Consequences of Viral Marketing on Purchase Decision

Consequences of Viral Marketing on Purchase Decision

Mehwish Aqeel – 8403

[email protected]

Muhammad Mazher Uddin Akhter – 7164

[email protected]

Ayaz Ahmed Farooqi – 6097

[email protected]

mailto:[email protected]



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Management brief

The purpose of this paper is to predict the impact of the social networking site on purchase

decision. For the purpose of this study, primary data is gathered via online questionnaire of

both genders of sample size 80 within Karachi. The result shows insignificant impact of

online shopping in our culture. It is suggested that for further study other variables like

rebates, discounts and marketing communication should be analyzed for policy making.

Keywords: Viral marketing, Click to mortar, Homophile, Social media, Cost

1. http://en.wikipedia.org/wiki/History_of_the_Internet 2. http://en.wikipedia.org/wiki/Viral_marketing

3. http://en.wikipedia.org/wiki/Social_networking_service 4. http://en.wikipedia.org/wiki/Online_community

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1. PrologueIn the era of globalization and advance technology our methodology living has been changed.

We prefer to be fast and updated in every moment of our lives. Therefore when we say

something about fast or updated first thing which click our mind is “Internet”. This global

system of interconnected computer networks emerges in 19501 and change our lives.

Different organizations or more precisely different people who want an edge over others

make most of it in many areas especially in education and business.

Like other areas modern trade is also positively affected by this system, and this flourishing

evolved as with the concept of viral marketing. Viral marketing, as an approach to

advertisement, has been tied to the popularization of the notion that ideas spread like viruses.

The field that developed around this notion peaked in popularity in the 1990s.2 When we talk

about viral marketing the platform clicks in our mind is Social networks. A social networking

service is a platform to build social networks or social relations among people who, for

example, share interests, activities, backgrounds or real-life connections.3 This platform

works in a similar way as traditional get to gather works. People can share their views openly,

criticize or dramatize the scenarios. This online community allows them to interact with each

other and taking parts in each other’s rituals. An online community can take the form of an

information system where anyone can post content, such as a Bulletin board system or one

where only a restricted number of people can initiate posts, such as Weblogs.4

http://en.wikipedia.org/wiki/Social_networking_service

http://en.wikipedia.org/wiki/Viral_marketing

http://en.wikipedia.org/wiki/History_of_the_Internet

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This online community is very attractive forum for marketers as well. Here they initiate about

the existence of their product, advertise it and directly analyze the response the customer’s

about their offering. Marketers receive instant cash without concerning about the distance

same for the customer they screen out maximum possible alternatives in just a click.

Therefore in developed countries this platform is highly utilized in marketing activities.

Social sites provide convenience for both customers and marketers and saves different costs

associated with selling and purchases. Different researches take place to predict the effectives

of online marketing and customer’s positive response and concluded by providing significant

outcome of social media marketing in creating and maintain brand awareness and image, but

can this practice is as much fruitful in our Pakistani culture is also as much fruitful as

different countries? The aim of doing this project is to analyze the impact of social media in

of our purchase.

Therefore we are picking same genuine facts from past researches and applied in our

purchase process and then evaluate the results by checking its significances or insignificance

in our society any draft the related factors associated with it.

2. Literature Review

2.1. Theoretical background:At first, generally individuals go and simply shop and settle on the buying choice in the shop.

They are off and on again bound to settle on choices of obtaining choice inside the business

sector or at some point they want or look for mindfulness from recently presented item from

their surroundings or media.

In any case, the pattern is change now. Client settles on buy choice prior as well as gets

enough data of item through online CRM. This is extremely useful for exhortation looking

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for clients in light of the fact that at first they don't have this administration to get item data of

give immediate criticism to the organization. Likewise, from business perspective, brand

elevated because of vigorously speculation through the conventional print media (daily

papers, magazine and so forth) and electronic media (particularly TV). Preceding viral

promoting, it is excessive to advertise the advertising offerings.

We have a place with that pop culture where the effect of expressions of mouth

correspondence is high. From business perspective just those item's deal level are on its top

whose mindfulness level is high around clients. No questions items, administrations or

offering's focusing on and situating likewise matters a ton however in the event that we talk

Facebook ads so its focused to that potential clients who makes some move as far as

obtaining perspective or alluding their companions. With the assistance of this examination, I

can reason that how a viral promoting message creates the brand mindfulness. A while later

how companions impart their plans to their companions, then how they respond and take the

choice of acquiring those new items, which are new in our business sector.

In late 90s, we simply take after Indian society then we curved to western society however

now we likewise take enthusiasm toward some different societies also in term of style,

apparel and so on because of globalization. Web is the best wellspring of globalized business

and because of social networking website or society changed. Because of social networking

locales, we can without much of stretch mindful of nearby and in addition worldwide brands.

2.2. Empirical evidence:According to literature review, the researchers found:

Chuhay (2010) identify the impact of social networking and friends circle on online

purchases by using word of mouth, friendship preference and social networks as variables

and linear function has been applied. Result shows that increased homophile is beneficial for

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both consumers and marketer for sales especially. Therefore; it is suggested that the

prediction derived from the model compare with the observation from real market.

Iyengar, Han and Gupta (2009) identify the power of advertising in social media (Myspace

and Facebook) in purchase. Their research is based on secondary data of sample of 206, taken

from Cyworld a Korean social networking site and research model is based on two major

component of choice (buy-no buy) and quantity (how much money to spend) via Bayesian

approach and MCMC method. Result shows that there are three distinct groups of users with

very different behavior. Therefore it is suggested that for further investigation “product

diffusion” and “customer segmentation” must be taken into consideration.

Janssen and Noll (2005) identify the Internet Retailing as a Marketing Strategy by analyzing

bricks-and-mortar firms and click-to-mortar firm by using two-stage model liner function of

order condition. E-Commerce, Internet, multichannel competition, online uncertainty, online

shopping convenience as variables. Results show that online markets are less interactive but

online retail channel cannibalizes conventional market sales. Therefore it is suggested that for

better relationship in online transactions firms need to be more interactive with customers and

for brick to mortar firm they need to open their inline sites to maintain their position in the

market.

Kumar, Lang and Peng (2005) identify the search behavior of online shopper by using search

cost and convenience as dependent variable whereas product differentiation, price level, price

elasticity, and price dispersion as independent variable. They use cluster analysis and

Vivisimo to compute the research. Result shows that online market reduces different type of

cost associated with purchase. Therefore, it is suggested that he technology by itself does not

significantly reduce search cost, but that technology in combination with behavioral factors

does.

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Chen and Xie (2004) identify the elemental issue concerning online consumer review as a

new component of marketing mix by using probability function with respect to Lemma as a

coefficient and time. Availability of Consumer Reviews used as dependent variable whereas

as Time and Product category is used as independent variables. Result shows that with the

help of technology online seller not only make sales but also supplying information to

consumers by allowing them to post their product evaluations on the seller’s website or

licensing consumer review information. Therefore it is suggested that for further investigation

is required in this area for those product which are new in the market.

2.3. Research questions (via literature review):1. When an online seller should provide consumer reviews to its customers?

2. How a seller’s decision to supply consumer reviews interacts with its product

assortment strategy?

3. How the seller’s strategy regarding the supply of consumer reviews interacts with its

traditional marketing communication strategy?

4. What timing is best for the seller to offer consumer review information for a product?

5. Do friends influence purchases (frequency and/or amount) of a user in a social

network?

6. Which users are more influenced by this social pressure?

2.4. Variables:1. Homophile

2. Social media marketing (Click to mortar’ convenience)

3. Search cost

2.5. Definition of variables:

1. Homophile: Same choice and like hood just like your peers/friends

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2. Social media marketing (Click to mortar’ convenience): Virtual markets; you can do

shopping any time you want.

3. Search cost: Travelling expense, time cost, information seeking cost.

3. MethodologyFor conducting this research in our context (i.e. in Pakistan) we have prepared questionnaire

on likert scale and fill these questionnaire on social networking site i.e. facebook.

For analysis purpose we have run box plot for outlier removal then we check the reliability of

the data then we have run factor analysis then compute variables according to factors and

finally run regression analysis to develop model.

Social media = Cost + Homophile

4. Data evaluationThe outlier exist in forth question of our dependent variable which is further removed.

The factor analysis shows that the

model is significant to run factor and the fitness of factors are 61.4%

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KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .614

Bartlett's Test of

Sphericity

Approx. Chi-Square 217.416

df 105

Sig. .000

The reliability analysis shows that the overall data is reliable because the Cronbach alpha’s

value seems significant.

Reliability Statistics

Cronbach's Alpha N of Items

.668 15

5. Outcome of evaluationAfter removal of outlier, checking reliability and making factor we have run linear regression

in which Social media is taken as dependent variable whereas homophile and cost is taking as

independent variable.

Coefficientsa

Model Unstandardized

Coefficients

Standardize

d

Coefficients

t Sig. Collinearity

Statistics

B Std.

Error

Beta Toleranc

e

VIF

1 (Constant) 3.089 .407 7.585 .000

Homophil

e

.118 .122 .112 .964 .338 .991 1.009

Cost .162 .093 .200 1.728 .088 .991 1.009

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a. Dependent Variable: Socialmedia

The model is free from multi but all the variables are insignificant which means cannot be the

part of the model.

Social media = α (Where α = 3.089)

Social media = 3.089

6. Epilogue and policy implicationSocial networking showcasing has turned into a vital some piece of up to date culture. It is

the most advantageous course to arrive at. Customers are controlled by interpersonal group

that it will do something uncommon for them which will change their life. The principle

explanations behind preferring social networking was the data it gave in regards to the rebate,

exceptional endowments appended, brands and nature of the item.

The outcomes of the study uncovered that the online purchase trends is not applicable in our

culture. The research shows that although we are using social media but not prefer click to

mortar firm. It is suggested that for further study other variables like rebates, discounts and

marketing communication should be analyzed for policy making.

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7. References

Stojanova, D., Ceci, M., Appice, A., & Džeroski, S. (2012). Network regression with

predictive clustering trees. Data Mining and Knowledge Discovery, 25(2), 378-413.

Iyengar, R., Han, S., & Gupta, S. (2009). Do friends influence purchases in a social network.

Harvard Business School.

Chen, M. C. (2006). The competition and integration between virtual channel and brick-and-

mortar channel.

Kumar, N., Lang, K. R., & Peng, Q. (2005, January). Consumer search behavior in online

shopping environments. In System Sciences, 2005. HICSS'05. Proceedings of the 38th

Annual Hawaii International Conference on (pp. 175b-175b). IEEE.

Chen, Y., & Xie, J. (2008). Online consumer review: Word-of-mouth as a new element of

marketing communication mix. Management Science, 54(3), 477-491.

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8. Appendixes

8.1. Test results

8.1.1. Box plot: Dependent: social media

Explore

Case Processing Summary

Cases

Valid Missing Total

N Percent N Percent N Percent

Social_media_marketing_1 80 100.0% 0 .0% 80 100.0%





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8.1.2. Factor analysis (without removal of outliers)

Conclusion:

Outlier found in variable 4.

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Kaiser-Meyer-Olkin Measure of Sampling

Adequacy.

.625

Bartlett's Test of

Sphericity

Approx. Chi-Square 249.58

1

df 105

Sig. .000

Reporting:

KMO represent 62.5% fitness of factors

whereas sig. shows significant result.

Rotated Component Matrixa

Component

1 2 3

Homophile_1 .582

Homophile_2 .740

Homophile_3 .731

Homophile_4 .669

Homophile_5 .49

4

Social_media_marketing_1 .68

0


8

.637



2


7

Search_cost_1

Search_cost_2 .76

0

Search_cost_3 .388

Search_cost_4 .667

Search_cost_5 .645

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8.1.3. Factor analysis (after removal of outliers)


Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .614

Bartlett's Test of Sphericity Approx. Chi-Square 217.416

df 105

Sig. .000

Reporting:

KMO represent 61.4% fitness of factors

whereas sig. shows significant result.

Reporting:

Table show where to transform variable

into factors.

Rotated Component Matrixa

Component

1 2 3

Homophile_1 .622

Homophile_2 .690

Homophile_3 .716

Homophile_4 .655

Homophile_5 .542




Social_media_marketing_4 -.47

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Search_cost_1

Search_cost_2 .725

Search_cost_3

Search_cost_4 .678

Search_cost_5 .634

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8.1.4. Regression analysis

Variables Entered/Removedb

Model

Variables

Entered

Variables

Removed Method

1 Cost,

Homophile

. Enter

a. All requested variables entered.

b. Dependent Variable: Socialmedia

Model Summaryb

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .238a .057 .030 .64670

a. Predictors: (Constant), Cost, Homophile


Reporting:

Table show “Cost and Homophile” as independent variable whereas “Social media” as dependent variable.

Reporting:

Table show “Cost and Homophile” as independent variable whereas “Social media” as dependent variable.

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ANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression 1.783 2 .892 2.132 .126a

Residual 29.694 71 .418

Total 31.477 73

a. Predictors: (Constant), Cost, Homophile


Coefficientsa

Model

Unstandardized Coefficients

Standardized

Coefficients

t Sig.

Collinearity Statistics

B Std. Error Beta Tolerance VIF

1 (Constant) 3.089 .407 7.585 .000

Homophile .118 .122 .112 .964 .338 .991 1.009

Cost .162 .093 .200 1.728 .088 .991 1.009

a. Dependent Variable: Socialmedia

8.1.5. Reliability analysis

Reporting:

The sig value shows that the overall model is insignificant.

Reporting:

The Homophile and Cost both are insignificant element in social media marketing, also the model is free from

multicolinearity (VIF < 10)

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N %

Cases Valid 76 100.0

Excludeda 0 .0

Total 76 100.0

a. Listwise deletion based on all variables in the procedure.

Reliability Statistics

Cronbach's

Alpha

N of Items

.668 15

Item-Total Statistics

Scale Mean if

Item Deleted

Scale Variance

if Item Deleted

Corrected Item-

Total

Correlation

Cronbach's

Alpha if Item

Deleted

Homophile_1 51.2632 40.996 .167 .668

Homophile_2 50.9079 39.151 .364 .642

Homophile_3 50.0526 40.077 .295 .651

Homophile_4 50.4737 39.239 .406 .639

Homophile_5 50.6579 39.001 .285 .652

Social_media_marketing_1 51.0395 36.625 .365 .639





Search_cost_1 50.1711 43.237 .032 .682

Reporting:

Chronbach’s alpha value is > 0.5 therefore it is concluded

that the data is reliable.

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Search_cost_2 51.0132 39.320 .284 .652

Search_cost_3 51.0526 41.277 .109 .680

Search_cost_4 50.1579 40.321 .334 .648

Search_cost_5 50.2237 40.256 .298 .651

8.1.6. Reliability (prior to the removal of outlier)


N %

Cases Valid 80 100.0

Excludeda 0 .0

Total 80 100.0

a. Listwise deletion based on all variables in the

procedure.

Reporting:

Chronbach’s alpha value is > 0.5 therefore it is concluded

that the data is reliable.

Item-Total Statistics

Scale Mean if

Item Deleted

Scale Variance

if Item Deleted

Corrected Item-

Total

Correlation

Cronbach's

Alpha if Item

Deleted

Homophile_1 50.9750 44.582 .177 .697

Homophile_2 50.6000 43.585 .307 .681

Homophile_3 49.7750 44.050 .279 .684

Homophile_4 50.2125 42.752 .425 .669

Homophile_5 50.3750 42.845 .282 .684






Search_cost_1 49.9125 46.258 .092 .704

Search_cost_2 50.7875 41.967 .347 .675

Search_cost_3 50.7750 44.556 .144 .703

Search_cost_4 49.8750 44.339 .311 .682

Search_cost_5 49.9375 43.857 .307 .681

1 2 3 4 5

Strongly

Disagree

Disagree Undecided Agree Strongly

Agree

1 2 3 4 51 2 3 4 51 2 3 4 51 2 3 4 51 2 3 4 51 2 3 4 51 2 3 4 51 2 3 4 51 2 3 4 51 2 3 4 51 2 3 4 5

1 2 3 4 5

1 2 3 4 5

1 2 3 4 5

1 2 3 4 5

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Consequences of Viral Marketing on Purchase Decision