MBA project report by Amit

Dissertation Report On “The Impact of Influencer Marketing on the viewing choice of OTT Platforms” Submitted in Partial Fulfillment for the award of Degree of Master of Business Administration Scholar Supervisor Amit Kumar Mandal Dr. Rachin Suri (42010015) Assistant Professor Submitted to Department of Business Administration NIT, Kurukshetra May 2022 CERTIFICATE ii iii iv v Acknowledgement Any accomplishment requires the effort of many people and this work is no different. It has been my proud privileges to be attached to do research on such a topic which gave me the chance to get connected with some great people who are thoroughly professional and also great pleasure for me to acknowledge the kind of help, guidance, patience and immense knowledge received by me during my dissertation work. I was fortunate enough to get support from many people to whom I shall always remain grateful. I specially remember and extend my humble words of thanks to Dr. Rachin Suri, Assistant Professor, Department of Business Administration, and NIT Kurukshetra under whose supervision and guidance this report was completed. I am also very grateful to the management of my college where I have been studying for allowing me to do the course and dissertation. I am also thankful to my parents, classmates and friends who were in some way or the other helpful to me in successfully completing this dissertation report. I firmly believe that there is always scope for improvement; I welcome any suggestions for future enriching the quality of this dissertation report. vi DECLARATION vii Table of Contents CERTIFICATE ii Plagiarism report iii Acknowledgement iv DECLARATION v INTRODUCTION 1 INDUSTRY PROFILE 1 LITERATURE REVIEW 6 RESEARCH METHODOLOGY 10 Sample region 11 Type of study 11 Population 11 Sampling Procedure 11 Sampling Unit 12 Sample Size 12 DATA ANALYSIS INTERPRETATION 14 Table 3.1 KMO and Bartlett's Test 14 FINDINGS, DISCUSSIONS, AND RECOMMENDATIONS 49 References 52 APPENDIX: QUESTIONNAIRE 54 viii CH-1 INTRODUCTION INDUSTRY PROFILE Introduction 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. The digital era created a new platform for brands, social media, which was previously restricted to television, radio, and newspapers. As a result, they came up with the notion of incorporating their trademarks into movies to draw attention to their products. As a result, as films developed and joined the digital media landscape, so did the number of advertisements. It is common in the film industry for product marketers to pay movie producers for the placement of their brands in movies. Advertising in product placement (PPL) is intended to influence filmgoers inconspicuously. You do not have a one-time marketing campaign with in-film posts. Cinema, digital, satellite premieres, VOD (video on demand), pay per view, DTH, in-flight, and DVD releases are all contact points for a film. The producer doesn't go to the brand. The remote can't ruin a brand, and consumers can’t click ‘skip ad’ in an in-film ad. To promote films, brand placements help. For producers, the significant advantage is that these agreements are written such that the money from brand endorsements is not directly tied to movie marketing. It's not just about the money that goes into incorporating a brand into a film; the producer wants to market it through that brand around its release date. Therefore, producers permit businesses to use film clips in their marketing collateral and tactical efforts. Many companies also consider the impact on the product of the main characters. It is a win-win for the company when a celebrity endorses their product or service and does so without spending a fortune. 1 In addition, new films appear on the tiny screen more often than in the past. Producers have recognized this and are taking steps to correct it. The cost of acquiring a movie's title has risen due to the rapid availability of movies on portable devices. In Comparison to three or four years ago, WTP (World Television Premiere) sponsors are now forced to pay more than double the price. Because of the high expense of airing a commercial, in-movie integration is the most excellent option. Those with expertise in the related fields of advertising, marketing, and communication have made an effort to ascertain how the public feels about this tactic. Influencer Marketing When a specific brand or product is mentioned in another work, such as a film or television program, to promote it, it is known as influencer marketing. Product placement is another term for influencer marketing. Product placements are implemented, mentioned, or discussed throughout the show to foster positive associations between viewers and the advertised brand. While it is widely accepted that product placement began to enhance the authenticity of movie scenes, in the modern era, it has evolved into a successful marketing strategy (Morton & Friedman, 2002). Traditional advertising has become less effective over time, and marketers are turning to this popular strategy in its place. Thanks to this tool, they have been able to break through the clutter and decline in advertising ratings (Gupta & Lord, 1998). In-film branding is a method of promoting commercial products in films. Adverts have taken advantage of this medium because of the film's entertainment value, emotional quotient, and psychological impact on viewers. Brands and audiences alike have been able to stand out on a much larger stage because of this new advertising medium. In the film industry, product placement is a common practice. Product placement impacts brand equity as a marketing tool because it raises consumer awareness of a company's unique values and, as a result, its public image. (Lehu, 2006). Compared to the exorbitant endorsement fees paid by today’s leading actors, partnering with films starring them seems like a more affordable option. This industry has attracted a large number of experienced managers. A brand provides the producer with a certain amount of media space in exchange for film placement. Several in-film stations occur throughout the media trade process. Co-branded 2 content is used in the brand's advertisements instead of the usual campaign. The value of in-film branding Extends beyond just the brand's on-screen appearance. It extends to the promotion of films as well. Brands that already have a solid connection to popular culture can Benefit from in-film advertising. With in-film branding, you will be there for the rest of your life. Because the film continues to exist, the impact will endure in perpetuity. It can be viewed again and again on satellite channels is a huge advantage. It is even better when done through a song because people hear the music far more often than they see the movie. To quote Wenner (in 2004): Movie studios and television networks used product placement to cut production costs using rented props (Newell et al. 2006). This fundamental premise holds even as the cost of making and marketing films and television content rises. Thanks to new technology and creative marketing strategies, even more products have been incorporated into popular movies and television shows. It is (Wenner, 2004). The use of product placement in films dates back almost as far as the history of cinema (Turner, 2003; Newell and Salmon, 2004). A product or brand is advertised by including it in a film scene where it can be seen or heard. The advertiser pays, or products and/or services like logistics facilities are swapped during placement (Karrh, 1998). OTT platforms 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 Hotstar, have come to light. At-home binge-watching is becoming increasingly popular, making it more difficult to create a realistic viewing experience in the lab. It raises ethical and attentional difficulties when participants must remain focused on a stimulus for as long as binge-watching does (Babin & Carder,1996). An OTT (over-the-top) service is a service that streams material directly to clients over the internet. Over the top media services offer streaming media as a standalone product. Video-on-demand 3 platforms, audio streaming, messaging services, and internet-based phone calling options are all examples of this term’s application. While OTT services avoid conventional media distribution routes such as telecoms networks and cable television providers, you can access all of the services if you have Access to a local or mobile internet connection. Although most over-the-top (OTT) services need a monthly membership fee, others do not. Why use Ott? A low-cost alternative to typical cable bundles, streaming services provide highquality material at a low price. Even if you just want to consume a portion of Netflix’s material, the HD membership costs 499/month, and Netflix's mobile plan costs 199/month. Over-the-top (OTT) providers such as Netflix and Amazon Prime have recently started generating original material that is only available through their service. Platforms such as HBO Go and Disney+, which have exclusive streaming licenses for previously aired material, are doing well. For many years, cable television viewing required a television set. OTT material may currently be seen on a broad range of devices. Every account holder will get the same OTT experience regardless of the device they use. How is OTT content delivered? Traditional third-party networks are no longer controlling online content on OTT platforms. Customers simply need an internet connection and a suitable hardware device to use the service. A compatible digital storefront is required to download OTT applications for mobile devices. The vast majority of personal PCs can screen OTT video via desktop programs or web browsers. With today's most up-to-date intelligent TVs, OTT applications are either pre-installed or may be downloaded by the user. Third-party devices like the Apple TV allow for a wide range of OTT explanations to be supported. OTT applications may be downloaded and run on many modern video gaming consoles. Aside from video-on-demand, OTT technology encompasses a broad spectrum of web-based content, such as podcasts and blogs. An OTT media service’s most well-known format is streaming video. Subscription-based services 4 like Netflix and iTunes and ad-supported ones like YouTube are all examples of popular platforms. OTT services make it possible to stream audio. Internet radio stations and podcasts are generally accepted as examples of this. Mobile SMS networks are bypassed by OTT-based instant messaging services, which link users directly over the internet. It is not only Facebook, Google, and Skype that offer these services. In most cases, smartphone text messaging functionality may be replaced or integrated. OTT Services include voice-over-the-internet platforms like Skype and others that use internet protocols to carry voice calls. Certain features of these services can be improved by combining them with mobile phone networks. Brands on OTT platforms OTT is presently the fastest-growing advertising platform, rapidly displacing traditional media such as television and radio. When it comes to advertising and maintaining a solid brand image, companies usually follow the latest trends. If you're looking for a way to get your product or brand out in front of people, OTT is a great way. Because the film's producer had parallel commercial arrangements with both the Lumières and Lever Bros., the presence of a branded product was not a coincidence. Thomas Edison's amusement films, which featured images in which he employed his items from his factory, were the first to introduce the concept of interweaving entertaining with educational themes (Newell et al. 2006). The value of product placements in movies and television has increased at an estimated compound rate of 30 percent since 1999, accounting for more than $3 billion in spending and trade transactions (Kivijarv 2006). As a result, little attention has been devoted to how products and brands are introduced into entertainment programming through institutional and organizational mechanisms (Russell & Belch 2005). For traditional advertising, the roles of marketer, advertising agency, and media space provider may be predicted and controlled through money exchanges. Still, the product placement’s ‘script to screen' process has received less attention and is seldom known to anyone outside participants. Product placement and how to make it most successful in grabbing viewers' attention to enhance product sales were bolstered following this achievement, according to firms and studies (Gupta & Lord, 1998, Newell, Salmon, & Change, 2006, Walton, 2010). According to Kivijarv (2005), product placement in movies is worth $1.2 billion, which sparked interest from companies. The drawbacks of product placement (the evident 5 desire to market a product and the ability of viewers to ignore the television during commercial breaks) have remained, if not worsened, with improvements in the area of television and movies that first made it an attractive alternative (Jenner, 2014). Brand recognition and conception appear to be more objective measures than brand recall and their influence on purchasing behavior. (Bettman, 1979). 6 CH-2 LITERATURE REVIEW One of the most essential parts of any research project is the literature review, which provides the researcher with the data they need to design their study. Analyzing past findings will help researchers understand gaps in prior research and support their choice of a particular study topic. The literature review is conducted in chronological sequence, with an eye on the study’s goals. Analysis of Product Placement in Web Series and its influence on consumer buying behavior According to Kakkar, advertising on web series and over the top (OTT) platforms is becoming increasingly popular, in part because of the massive audience that is drawn to binge-watching at all hours of the day and night. A. and Nayak. Secondly, it's less expensive and more effective than traditional forms of advertising like TV and radio ads. Many companies are sponsoring OTT platforms to reach a younger demographic that may immediately connect to the product's quality. Advertising can be ignored if the intended audience is not identified. Still, if a product is being sold, it will be accompanied by a movie to ensure that the intended message is sent to them. Advertising revenue is expected to soar due to the burgeoning OTT sector. It helps the product or brand obtain exposure and boost its recall value and brand image through influencer marketing. An Empirical Study of the effectiveness of product placement Patel, H., and Chauhan make the following claims: Product placement includes both the movie and the brand to boost the brand's memory when the product is bought. The only goal is to bring brands and entertainment together in one place. The brand placement provides a chance for the audience to learn about companies and goods while the movie is being described, and it does it discreetly. Advertisements between shows with high TRPs appear to be less effective since viewers often switch channels. As far as character traits go, brand recognition beats out a brand recall. In product placement advertising, advertisers hope to raise awareness of their brand. Relationship between Beliefs towards Product Placement and Usage Behavior Qasim Gul claims that product placement in movies is a way for product marketers to get their products into movies for a charge paid by the movie producers. Product 7 placement or PPL is a pre-planned, non-obtrusive introduction of a brand-named product into a film to influence the cinema audience. An agreement between a movie producer and a marketer may also be necessary for product placement. Putting products in movies is to raise the brand's awareness, boost its memorability, and make it instantly recognizable at the time of purchase. While it is widely accepted that product placement began as a way to enhance the authenticity of movie scenes, in the modern-day, it has grown into a highly effective marketing tool. Traditional advertising has lost its effectiveness over time, and marketers are turning to this popular tactic in its place. It has been an enormous asset in helping them cut through the noise and maintain a higher advertising grade. In an OTT world, only the consumer is on top. When it comes to media and entertainment, Katial claims that the rise of Over-TheTop 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 a few years ago. In 2019, the velocity of this change of OTT companies to offer a wide variety of content while developing an engaging experience for customers accelerated significantly. There has been a notable shift in consumer behavior due to the abundance of options and easy access to content, making bingewatching common. Thus, a great deal is made only to make it look cheesy or tacky. It is possible to target specific viewers based on their profiles and regular watching patterns using OTT platforms, which improves customer relations. OTT, according to Nair, is a crucial tool for establishing a brand, but it should also be viewed as a tool for active integration. Because you can now watch a show that you missed on TV on Digital, there is less need for an appointment presentation thus, we are seeing a lot of clients who want both TV and OTT packages. Advertisers can't expect to reach as many people with just TV plans. To stay ahead of the curve, every major broadcaster in the nation has launched its own OTT service. In the future, you'll be unable to tell the difference between what you're seeing on your TV and what you're watching on an OTT service like Netflix or Hulu. You'll soon see a significant portion of your TV and digital advertising dollars shifting to OTT. There is a movement in spending from TV to OTT platforms since it is all about the same material and screen. Many TV expenses are going to OTT platforms because the content and screen are the same in both mediums. As Nagar Komal points out, in an era of ever-increasing global rivalry, 8 enterprises are working hard to reach out to clients across the country to successfully advertise their products and services. Even though previous attempts to analyze brand placements have been undertaken, further attention is required. Considering how much exposure Brunein audiences have to national and international entertainment, it's reasonable to assume that events like these will affect how customers see the brands they see there. Product placement has emerged as a crucial technique for advertisers and marketers, displacing others as an alternative to the conventional commercial medium of commercial advertising. According to Pamela Homer, it's critical to have a clear picture of the product on screen, to show the brand name in the conversation, and to weave in the brand's story arc. Product placement is becoming increasingly popular, but there is only a limited amount of actual proof to back it up. Increasing the level of coverage from a low to a reasonable level is critical because it allows for better exposure to the message's content and for people to pay attention to the specifics and uniqueness of the message, resulting in better recall. Boredom can lead to larger counterarguments when the message recipient is exposed to a stimulus for an extended period, although this is not always the case. For example, De Gregorio, Federico & Sung, Yongjun discuss the evolution of people's views and social roles. One way to characterize socialization is that it is a process through which young people collectively come to acquire skills, information, and attitudes necessary for their role as consumers in the market. To put it simply, the framework gives a way to examine the impacts and causes of how people learn to execute their responsibilities as consumers in society. Marketing communications approaches like product placement have a mixed reputation among consumers. Knowing this helps advertisers refine their targeting strategies and learn more about the benefits of employing them. According to Osborne Margaret, program viewers commonly detect product placement when they see an essential character consuming cola or driving a highend automobile invisible frames. Even though many people think this to be a modern attempt at making money, these annoying, and at times obnoxious, shots date back to the 1800s. "Tie-ins," "publicity through motion picture," and other terms have been used to describe these product placements, which were assumed by many to be a tradeoff between movie producers and corporations. The product companies often provided the media producers with the items they used in their media rather than 9 having to purchase the things themselves. With the growing number of businesses realizing that it was a way of promoting their products that would be tougher to ignore than a commercial, the number of corporations interested in the format increased. Commercials can be skipped, ignored, or used as an opportunity to get out of the house. Susan Chang suggests product placement for movies and television shows to reduce production costs (Newell et al. 2006). This fundamental concept stays true even when the cost of making and marketing films and television programs rises. Thanks to new technology and creative marketing strategies, even more brands have been included in famous movies and television shows. High-profile product placement failures have occurred because of the uncertainty of business procedures, which have led to misaligned expectations between manufacturers and producers, causing agreements to fail to materialize on the screen. 10 CH-3 RESEARCH METHODOLOGY Research Methodology act as a building block and a mainstay of each discipline either it is scientific or else. The research process is almost analogous to undertaking a journey. Here for this journey important decisions needs to make like what we need to find out, what should be taken into consideration etc. This chapter comprises of methodology use for conducting the present research: Significance of the study Influencer marketing has gained importance in contemporary times as advertising/promoting has become a need in everybody’s life, be it the producer, the traders, or the customer. It plays a vital role in today’s age competitiveness & help to choice content as well as particular platform for viewing experience. Objectives of the study 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. 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. 11  Sample region To achieve the objectives of the study employees’ survey across the INDIA has been taken into consideration. For collection of data a Google Doc questionnaire was designed for the employees to revert for the same.  Type of study The type of study is descriptive. Descriptive- The term descriptive is self-explanatory, and the research that describes a situation, an event, and an institution is descriptive research. It describes the nature of a situation as it exists at the time of study. Descriptive research answers the questions who, what, where, when, and how. Descriptive research is all about describing the phenomenon, observing and drawing conclusions from it. Here, the information is collected without changing the environment (i.e nothing is manipulated). It is any study that is not truly experimental. It includes surveys and fact finding enquiries with adequate interpretation. i.e Primary sources, so as to come up with better results. In the study, Employees perception towards Employee Performance in IT Sector has been analyzed.  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 Procedure The techniques used for collecting the data from the respondents are nonprobability Sampling procedure. Non-probability Sampling- It is a non-structured sample and items are included in the study due to some convenience of the researcher etc. This sampling takes less time and is handy. As all members of population do not get equal chance of being selected, non-probability sampling may be lopsided, loaded with biases and have higher margin of error. I took Convenience Sampling- This is the easiest population members from which 12 to obtain information. The non-probability sampling is used because all of the Respondents were not given the equal opportunity to be considered for the research. This procedure is used for collecting data because the responders belong to IT sector. The purposive sampling is used since only the IT employees of Delhi NCR were targeted not the whole of the society. Only employees involved in the IT sector were considered deliberately for the study. 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.  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 By distributing a well-structured questionnaire about the efficiency of influencer marketing on OTT platforms, the critical data will be collected. They were taking into account demographic information such as age, gender, interest in advertising, and so on. For the survey, a Likert scale, closed-ended questions, multiple-choice questions, and other methods were employed to ensure that the results were accurate. Primary Data Collection Responses will be gathered online through Google forms as part of the data gathering process. People who watch movies and understand advertising will learn about 'Influencer Marketing' through a questionnaire that the researcher will put together. Tool The tool used for data collection for the research was a questionnaire. The 13 questionnaire contained eleven (11) questions and for data analysis we used SPSS tool. Validation of the Tool Dr. Rachin Suri (Assistant Professor of the DBA) at National Institute of technology, Kurukshetra, Haryana validated the tool for the study. Limitations of the Study 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. 14 DATA ANALYSIS INTERPRETATION Introduction This research aimed to learn about the effect and evolution of Influencer Marketing on the OTT platform. The study's goals and objectives must be achieved. There are four central portions to this chapter, one covering the respondents' demographics (which were discussed in the section on the general public), second covering factor analysis which influenced to followers towards OTT platform, third covering T-test and the forth in which use cluster for delving into their perspectives on the impact of influencer marketing advertising. After the data analysis interpretation, the study objectives and hypotheses will be described and achieved. Analysis of the Questionnaire To determine the factors of influencer marketing impact of viewing OTT platform Table 3.1 KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling .943 Adequacy. Bartlett's Test of Approx. Chi-Square 2569.621 Sphericity Df 190 Sig. .000 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. 15 Table 3.2 Communalities Initial [If my favourite Extraction 1.000 .678 1.000 .786 1.000 .656 1.000 .609 influencer recommends an OTT-related brand on social media, I am more likely to try it.] [The more followers an OTT related influencer on social media has, the more trustworthy I find him/her] [Reviews by influencers who have already tried out an OTT-related product are more trustworthy than reviewers provided by the most famous personality.] [OTT-related influencers on social media have my best interest at heart.] 16 [OTT-related 1.000 .468 1.000 .589 1.000 .583 1.000 .529 1.000 .496 influencers on social media will not purposefully endorse a brand that will harm me.] [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.] [If an influencer on social media has a personal experience or review, I am more likely to follow their advice] [OTT-related influencers on social media who themselves achieved a mass audience and comment, like for views are the most authentic.] [Influencers on social media who keep educating themselves by attending OTTrelated viewing choices are the most credible & trustworthy.] 17 [Reviews of movies and 1.000 .629 1.000 .573 1.000 .552 1.000 .578 1.000 .651 1.000 .569 web series made by influencers I follow influence me to watch the content] [Event promotion made by influencer for OTT content influences me to watch that OTT Content] [Interviews of celebrities by influencers is creating major impact on the audience to watch OTT Content] [Contest run by influencers is creating more & more interactive sessions to watch OTT Content] [Casting of social media influencer in an OTT increasing more & more, this influences me to watch the content that have been casted in.] [Reaction videos by influencer can impact on followers to watch the OTT Content] 18 [Short videos and reels 1.000 .657 1.000 .550 1.000 .612 1.000 .554 1.000 .515 are for the information about the upcoming events & movie trailer , web series] [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] [Trust on influencers that the information is provided influences the followers to watch the OTT Content] [Review and comments of influencer are helpful for the followers in deciding what to watch on OTT Platforms] [I find it useful that the influencer provide information by promoting OTT content and this helps me in deciding what to watch] Extraction Method: Principal Component Analysis. The community table mentioned above in Table 3.2 shows the details of all 20 variables and the number of individual releases. The sixth rule of this rule is that any value less than 0.5 should be discarded and the test should 19 again. The subtraction method used remove the variable and activate the method for subtraction is the analysis of the Main Part. All variables have an output value of Initial Eigenvalues Extraction Sums of Rotation Sums of Squared Loadings Squared Loadings % of Varian Cumulati Compon ent 1 % of Total ce 10.4 52.376 ve % 52.376 75 2 1.35 Varian Cumulati Tot Varian Cumulati Total ce 10.4 52.376 75 6.795 59.170 9 1.35 .842 4.209 63.379 4 .804 4.020 67.399 5 .684 3.422 70.821 6 .651 3.254 74.076 7 .596 2.982 77.057 8 .574 2.869 79.926 9 .536 2.682 82.608 10 .439 2.196 84.804 11 .436 2.182 86.985 12 .419 2.094 89.079 13 .378 1.889 90.969 14 .326 1.629 92.598 15 .296 1.479 94.077 16 .289 1.447 95.524 17 .268 1.342 96.866 18 .243 1.215 98.081 19 .203 1.015 99.095 20 .181 ve % al ce 52.376 7.24 36.236 ve % 36.236 7 6.795 9 3 % of 59.170 4.58 22.934 59.170 7 .905 100.000 Extraction Method: Principal Component Analysis. Table 3.3 is the most important table. In this table the value of Eigen for each element from the variable is calculated. EFA made Factors until the value of Eigen did not fall below 1. Up to 2 factors Eigen value is always higher than 1 so 2 factors 20 extracted using the PCA method are retained. The first factor of Eigen value is 10.4571and the last value is Eigen is 1.193. There has been a sudden and dramatic decline after Eigen's first value and this climb has an impact and the difference described by the first factor is 52.376 and the second is 6.795. The aggregate percentage of this test was 59.170. The percentage achieved whenever it is more than 60% is considered positive. The variables and factors do not well in the definition of Influencer followers. Table 3.4 Rotated Component Matrixa Component 1 [Contest run by 2 .742 influencers is creating more & more interactive sessions to watch OTT Content] [Casting of social media .739 influencer in an OTT increasing more & more, this influences me to watch the content that have been casted in.] 21 [Trust on influencers .736 that the information is provided influences the followers to watch the OTT Content] [Short videos and reels .735 are for the information about the upcoming events & movie trailer , web series] [Review and comments .722 of influencer are helpful for the followers in deciding what to watch on OTT Platforms] [Merchandise related to .707 the OTT Content with increase the foot fall on the online platform & reviews related to the brand that is endorsed by the influencer] [Reaction videos by .701 influencer can impact on followers to watch the OTT Content] [Event promotion made .701 by influencer for OTT content influences me to watch that OTT Content] 22 [Interviews of celebrities .662 by influencers is creating major impact on the audience to watch OTT Content] [Reviews of movies and .640 web series made by influencers I follow influence me to watch the content] [I find it useful that the .613 influencer provide information by promoting OTT content and this helps me in deciding what to watch] [If an influencer on .611 social media has a personal experience or review, I am more likely to follow their advice] [Influencers on social .597 media who keep educating themselves by attending OTTrelated viewing choices are the most credible & trustworthy.] 23 [OTT-related influencers .515 on social media who themselves achieved a mass audience and comment, like for views are the most authentic.] [The more followers an .863 OTT related influencer on social media has, the more trustworthy I find him/her] [If my favourite .815 influencer recommends an OTT-related brand on social media, I am more likely to try it.] [Reviews by influencers .722 who have already tried out an OTT-related product are more trustworthy than reviewers provided by the most famous personality.] [OTT-related influencers .633 on social media have my best interest at heart.] 24 [If I found out that a OTT .585 -related influencer had been paid for a post on social media, it would not negatively impact my perception of their credibility.] [OTT-related influencers .514 on social media will not purposefully endorse a brand that will harm me.] Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 3 iterations. 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 table above shows the order of the items according to their contribution. The contribution described in Table 3.3 in which the full variance of the scale was defined. 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 25 These are the two factors that represent the scale designed by the researcher. The research further progresses to other objectives that require parametric and nonparametric testing based on these factors. Frequency Table Table 3.5 gender Cumulative Frequency Valid Percent Valid Percent Percent Male 103 51.0 51.2 51.2 Female 98 48.5 48.8 100.0 Total 201 99.5 100.0 Missing System 1 .5 Total 202 100.0 Table 3.5 with the use of SPSS table 3.5 revealed that most respondent in this study are males (51.0%) and in other side ( 48.5%) are female respondents . Table 3.6 age Cumulative Frequency Valid Missing Percent Valid Percent Percent Below 18 19 9.4 9.5 9.5 18 - 25 62 30.7 30.8 40.3 26 - 35 76 37.6 37.8 78.1 36 - 50 36 17.8 17.9 96.0 Above 50 8 4.0 4.0 100.0 Total 201 99.5 100.0 System 1 .5 202 100.0 Total Table 3.6 revealed that most respondents having age group 26-35 (37.8%) and only 4 % respondents are from above 50. 26 Table 3.7 Occupation Cumulative Frequency Valid Workinf Full time more Percent Valid Percent Percent 45 22.3 22.4 22.4 36 17.8 17.9 40.3 Student 88 43.6 43.8 84.1 Temporarily 21 10.4 10.4 94.5 Retired 9 4.5 4.5 99.0 Permanently 2 1.0 1.0 100.0 Total 201 99.5 100.0 System 1 .5 202 100.0 than 30 hours a week Working Part time 8 - 30 hours a week unemployed Unemployed Missing Total Table 3.7 the major percentage of the respondent are students with (43.6%) where as only 1% are permanently unemployed . Table 3.8 What is your frequency of viewing OTT content Cumulative Frequency Valid Percent Valid Percent Everyday 93 46.0 46.3 46.3 Thrice a week 35 17.3 17.4 63.7 Twice a week 33 16.3 16.4 80.1 Onc a week 29 14.4 14.4 94.5 Few times in a 11 5.4 5.5 100.0 Total 201 99.5 100.0 System 1 .5 month Missing Percent 27 Total 202 100.0 Table 3.8 show that the number of respondents that are viewing OTT are everyday (46%) and the lowest respondents are with few tine in months(5.4%) . To analyze the impact of demographic on the perception of impact influencer marketing on the viewing choice of OTT platform. Table 3.9 One-way ANOVA based on Age Descriptives 95% Confidence Interval for Mean Std. N Mean Deviatio Std. Lower Upper Minim Maxim n Error Bound Bound Influencer Belo 19 .39673 .744504 .17080 .03789 .75557 Credibility w 18 52 25 099 57 48 um um - 1.2454 1.8966 4 9 18 - 62 -.1237 .988251 .12550 -.3747 .12718 25 815 20 803 503 73 - 1.7524 3.3371 3 9 26 - 76 -.1377 1.12304 .12882 -.3943 .11887 35 476 484 208 744 91 - 2.0212 3.5494 5 3 36 - 36 .24634 .806919 .13448 -.0266 .51936 50 14 41 657 808 37 - 1.7051 2.3781 1 7 28 Abo 8 .21712 .855404 .30243 -.4980 .93226 ve 63 46 115 097 23 50 1.4867 1.4855 3 6 Tota 20 .00000 1.00000 .07053 -.1390 .13908 l - 1 00 000 456 868 68 - 2.0212 3.5494 5 3 Trustworthi Belo 19 -.1984 1.04075 .23876 -.7001 .30313 ness and w 18 931 063 457 188 26 content quality - 1.2656 2.7752 6 0 18 - 62 .18741 .921556 .11703 -.0466 .42144 25 06 04 773 208 20 - 1.7127 1.8505 2 8 26 - 76 -.0556 1.07147 .12290 -.3005 .18915 35 898 802 696 330 34 - 1.8270 2.5080 5 3 36 - 36 -.1324 .968430 .16140 -.4601 .19521 50 587 51 509 284 11 - 1.1828 2.4459 9 8 Abo 8 .14410 .910911 .32205 -.6174 .90564 ve 58 47 584 352 69 50 1.0005 1.4900 3 4 Tota 20 .00000 1.00000 .07053 -.1390 .13908 l - 1 00 000 456 868 68 - 1.8270 2.7752 5 0 Table 3.9 is the definition table. This table 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. 29 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. Table 3.10 Test of Homogeneity of Variances Levene Influencer Credibility Statistic df1 df2 Sig. Based on Mean 2.398 4 196 .052 Based on Median 2.370 4 196 .054 Based on Median 2.370 4 193.18 .054 and with adjusted df Based on trimmed 9 2.506 4 196 .043 mean Trustworthiness and Based on Mean .892 4 196 .470 content quality Based on Median .768 4 196 .547 Based on Median .768 4 193.47 .547 and with adjusted df Based on trimmed 0 .915 4 196 .456 mean Table 3.10 shows the statistics of Levene's test results. Levene's analysis shows that the differences between the three categories are the same for each variability or not. This is for comparison, if the variance of all two sample differs, it means that ANOVA does not work. Sig. Levene value should be greater than 0.05 to indicate that the two variants are equal and the samples are compared. In the above test the total number of all components is above 0.05, which means that the classification or 30 sampling by age is comparable. Table 3.11 ANOVA Sum of Mean Squares df Square F Sig. 7.944 4 1.986 2.027 .092 192.056 196 .980 Total 200.000 200 Trustworthiness Between 3.960 4 .990 .990 .414 and content Groups quality Within 196.040 196 1.000 200.000 200 Influencer Between Credibility Groups Within Groups Groups Total Table 3.11 is the ANOVA table. The table above shows the differences in the categories according to age. The value of the F test is that if it exceeds 0.05 level it shows no difference in opinion and categories. In the above test the values ​of all the components are higher than the level of 0.05. The trustworthiness and content quality is a structure in which the view reflects diversity. Sig value for influencer objects is .092. Table 3.12 One-way ANOVA based on Occupation Descriptives 31 95% Confidence Interval for Mean Std. N Mean Deviatio Std. Lower Upper Minim Maxim n Error Bound Bound Influencer Workinf 45 .02586 .909551 .13558 -.2473 .29912 Credibility Full time 25 55 794 971 20 more um um - 1.880 2.044 85 89 than 30 hours a week Working 36 -.1069 1.22944 .20490 -.5229 .30905 Part 327 580 763 173 19 time 8 - - 2.021 3.337 25 19 30 hours a week Student 88 .00175 .971277 .10353 -.2040 .20754 53 12 849 387 92 - 1.886 3.549 14 43 Tempor 21 -.1469 .991896 .21644 -.5984 .30458 arily 254 53 957 313 04 unempl - 1.705 2.044 11 89 oyed Retired 9 .63502 .736399 .24546 .06898 1.2010 -.3939 1.943 92 Perman 2 ently 82 661 -.0492 .276959 .19584 621 97 027 Unempl 21 2.5376 487 oyed 32 762 4 08 2.4391 -.2451 .14658 244 0 Total 20 .00000 1.00000 .07053 -.1390 .13908 1 00 000 456 868 68 - 2.021 3.549 25 43 Trustworth Workinf 45 -.2815 .945353 .14092 -.5656 .00242 iness and Full time content more quality than 30 868 39 496 024 88 - 1.530 2.445 59 98 hours a week Working 36 .20968 1.04590 .17431 -.1441 .56356 Part 68 435 739 963 99 time 8 - - 1.827 2.189 05 68 30 hours a week Student 88 .08631 .984636 .10496 -.1223 .29493 42 11 256 103 87 - 1.712 2.775 72 20 Tempor 21 -.1470 1.01838 .22223 -.6105 .31654 arily 194 768 041 840 51 unempl - 1.182 1.794 89 02 oyed Retired 9 -.1667 1.02675 .34225 -.9559 .62250 284 720 240 639 70 - 1.000 1.726 53 70 Perman 2 1.0574 .346175 .24478 ently 981 68 317 Unempl 2.0527 4.1677 .8127 1.302 632 1 28 - 1.827 2.775 05 670 oyed Total 20 .00000 1.00000 .07053 -.1390 .13908 1 00 000 456 868 68 20 33 Table 3.12 is the definition table. This table shows the division of the sample total into six occupations has groups. The first one is influencer credibility in this case first phase working full time more than 30 hours a week has 45 responders in its category. The second phase is working part time 8-30 hours a week have a 36 respondent in that category and the third phase of the students has 88 responders and the fourth phase is temporarily unemployed and has 21 and the fifth one in this phase is retired has 9 responders and the last one in this phase is permanently unemployed has 2 respondent 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 working full time more than 30 hours a week has 45 responders in its category. The second phase is working part time 8-30 hours a week have a 36 respondent in that category and the third phase of the students has 88 responders and the fourth phase is temporarily unemployed and has 21 and the fifth one in this phase is retired has 9 responders and the last one in this phase is permanently unemployed has 2 respondent 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. Table 3.13 Test of Homogeneity of Variances Levene Statistic df1 df2 Sig. Influencer Based on Mean 1.357 5 195 .242 Credibility Based on Median .906 5 195 .478 Based on Median .906 5 173.48 .478 and with adjusted 4 df Based on trimmed 1.288 5 195 .271 .623 5 195 .682 mean Trustworthiness Based on Mean 34 and content quality Based on Median .506 5 195 .772 Based on Median .506 5 179.34 .772 and with adjusted 9 df Based on trimmed .614 5 195 .690 mean Table 3.13 shows the statistics of Levene's test results. Levene's analysis shows that the differences between the three categories are the same for each variability or not. This is for comparison, if the variance of all two sample differs, it means that ANOVA does not work. Sig. Levene value should be greater than 0.05 to indicate that the two variants are equal and the samples are compared. In the above test the total number of all components is above 0.05, which means that the classification or sampling by occupation is comparable. Table 3.14 ANOVA Sum of Mean Squares df Square F Sig. 4.530 5 .906 .904 .480 195.470 195 1.002 Total 200.000 200 Trustworthiness Between 8.747 5 1.749 1.784 .118 and content quality Groups 191.253 195 .981 200.000 200 Influencer Between Credibility Groups Within Groups Within Groups Total Table 3.14 is the ANOVA table. The table above shows the differences in the categories according to age. The value of the F test is that if it exceeds 0.05 level it shows no difference in opinion and categories. In the above test the values ​of all the components are higher than the level of 0.05. The influencer credibility is a structure 35 in which the view reflects diversity. Sig value for trustworthiness and content quality objects is .118. Table 3.15 One-way ANOVA based on Frequency of viewing Descriptives 95% Confidence Interval for Mean Std. N Influencer Credibility Mean Deviatio Std. Lower Upper Minim Maxim n Error Bound Bound Every 93 .16393 .812443 .08424 -.0033 .33125 day 48 28 644 859 56 um um - 1.8808 2.6476 5 9 Thrice 35 -.2095 1.23044 .20798 -.6321 .21316 a 115 247 274 833 03 - 1.8861 3.5494 4 week 3 Twice 33 -.1098 1.22076 .21250 -.5426 .32303 - 2.0212 3.3371 5 a 306 912 863 965 53 week 9 Onc a 29 .00031 1.01662 .18878 -.3863 .38702 - 1.9430 2.0448 8 week 88 188 194 835 11 9 Few times 11 -.3907 .711200 .21443 -.8685 .08707 157 88 513 in a 070 55 1.4497 0 month 36 .68170 Total 20 .00000 1.00000 .07053 -.1390 .13908 1 00 000 456 868 68 - 2.0212 3.5494 5 3 Trustworthi Every 93 .12104 .953043 .09882 -.0752 .31732 ness and day 45 23 598 324 15 content quality - 1.8270 2.7752 5 0 Thrice 35 -.3382 1.15335 .19495 -.7344 .05791 a 724 698 291 644 96 - 1.7127 2.5080 2 week 3 Twice 33 .12028 .900389 .15673 -.1989 .43954 - 1.5305 2.0024 9 a 19 21 764 822 60 week 6 Onc a 29 -.1739 .998215 .18536 -.5536 .20575 - 1.5976 1.9526 3 week 429 56 398 438 80 1 Few 11 .15067 1.01953 .30740 -.5342 .83560 times 58 447 121 568 83 in a - 1.5175 1.3148 1 2 month Total 20 .00000 1.00000 .07053 -.1390 .13908 1 00 000 456 868 68 - 1.8270 2.7752 5 0 Table 3.15 is the definition table. This table shows the division of the sample total into five frequency of viewing have groups. The first one is influencer credibility in this case first phase everyday viewing has 93 responders in its category. The second phase is thrice a week viewing have 35 respondent in that category and the third phase of twice a week viewing has 33 responders and the fourth phase is ones a week viewing and has 29 respondent and the fifth one in this phase is few times in a months has 11 responders and in its category making it a total of 201 respondents' data. The second one is trustworthiness and content quality in this case first phase everyday viewing has 93 responders in its category. The second phase is thrice a week viewing have 35 respondent in that category and the third phase of twice a week viewing has 33 responders and the fourth phase is ones a week viewing and 37 has 29 respondent and the fifth one in this phase is few times in a months has 11 responders and 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. Table 3.16 Test of Homogeneity of Variances Levene Influencer Credibility Statistic df1 df2 Sig. Based on Mean 4.577 4 196 .001 Based on Median 3.619 4 196 .007 Based on Median and 3.619 4 182.959 .007 4.479 4 196 .002 with adjusted df Based on trimmed mean Trustworthiness and Based on Mean 1.803 4 196 .130 content quality Based on Median 1.683 4 196 .155 Based on Median and 1.683 4 179.608 .156 1.895 4 196 .113 with adjusted df Based on trimmed mean Table 3.16 shows the statistics of Levene's test results. Levene's analysis shows that the differences between the four categories are the same for each variability or not. This is for comparison, if the variance of all two sample differs, it means that ANOVA does not work. Sig. Levene value should be greater than 0.05 to indicate that the two variants are equal and the samples are compared. In the above test the total number of all components is below 0.05, which means that the classification or sampling by occupation is comparable. 38 Table 3.17 ANOVA Sum of Trustworthiness Between and content quality Groups Within Mean Squares df Square F Sig. 6.972 4 1.743 1.770 .136 193.028 196 .985 200.000 200 Groups Total Table 3.17 is the ANOVA table. The table above shows the differences in the categories according to frequency of viewing. The value of the F test is that if it exceeds 0.05 level it shows no difference in opinion and categories. In the above test the values ​of all the components are higher than the level of 0.05. The trustworthiness and content quality is a structure in which the view reflect Sig value for trustworthiness and content quality objects is .136 Table 3.18 Robust Tests of Equality of Means Influencer Credibility Welch Statistica df1 df2 Sig. 1.961 4 49.536 .115 a. Asymptotically F distributed. Table 3.18 of robust test of equality of means show the influencer credibility which the view reflect sig value of object is .115 above the level of 0.05. T-Test based on gender 39 Table 3.19 Group Statistics Std. Error gender N Mean Std. Deviation Mean Male 103 .1213862 .87391411 .08610932 Female 98 -.1275793 1.10755234 .11187968 Trustworthiness and Male 103 .1060458 1.02307889 .10080696 content quality Female 98 -.1114563 .96784309 .09776692 Influencer Credibility In above table 3.19 The following test is the Independent Sample T-Test used to analyze and compare the variance between responses between two individual samples. This T test is used to compare the male & female. There are two stages a researcher has taken to look a influencer credibility & trustworthiness and content quality. description table. This table shows the division of the complete sample into two categories based on influencer credibility & trustworthiness and content quality. The first phase of the sample is male has 103 respondents in its category and female has 98 respondents in influencer credibility. The second category is male has 103 respondents in its category and female has 98 respondents in trustworthiness and content quality. 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. Table 3.20 Independent Samples Test 40 Levene' s Test for Equality of Varianc es t-test for Equality of Means 95% Confidence Interval of the Difference Sig. (2Sig F . Mean Error taile Differe Differe t Influencer Equal 4.2 .04 1.7 Credibility varian 86 0 Std. df d) 199 74 nce nce Lower Upper .078 .24896 .14036 -.02782 .52575 549 170 168 267 ces assum ed Equal 1.7 184.4 .079 .24896 .14118 -.02957 .52750 varian 63 18 .01 .89 1.5 199 549 030 067 166 ces not assum ed Trustworthi Equal ness and varian content ces quality assum 8 4 47 .124 .21750 .14062 -.05980 .49480 208 ed 41 418 269 685 Equal 1.5 198.9 .123 .21750 .14042 -.05941 .49442 varian 49 94 208 939 862 278 ces not assum ed In the above table 3.20 Differences of opinion categories divided on the basis of equal variances assumed and equal variances not assumed they have. The respondent data in the table above were analyzed based on t. Independent variance is a a influencer credibility & trustworthiness and content quality. on the basis that the sample is divided into 2 parts and the above-mentioned 2 aspects of work ethic have been compared. There are two main points that are highlighted in the table above. One is Levene's test and the other is the 'critical level of tailed 2'. In the table mentioned above, Levene's value shows two different sample variables that are divided on the basis of a influencer credibility & trustworthiness and content quality equal or not. If the Levene sig value is above the 0.05 level then the same variance is considered and the 2-tailed value taking the same variance is the study otherwise the non-considered variance is studied. As in the table above all Levene values ​above 0.05, the value of the estimated variance will be calculated. Similarly if the value of the tail value of 2 is more than 0.05 then their view of the two segment is inseparable. Which means that the effect of a influencer credibility & trustworthiness and content quality, as a variable is non-existent and the total value is more than 0.05. To identify the size of cluster which is highly influenced by influencer marketing on its viewing choice of OTT platform. Quick Cluster 42 Table 3.21 Final Cluster Centers Cluster [If my favourite 1 2 4 2 4 2 4 2 4 2 4 2 influencer recommends an OTT-related brand on social media, I am more likely to try it.] [The more followers an OTT related influencer on social media has, the more trustworthy I find him/her] [Reviews by influencers who have already tried out an OTT-related product are more trustworthy than reviewers provided by the most famous personality.] [OTT-related influencers on social media have my best interest at heart.] [OTT-related influencers on social media will not purposefully endorse a brand that will harm me.] 43 [If I found out that a OTT 4 2 4 2 4 3 4 3 4 2 -related influencer had been paid for a post on social media, it would not negatively impact my perception of their credibility.] [If an influencer on social media has a personal experience or review, I am more likely to follow their advice] [OTT-related influencers on social media who themselves achieved a mass audience and comment, like for views are the most authentic.] [Influencers on social media who keep educating themselves by attending OTT-related viewing choices are the most credible & trustworthy.] [Reviews of movies and web series made by influencers I follow influence me to watch the content] 44 [Event promotion made 4 2 4 2 4 3 4 2 4 3 4 2 by influencer for OTT content influences me to watch that OTT Content] [Interviews of celebrities by influencers is creating major impact on the audience to watch OTT Content] [Contest run by influencers is creating more & more interactive sessions to watch OTT Content] [Casting of social media influencer in an OTT increasing more & more, this influences me to watch the content that have been casted in.] [Reaction videos by influencer can impact on followers to watch the OTT Content] [Short videos and reels are for the information about the upcoming events & movie trailer , web series] 45 [Merchandise related to 4 3 4 3 4 3 4 3 the OTT Content with increase the foot fall on the online platform & reviews related to the brand that is endorsed by the influencer] [Trust on influencers that the information is provided influences the followers to watch the OTT Content] [Review and comments of influencer are helpful for the followers in deciding what to watch on OTT Platforms] [I find it useful that the influencer provide information by promoting OTT content and this helps me in deciding what to watch] The above mentioned table 3.21 represents the 2 groups that were made after a the study of the dendrogram. The graph represent close association at micro level In the major division out of which the largest division further showed two segregation . hence it was decided based on the dendrogram that in K means Cluster, 2 divisions of the sample will be studied . the nature of response of the respondent in the above 2 division shows a significance difference in the opinion recorded of the respondents. .Table depict that the ANOVA table this represent that the division are significantly different on each variable. The second 46 cluster is the cluster that has been chosen to check the demographic profile . in this cluster the representation of variable were found significantly higher in comparison to the other three clusters. This cluster respondent seems to be influenced higher by influencer marketing factor than other three clusters. Table 3.21.1 ANOVA Cluster [If my favourite Error Mean Square df Mean Square df F Sig. 84.318 1 1.389 199 60.724 .000 92.803 1 .830 199 111.846 .000 99.460 1 .774 199 128.438 .000 115.326 1 .781 199 147.597 .000 influencer recommends an OTT-related brand on social media, I am more likely to try it.] [The more followers an OTT related influencer on social media has, the more trustworthy I find him/her] [Reviews by influencers who have already tried out an OTT-related product are more trustworthy than reviewers provided by the most famous personality.] [OTT-related influencers on social media have my best interest at heart.] 47 [OTT-related influencers 109.850 1 .779 199 141.010 .000 98.397 1 .718 199 137.116 .000 106.255 1 .562 199 189.155 .000 76.668 1 .735 199 104.329 .000 70.913 1 .755 199 93.883 .000 on social media will not purposefully endorse a brand that will harm me.] [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.] [If an influencer on social media has a personal experience or review, I am more likely to follow their advice] [OTT-related influencers on social media who themselves achieved a mass audience and comment, like for views are the most authentic.] [Influencers on social media who keep educating themselves by attending OTT-related viewing choices are the most credible & trustworthy.] 48 [Reviews of movies and 111.641 1 .689 199 162.065 .000 86.258 1 .649 199 132.946 .000 80.927 1 .702 199 115.345 .000 72.046 1 .683 199 105.424 .000 100.311 1 .538 199 186.450 .000 79.629 1 .582 199 136.907 .000 web series made by influencers I follow influence me to watch the content] [Event promotion made by influencer for OTT content influences me to watch that OTT Content] [Interviews of celebrities by influencers is creating major impact on the audience to watch OTT Content] [Contest run by influencers is creating more & more interactive sessions to watch OTT Content] [Casting of social media influencer in an OTT increasing more & more, this influences me to watch the content that have been casted in.] [Reaction videos by influencer can impact on followers to watch the OTT Content] 49 [Short videos and reels 109.831 1 .630 199 174.428 .000 72.046 1 .623 199 115.627 .000 83.522 1 .699 199 84.135 1 .672 199 125.175 .000 85.101 1 .670 199 127.058 .000 are for the information about the upcoming events & movie trailer , web series] [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] [Trust on influencers 119.475 .000 that the information is provided influences the followers to watch the OTT Content] [Review and comments of influencer are helpful for the followers in deciding what to watch on OTT Platforms] [I find it useful that the influencer provide information by promoting OTT content and this helps me in deciding what to watch] The F tests should be used only for descriptive purposes because the clusters have been chosen to maximize the differences among cases in different clusters. The observed significance levels are not corrected for this and thus cannot be interpreted as tests of the hypothesis that the cluster means are equal. 50 Table 3.21.1 represent the ANOVA results. As it can be seen that the significance value of every variable is very low. In this case every variable value is low then 0.05, that is measure a point that shows the values low to represent significance in the variation of the response of the sample division that is compared. The above mentioned the there is group is highly influenced by marketing effort of influencer . this is the matter of fact that closely group 1 & 2 both show influencer marketing & the number represent more then 50% of the total sample size. The worth of influencer marketing efforts can be seen here but the study is created for the different objective. Table 3.21.2 Number of Cases in each Cluster Cluster 1 164.000 2 37.000 Valid 201.000 Missing 1.000 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. Conclusion Primary data was examined and presented in this chapter based on information gathered during the research process. Each table was described in detail. The next chapter focuses on the most important discoveries from the previous research. 51 FINDINGS, DISCUSSIONS, AND RECOMMENDATIONS Introduction Data analysis has yielded several significant conclusions discussed in this chapter. For this reason, the findings are described in greater depth so that the researcher can offer new study ideas. Objectives Achieved To achieve the following goals, the researcher used a thorough study of both primary and secondary data: To analyze the new way of product placement through influencer marketing. To show how effective it is by stating examples. To show it is imp in brand recall. To study consumers' attitudes towards the Impact of Influencer Marketing advertising. Restatement of Hypothesis The research hypotheses were: Influencer marketing influences the decision process. Influencer marketing is on the rise and is an effective tool for brand recall. Brand awareness from product placement in movies affects an enhanced brand image. According to the data research, people still rely on television commercials to influence their purchasing decisions. Therefore, influencer marketing aids in product recall and improves the brand’s image, while the other two theories have been proven correct. Summary of Findings 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. 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 52 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. Limitations of the Study. The researcher was lacking in these areas when working on this thesis: The poll was limited to a particular geographic area, omitting a wide range of viewpoints that may have influenced this research. The sample size of this study is small. For future researches, to get a representative results, population and sample size should be taken large. Convenient sampling method was used due to limited availability of time and resource that may not provide more universal results. Moreover, the response given in the questionnaire may be influenced by some personal characteristics of the respondent. 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. 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 53 (over-the-top) platforms, rapidly displacing traditional television and creating a new type of medium. Bruneian audiences have always been deeply invested in their performances when it comes to on-screen actors. Artists have always been a go-to source for the latest style, from clothing to hairdos. Since advertising through Influencers have always used popular films to promote their products, shows it should come as no surprise that product placement is bringing about a paradigm shift through OTT when it comes to the entertainment business. followers are looking for an eyecatching content to influence the audience. As a result, influencer marketing has become an integral aspect of the advertising industry in the following years and decades. The study was focused on finding the factors of influencer marketing impacting the viewing OTT platform. Further, the impact of demographic variables on the perception of impact influencer marketing on the viewing choice of OTT platform was also analyzed through t test and anova. The findings revealed that Influencer Credibility and Trustworthiness and content quality are not influenced by demographic variables. 54 References 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. Kit, L. C., & P'ng, E. L. Q. (2014). The effectiveness of product placement: The influence of product placement on consumer behavior of the millennial generation. International Journal of Social Science and Humanity, 4(2), 138142. Nair, N. (2019, December 16). How to unleash the potential of advertising on OTT platforms. Osborne, M. (2016). Product placement in House of Cards: the effects of presentation mode and prominence on memory (Doctoral dissertation). Chauhan, H. C., Patel, B. K., Bhagat, A. G., Patel, M. V., Patel, S. I., Raval, S. H., ... & Chandel, B. S. (2015). Comparison of molecular and microscopic techniques for detection of Theileria annulata from the field cases of cattle. Veterinary World, 8(11), 1370. Qureshi, I. H., & Gul, M. (2015). Product placement in movies: Relationship between beliefs towards product placement and usage behavior. Indian Journal of Marketing, 45(7), 35-47. Ramesh, P., Shivde, R., Jaishankar, D., Saleiro, D., & Le Poole, I. C. (2021). A palette of cytokines to measure anti-tumor efficacy of T cell-based therapeutics. Cancers, 13(4), 821. 55 Redondo, I. (2006). Product-placement planning: How is the industry placing brands about moviegoer consumption?. Journal of International Consumer Marketing, 18(4), 33-60. 56 APPENDIX: QUESTIONNAIRE 1. What is you gender? female male transgender 2. What is your age? under 18 18 - 25 26 - 35 36 - 50 above 50 3. What is your occupation? working full time (more than 30 hours a week) working part-time (8-30 hours a week) student (full-time) temporarily unemployed retired permanently unemployed 4. Are you an active OTT platform user yes no 5. Do you follow one or more social media influencers, whose content is evolving around OTT Platform or informational posts on Instagram and Facebook? yes no Continues if both were answered with yes 6. What is your frequency of viewing OTT content Everyday Thrice a week Twice a week Once a week 57 Few times in a month 7. After reading each of the statements below please indicate your level of agreement by using the following scale: “Strongly disagree”, “Disagree”, “Neutral, “ agree”, “Strongly agree”. Strongly disagree If my favourite influencer recommends an OTT-related brand on social media, I am more likely to try it. The more followers an OTT related influencer on social media has, the more trustworthy I find him/her Reviews by influencers who have already tried out an OTT-related product are more trustworthy than reviewers provided by the most famous personality. OTT-related influencers on social media have my best interest at heart. OTT-related influencers on social media will not purposefully endorse a brand that will harm me. 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. If an influencer on social media has a personal experience or review, I am more likely to follow their advice OTT-related influencers on social media who themselves achieved a mass audience and comment, like for views 58 Disagree Neutral Agree Strongly agree are the most authentic. Influencers on social media who keep educating themselves by attending OTTrelated viewing choices are the most credible & trustworthy. Reviews of movies and web series made by influencers I follow influence me to watch the content Event promotion made by influencer for OTT content influences me to watch that OTT Content Interviews of celebrities by influencers is creating major impact on the audience to watch OTT Content Contest run by influencers is creating more & more interactive sessions to watch OTT Content Casting of social media influencer in an OTT increasing more & more, this influences me to watch the content that have been casted in. Reaction videos by influencer can impact on followers to watch the OTT Content Short videos and reels are for the information about the upcoming events & movie trailer , web series 59 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 Trust on influencers that the information is provided influences the followers to watch the OTT Content Review and comments of influencer are helpful for the followers in deciding what to watch on OTT Platforms I find it useful that the influencer provide information by promoting OTT content and this helps me in deciding what to watch 10. Rank OTT platform of your choice from 1 to 10. i. Netflix ii. Amazon prime iii. Apple TV iv. ZEE 5 v. Hulu vi. MX Player vii. Disney plus Hotstar viii. Voot ix. Sony Liv x. Alt Balaji 11. What if your favourite day and time to watch OTT content ______________________________________ 60 12. Is any influencer that influence you for viewing or using OTT platforms. ________________________________ 61 62 63