see others using them. Though relatively
little research has examined this issue, some data suggests that young people
are more susceptible(Park and Lessig 1977; Pasupathi 1999) and people who
perceive themselves as opinion leaders are less susceptible (Iyengar et al.
2011).Beyond individual differences, situational factors should also shape
17

18. susceptibility. The closer people already are to taking some action, the more
likely it is that a dose of word-of-mouth will push them over the edge. People
who are searching online reviews, for example, are often close to being ready to
make a purchase, and thus may be particularly susceptible to influence.
18

19. Objective
The objective of the project is “To investigate and compare the
reliability of recommendation made through social
networking and word of mouth.
Hypothesis
H1- WOM and social networking influence the customer purchase decision.
H2- Social networking recommendation are more reliable than traditional WOM.
19

20. 20
Research Methodology
Research Design- Descriptive
Sampling Technique- Judgmental Sampling
Sample Size- 100
Area- Varanasi
Time Period- 1 month(March-14)
Data Collection Method- Personally Administered
Survey

21. Data Analysis and Interpretation
Table 1.Demographic profile of Respondent with mean score (N=100)
21
Age % Monthly Income % Edu. Qualification Gender
15-20 22 0-5 thousand 33 Secondary
Level
8 Male-
68
20-25 40 5-10 24 Undergraduate 14
25-30 20 10-20 18 Postgraduate 65
Above 30 18 20-30 15 Doctorate 13 Female -
Above 40 10 32
Table 1 depict the demographic information of the respondents which reveal that
22%of the population comes under the age group of 15-20 and majority falls
under the age group 20-25 i:e 40% .

22. 2. Are you aware of marketing made through social networki
networking and WOM
Response
Table 2 shows that 65% of the target population know about the
made through social networking and WOM
about it.
Some say that they heard about
they seen other using social networking
marketing
and 16% have a little information
social networking and WOM while a few said
networking.
Yes 65%
No 19%
A Little 16%
22
ng ?
%

23. 3. Do you believe recommendation made through Social Networking and WOM
are reliable?
40%
30%
20%
10%
The figure shows that 57% of the consumer believe on recommendation made
through social networking and traditional word of mouth website while 28% do
not believe on such recommendation because they believe they are intentionally
done by the marketers to promote positive word about their products. Whilst
15% neutral who do not have much idea about Social Networking and WOM.
23
0%
Response
Response

24. 24
4. Is your purchase decision is influenced by Social Networking or WOM?
30
25
20
15
10
0 5
Response
Response
54% of total targeted populations purchase decision is influenced by Social
Networking and traditional WOM. While 27% populations decision was not
changing by Social Marketing and WOM.

25. 5. Your purchase decision is more influenced by recommendation made through
social networking or WOM?
35%
30%
25%
20%
15%
10%
5%
28% of people are more influenced by social networking than WOM while 26%
by WOM compared to social networking. But majority of the people 32% said
that their purchase decision is equally influenced by Social Networking and
WOM.
25
0%
Response
Response

26. 6. . Will you pay extra for a product having positive WOM or social networking?
35
30
25
20
15
10
48% of the people will pay extra for the product having positive WOM or Social
Networking. While 20% stand neutral on this question and remaining disagree to
pay extra for such products.
26
0 5
Response
Response

27. Response
27
7. Do you think it is difficult for a company to spread positive WOM or Social
Networking?
35
30
25
20
15
10
0 5
Response
Majority of the 54% customer believe that spreading positive WOM and Social
Networking is difficult because there is less control of marketers on it. And 12%
are neutral on this. While 34% believe that company can easily do so by
manufacturing quality product which automatically generate positive WOM and
social networking.

28. Response
28
8. Do you think Social Networking or WOM provide enough information about
the product?
30
25
20
15
10
0 5
Response
43% of the targeted population believe that Social Networking and WOM provide
enough information about the product while almost same 40% of the people
believe that its not possible to provide full information about the product on
social networking and WOM. Thus in this case it is difficult to recognize whether
information provided on social networking and WOM is enough for a customer to
buy that product.

29. Response
29
9. Why do you think social networking and WOM is in headlines nowadays?
a. Increase consumerism 15%
b. Traditional Advertising is losing its effectiveness 33%
c. Company’s attempt to address society’s new way 12%
d. Increasing no. of internet users 28%
e. Other 12%
35%
30%
25%
20%
15%
10%
5%
0%
Response
Majority of the 33% population believe that Social networking and WOM are in
headline because traditional advertising losing its effectiveness and 28% of the
population believes that increasing no of internet user is also one of the reason
because of which social networking and WOM are in headline now a days.
Whilst other 12% believe that companies are doing so just to increase their profit
and market share.

30. 10. In your opinion is WOM or social network marketing is more effective than
traditional marketing ?
35
30
25
20
15
10
43% of the targeted population believes that social networking and WOM of
moth marketing is more effective than traditional advertising because they are
not control by marketers and are more reliable that those traditional advertising .
Whilst 30% still believes that traditional advertising is much more effective that
social networking and WOM is marketing.
30
0 5
Response
Response

31. 11. Do you think in near future WOM or social networking will be a necessary for
every company?
35
30
25
20
15
10
38% of the targeted population believes that social marketing and WOM will be
necessary for every company in near future because of its effectiveness and
also because of increasing no. of internet users. But there are 32% who still
believe that it is not necessary for company to have social networking marketing
and WOM.
31
0 5
Response
Response

32. 32
Conclusion and Findings
Consumers awareness towards Social Networking and traditional WOM is
high
Customer are having good knowledge of social networking and traditional WOM
Apart from this customer believes that social networking and WOM are more
effective that traditional form of advertising because marketers having less
control over it. And people are aware of social network marketing because
education level in the society increased by a good percentages. And the use of
the internet has also increases very fast due to which concept of e- marketing
and e shopping evolved and is growing very fast.
Social Network Marketing is more reliable that traditional WOM.
From the survey we found that majority of the 32% targeted population is equally
influenced by traditional WOM and social networking. But when we compared
which is more influential in consumer purchase decision social networking or
WOM then we found that social networking is more influential than traditional
WOM. Although difference between both was not very large, its of 2% but still
we can say that reliability of recommendation made though social networking is
high that traditional WOM.

33. Consumer purchase decision is influenced by social networking and WOM
As far as purchase decision is concerned customer purchase decision are
influenced by traditional WOM and social networking. 57% of the targeted
population accepted that their purchase decision is influenced by social
networking and WOM marketing. And majority of them are ready to pay extra for
a product having positive WOM or social networking. And they believe that this
mean provide enough information to buy the product and company should opt
this medium to target customer though it is difficult to have positive social
networking and WOM.
33

34. 34
Suggestion
 Companies should try to promote positive word about their products
through social networking and WOM because traditional advertising id
losing its effectiveness and due to increased consumerism.
 Companies should to use social networking efficiently to increase their
market share because it is not only cost effective but reliable too.
 Quality should be maintained because consumer believe that spreading
positive WOM and social networking is difficult because they are not
controlled by the marketers and its possible only when product quality is
good.

35. 35
Learning
 The project helped me think pro actively on a topic of interest.
 Talking to people and understanding their perception was an enriching
experience.
 The purchasing behaviors of Indian consumer align with their global counterparts
thus I have been able to map this phenomenon in global context.

36. 36
Limitations
 A convenience sample was used for the data collection which makes the result no readily
generalizable. Although great effort was put in to get a sample which include people from
different demographics.
 This study is only conducted in Varanasi region. So it is very difficult to determine whether it
can be extended to a larger population outside this region.
 This study is not product specific. This study is conducted only to understand the perception
of consumers about green product as a whole.
 Personal bias of the respondent while answering the question may have skewed the result
slightly. Although an effort has been made to verify the result through all sorts of possible
analysis applicable to this research.

37. 37
References
 Social-Media-Word-of-Mouth-White-Paper-Microsoft-Advertising-August-
2011 Driving Word-of-mouth with the MSN Audience.
 2013 social media marketing industry report.
 Dee T ALLSOP , BRYCE R. BASSETT 1993. " 2013 social media
marketing industry report.
 Derek Foster Shaun Lawson and Mark Doughty “Social networking sites
as platforms to persuade behavior change in domestic energy
consumption”
 Effects of Word-of-Mouth Versus Traditional Marketing: Findings from an
Internet Social Networking Site. Working Paper No. RHS-06-065
 Intern. J. of Research in Marketing 25 (2008) 215–224 “Measuring the
impact of positive and negative word of mouth on brand purchase
probability”

38. Questionnaire To investigate and compare the reliability of recommendation made
38
through WOM and social networking
1. Name …………………………….
2. Gender a. Male b. Female
3. Age
a. 15-20 b 20-25 c. 25-30 d. 30 &above
4. Education Qualification:
a. Secondary Level b. Undergraduate c. Postgraduate
e. Doctorate
5. Monthly Income (in thousands)
a. 0-5 b. 5-10 c. 10-20 d. 20-30 e. Above 40
6. Are you aware of marketing made through social networking and WOM?
a. Yes b. No c. A little
7. Do you believe recommendation made through Social Networking and WOM are reliable?
a. Strongly Agree
b. Agree
c. Neutral
d. Disagree
e. Strongly Disagree
8. Is your purchase decision is influenced by Social Networking or WOM?
a. Strongly Agree
b. Agree
c. Neutral
d. Disagree
e. Strongly Disagree

39. 39
9. Your purchase decision is more influenced by recommendation made through social
networking or WOM?
a.WOM b. Social Networking c. Both equally d. None
10. Will you pay extra for a product having positive WOM or social networking?
a. Strongly Agree
b. Agree
c. Neutral
d. Disagree
e. Strongly Disagree
11. Do you think it is difficult for a company to spread positive WOM or Social Networking?
a. Strongly Agree
b. Agree
c. Neutral
d. Disagree
e. Strongly Disagree
12. Do you think Social Networking or WOM provide enough information about the product?
a. Strongly Agree
b. Agree
c. Neutral
d. Disagree
e. Strongly Disagree
13. Why do you think social networking and WOM is in headlines nowadays?
a. Increase consumerism
b. Traditional Advertising is losing its effectiveness
c. Company’s attempt to address society’s new way
d. Increasing no. of internet users
e. Other

40. 40
14. In your opinion is WOM or social network marketing is more effective than traditional marketing?
a. Strongly Agree
b. Agree
c. Neutral
d. Disagree
e. Strongly Disagree
15.Do you think in near future WOM or social networking will be a necessary for every company?
a. Strongly Agree
b. Agree
c. Neutral
d. Disagree
e. Strongly Disagree