We live in a digital age when everyone has access to the internet, a medium that connects and informs everyone. Digital media, sometimes known as alternative media, is how the internet allows us to communicate, consume material, and obtain fashion inspiration from online influencers.

1. “The Impact
of Influencer
Marketing on
the viewing
choice of OTT
Platforms”
Presented by:
Amit Kumar Mandal
MBA-II Year
(Marketing)

2. Industry Profile
• We live in a digital age when everyone has access to the internet, a medium that connects and
informs everyone.
• Digital media, sometimes known as alternative media, is how the internet allows us to
communicate, consume material, and obtain fashion inspiration from online influencers. With
the rise of digital media, the notion of exhibiting movies, shows, and other content through the
internet arose.
• Additionally, the emergence of digital platforms allowed marketers to target specific audiences on
a variety of channels and mediums.
• OTT (Over the top) is a method of distributing media over the internet in the form of live
streaming video and audio. The distribution of movies and television shows via the internet,
without the need for a typical pay-tv subscription such as Comcast or Time Warner Cable, is
known as streaming.
• As a result of the internet era, mobile phones were employed for entertainment purposes, and OTT
was born. Platforms featuring various types of content, such as Netflix, Amazon Prime, Voot, and
Hot-star, have come to light.
• An OTT (over-the-top) service is a service that streams material directly to clients over the internet.
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3. Introduction to the Topic
Influencer
• Influencers are real people who are viewed as friends who audiences feel a connect with,
want to emulate and buy into in comparison to glamorous ads.
• An influencer must have the right kind and right amount of audience.
Influencer marketing
An influencer is someone who can influence others.
A social media influencer is someone who wields their influence through social media. When
you hire an influencer to promote your products or services, that’s influencer marketing.
OTT platform
OTT stands for “Over The Top” and refers to any streaming service that delivers content over the
internet. There's a wide range of OTT platforms, including Netflix, Disney+, Hulu, Amazon Prime
Video, Hulu, Peacock, Curiosity Stream & Pluto TV.
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4. Need for the Study
• Why this study was chosen in the first place?
• Because, Influencer marketing is estimated to be one of the fastest-growing and preferred online customer
acquisition channels, which would also outpace organic search and email marketing soon.
• It also opens up more organic means for audience engagement and brand awareness.
• To know about the business plan’s by influencers and how people influence by influencer marketing apart
from this, how is the relations between influencers and audience.
• What prompted you to study this topic?
• The word ‘Influencer Marketing’ has been causing a buzz in the world of digital marketing of lately and is
rapidly catching up with brands as well!
• A lot of western companies are leveraging this strategy of marketing and a lot of Indian companies are also
following suit, with having come up with a lot of successful influencer campaigns during the past 2-3 years.
• OTT platform having successful market in Indian in last 4-5 years. People have lots of options to decide for
best viewing experience.
• So, factor behind influence to people by influencers about choose OTT platform for better viewing experience
is suitable or not.
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5. Review of Literature
Author (Year) Key-Findings
Bressoud, E., & Lehu, J.
M. (2007).
In this study author explain about second life of product placement in movies that is
DVD.
De Gregorio, Federico &
Sung, Yongjun(2010)
In this particular paper author discussed the evolution of people's views and social
roles.
Patel, H., and
Chauhan(2016)
Author make the following claims: Product placement includes both the movie and
how the consumer influence by influencer when the consumers going to decide about
OTT platform.
Kakkar(2016) In this paper author explain how companies are sponsoring OTT platforms to reach a
younger demographic that may immediately connect to the product's quality
Katial(2019) Author claims that the rise of Over-The-Top platforms has had a profound impact. It's
changed the way we create, distribute, and consume media. Brunei's over-the-top
(OTT) media consumption began to alter dramatically
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6. Project Profile (Research Design)
• Statement of the Problem
The main objective of this study to know what is main factor behind to influence
people by Influencers to viewing choice of OTT. Now a days peoples are mostly
influenced by influencer on different social media platform.
• Objectives:
1. To determine the factors of influencer marketing impact of viewing OTT platform.
2. To analyze the impact of demographic on the perception of impact influencer marketing on the
viewing choice of OTT platform.
3. To identify the size of cluster which is highly influenced by influencer marketing on its viewing
choice of OTT platform.
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7. Project Profile (Research Design)
• Hypothesis
1. There is no signification of gender informing the perception of the respondents towards influencer
marketing.
2. There is no signification of age informing the perception of the respondents towards influencer
marketing.
3. There is no signification of Occupation informing the perception of the respondents towards
influencer marketing.
4. There is no signification of frequency of OTT informing the perception of the respondents
towards influencer marketing.
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8. Project Profile
• Type of Study: Descriptive
• Population: All the followers, who watch (Netflix, Amazon prime, Apple TV, ZEE 5, Hulu,
MX Player, Disney plus Hotstar, Voot, Sony Liv, Alt Balaji) of India.
• Sampling Unit: The whole research was done on the followers of all over India. The
individual followers of India are the sampling units. As the Google docs Questionnaire was
filled by employee of the IT sector, so they are the sampling unit. The whole research was done
on this unit and their feedback is taken and their viewpoints regarding the employee’s
perception towards employee performance has been taken.
• Sampling Technique: Non-Probability
• Sample Size: The sample size used for doing the research was 201. Questionnaire was given to 250
employees working in the IT sector. Out of 250 Questionnaire, only 201 have been answered in which
49 Questionnaire were not filled properly as some questions were unanswered. So finally, only 201
responses were obtained and on which the statistical tool has been applied.
• Data Collection Technique: Primary
• Limitations: Constraints included the time limit. Only a 201-sample size was used in this
investigation. Better results may be obtained if the sample size is increased.
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9. Respondents / Data Profile
In this study
If we talk about the demographic part of the study then in this study we took 201 respondents only, where as
47% are female,50.50% are male and 2.50% are not prefer say. (as soon in the above chart)
When come to age of respondents then we found 9.50% are under 18, 30.80% are comes under age range 18-
25, 37.80% are 26-35, 17.90% are 36-50 and 4% only are above 50 years.(as soon in the above chart)
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9.50%
30.80%
37.80%
17.90%
4%
0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
30.00%
35.00%
40.00%
under 18 18-25 26-35 36-50 above 50
Respondents Age Chart

10. Data Analysis
• Objective-1
• To determine the factors of influencer marketing impact of viewing OTT platform
• The first table in the KMO test and Bartlett’s Test. KMO tells the
sample sufficiency. This means whether the data collected while
comparing the number of changes is sufficient or not. There is a
sixth rule in this case to check that the data presented should be five
times the number of variables. For example there are 20 variants in
this data and the size of the respondent requires a minimum of 201 to
Indicate the suitability of the sample.
• The KMO value is 0.943 this is more than the required point of 0.6. Although testing can be
done with a low number and the results may also come but that will not be as accurate and
effective as it should be.
• Following is Bartlett's sphericity test, this examines the distribution of sample data. This value
in this test needs to be less than 0.05 and the value is less than the stated value.
• Tests show that the data is ready for use in EFA.
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Table 3.1 KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of
Sampling Adequacy.
.943
Bartlett's Test of
Sphericity
Approx. Chi-
Square
2569.6
21
Df 190
Sig. .000

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Table 3.4 Rotated Component Matrixa
Component
1 2
[Contest run by influencers is creating more & more interactive sessions to watch OTT Content] .742
[Casting of social media influencer in an OTT increasing more & more, this influences me to watch the content that have been
casted in.]
.739
[Trust on influencers that the information is provided influences the followers to watch the OTT Content] .736
[Short videos and reels are for the information about the upcoming events & movie trailer , web series] .735
[Review and comments of influencer are helpful for the followers in deciding what to watch on OTT Platforms] .722
[Merchandise related to the OTT Content with increase the foot fall on the online platform & reviews related to the brand that
is endorsed by the influencer]
.707
[Reaction videos by influencer can impact on followers to watch the OTT Content] .701
[Event promotion made by influencer for OTT content influences me to watch that OTT Content] .701
[Interviews of celebrities by influencers is creating major impact on the audience to watch OTT Content] .662
[Reviews of movies and web series made by influencers I follow influence me to watch the content] .640
[I find it useful that the influencer provide information by promoting OTT content and this helps me in deciding what to watch] .613
[If an influencer on social media has a personal experience or review, I am more likely to follow their advice] .611
[Influencers on social media who keep educating themselves by attending OTT-related viewing choices are the most credible &
trustworthy.]
.597
[OTT-related influencers on social media who themselves achieved a mass audience and comment, like for views are the most
authentic.]
.515
[The more followers an OTT related influencer on social media has, the more trustworthy I find him/her] .863
[If my favourite influencer recommends an OTT-related brand on social media, I am more likely to try it.] .815
[Reviews by influencers who have already tried out an OTT-related product are more trustworthy than reviewers provided by the
most famous personality.]
.722
[OTT-related influencers on social media have my best interest at heart.] .633
[If I found out that a OTT-related influencer had been paid for a post on social media, it would not negatively impact my perception
of their credibility.]
.585
[OTT-related influencers on social media will not purposefully endorse a brand that will harm me.] .514
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 3 iterations.

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Table 3.4 above shows the value of the Rotated Component Matrix. In this matrix it describes the family of
variables based on their relative value. The flexibility approach helps flexibility to build a building family. The
table shows a clear picture of what type of flexibility has gone and is based on the structure or output features
that have been named. The first factor has a variables, the second factor has 5 variables and all subsequent
ones have 2 variables in it. Based on the type of dynamics the structure is named and stored in the SPSS file as
follows:
Factors
1 - Influencer Credibility
2 - Trustworthiness and content quality
These are the two factors that represent the scale designed by the researcher. The research further progresses to
other objectives that require parametric and non-parametric testing based on these factors.

13. Data Analysis
• Objective-2
To analyze the impact of demographic on the perception of impact influencer marketing on the
viewing choice of OTT platform.
Table 1. shows the division of the sample total into five age groups.
• The first one is influencer credibility in this case first phase of the sample is below 18 and has 19 responders in its
category. The second phase is 18 - 25 and has 62 in that category and the third phase of the sample is 26-35 and has 76
responders and the fourth phase is 36-50 and has 36 and the last one in this phase is above 50 and has 8 responders in its
category making it a total of 201 respondents' data.
• The second one is trustworthiness and content quality in this case first phase of the sample is 18 below and has 19
responders in its category. The second phase is 18 - 25 and has 62 in that category and the third phase of the sample is 26-
35 and has 76 responders and the fourth phase is 36-50 and has 36 and the last one in this phase is above 50 and has 8
responders in its category making it a total of 201 respondents' data. Other descriptive factors are What You Say, General
Deviation, Error and confidence level for each category and theme. This helps to study the variation in the meaning of each
paragraph. And if it is a good study it shows how stable or unstable it is in the answer one part can be.
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Descriptives
N Mean Std. Deviation Std. Error
95% Confidence Interval for Mean
Minimum Maximum
Lower Bound Upper Bound
Influencer Credibility Below 18 19 .3967352 .74450425 .17080099 .0378957 .7555748 -1.89669 1.24544
18 - 25 62 -.1237815 .98825120 .12550803 -.3747503 .1271873 -3.33719 1.75243
26 - 35 76 -.1377476 1.12304484 .12882208 -.3943744 .1188791 -3.54943 2.02125
36 - 50 36 .2463414 .80691941 .13448657 -.0266808 .5193637 -2.37817 1.70511
Above 50 8 .2171263 .85540446 .30243115 -.4980097 .9322623 -1.48556 1.48673
Total 201 .0000000 1.00000000 .07053456 -.1390868 .1390868 -3.54943 2.02125
Trustworthiness and content
quality
Below 18 19 -.1984931 1.04075063 .23876457 -.7001188 .3031326 -2.77520 1.26566
18 - 25 62 .1874106 .92155604 .11703773 -.0466208 .4214420 -1.85058 1.71272
26 - 35 76 -.0556898 1.07147802 .12290696 -.3005330 .1891534 -2.50803 1.82705
36 - 50 36 -.1324587 .96843051 .16140509 -.4601284 .1952111 -2.44598 1.18289
Above 50 8 .1441058 .91091147 .32205584 -.6174352 .9056469 -1.49004 1.00053
Total 201 .0000000 1.00000000 .07053456 -.1390868 .1390868 -2.77520 1.82705
Table 1. One-way ANOVA based on Age

15. Data Analysis
• Objective-3
To identify the size of cluster which is highly influenced
by influencer marketing on its viewing choice of OTT
platform.
The table 3.21.2 depict that the size of the cluster has been
chosen to represent the desired outcome is 37. the total
niche segment targeted the influencer marketing are
highly worth.
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Table 3.21.2 Number of Cases in each Cluster
Cluster 1 164.000
2 37.000
Valid 201.000
Missing 1.000

16. Observations
• The results of t test applied on gender revealed that there
are no significance differences in Influencer Credibility and
Trustworthiness and content quality due to gender.
• As significance value is greater than 0.05. The test of one-
way anova for age showed that age doesn’t affect the
Influencer Credibility and Trustworthiness and content
quality.
• Similarly, for occupation and frequency of viewing the p >
0.05. Hence, respondent occupation and their frequency of
viewing doesn’t impact Influencer Credibility and
Trustworthiness & content quality.
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17. Observations
• With 201 responses, social media is the most popular channel for advertising
by Influencer towards OTT platform.
• In particular study we find 51% male respondents have influenced by
influencer about OTT platform This data disproves our study's initial
hypothesis, which claimed that no signification of gender information the
perception of the respondents towards influencer marketing.
• About 44% of consumers believe that product placement impacts their
purchasing choice. At the same time, 28% of those polled were undecided.
• According to the findings, 77% of individuals utilize OTT platforms, making
them a prime target for influencer marketing campaigns. 81.6 percent of the
102 respondents correctly identified the brands depicted in the photos.
• This proves that influencer marketing is an effective strategy for brand
memory, which influences and influences the purchasing choice at the time of
purchase.
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18. Conclusion
• Unambiguous Viewing choice is appropriate for OTT platforms, as many respondents accurately influenced
by influencers for the choice of OTT platforms to experience the movies and easily recall them.
• It will become increasingly important for followers to identify factors which influence to followers to
viewing OTT platform to effectively influence towards OTT grow saturated with rival brands.
• Product placement may also become a popular and successful method for creating and fostering high-quality
attitudes and awareness. Brands have several options to promote and be remembered thanks to the increasing
popularity of OTT (over-the-top) platforms, rapidly displacing traditional television and creating a new type
of medium.
• influencer marketing has become an integral aspect of the advertising industry in the following years and
decades.
• Influencer Credibility and Trustworthiness and content quality are not influenced by demographic
variables.
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19. Recommendations
• The researcher has pinpointed specific topics for additional study. The
following are examples of those areas: It's possible to conduct
research in more than three cities or focus on tier-wise study in
particular—one investigation at how an advertising agency sees
Influencer Marketing in secondary cities.
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20. Bibliography(in APA Format)
• Bressoud, E., & Lehu, J. M. (2007). The second life of product placement in movies: the DVD. In The EMAC
36th Conference, Reykjavik, 22-25 May.
• Bressoud, E., & Lehu, J. M. (2008). Product placement in movies: questioning the effectiveness according to the
spectator's viewing conditions.
• Chang, S., Newell, J., & Salmon, C. T. (2009). Product placement in entertainment media: Proposing business
process models. International Journal of Advertising, 28(5), 783-806.
• De Gregorio, F., & Sung, Y. (2010). Understanding attitudes toward and behaviors in response to product
placement. Journal of Advertising, 39(1), 83-96.
• Miles, P. (2009). Product Placement. The Impact of Placement Type and Repetition on Attitude. Journal of
Advertising, 4, 21-31.
• Kakkar, A., & Nayak, K. (2019). Analysis of Product Placement in Web Series and Its Influence on Consumer
Buying Behavior. Global Journal of Management And Business Research.
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