The Relationship between Digital Marketing, Customer Engagement, and Purchase Intention via OTT Platforms

Habib, Sufyan; Hamadneh, Nawaf N.; Hassan, Asif

doi:https://doi.org/10.1155/2022/5327626

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Volume 2022 | Article ID 5327626 | https://doi.org/10.1155/2022/5327626

The Relationship between Digital Marketing, Customer Engagement, and Purchase Intention via OTT Platforms

Sufyan Habib,¹Nawaf N. Hamadneh,²and Asif Hassan¹

Academic Editor: Miaochao Chen

Received20 Oct 2021

Revised03 Dec 2021

Accepted14 Mar 2022

Published14 Apr 2022

Abstract

The Internet and digital technologies have grown exponentially and have become a part of billions of people’s daily lives around the world. Over-the-top (OTT) services are delivered directly over the Internet, providing customers access to films and TV series. In India, there has been a tremendous surge in the consumption of video material on OTT platforms. The significant growth in the digital marketing application in online businesses and its ability to engage customers has enhanced its importance. The emergence of the Internet and digital technologies has provided a modernized setting and a fertile ground for business organizations to reach millions of customers at affordable prices with effective and customized promotion content. The present study aims to investigate the relationship between digital media marketing (DMM), consumer engagement, brand image, and OTT platform purchase intention in the Indian context. The researchers will also investigate the mediating role of consumer engagement and brand image in mediating the relationship between digital marketing practices and OTT platform purchase intention. In a survey of 417 Indian consumers, it was found that there was no direct effect of DMM on the purchase intention of OTT platforms. In addition, there is a strong indirect effect through brand image and consumer engagement, supporting the hypothesis that brand image and consumer engagement mediate the relationship between DMM practices and the purchase intention of OTT platforms. Some of the managerial implications, limitations, and scope of future research are also presented in the study.

1. Introduction

The information revolution and digitalization across the globe have changed the way of media consumption among people. The emergence of new OTT media that provides services to viewers directly over the internet has occurred due to an increase in the number of internet connections, improved networks, technological advancements, and the availability of smart gadgets. With a 45-percent growth rate predicted, India is on track to become the world’s second-largest OTT market (after the United States), with a market value of INR 138 billion by the end of fiscal year 2023. Popular OTT service providers like YouTube, Netflix, and Spotify have played an important part in the expansion of data streaming. DMM is a type of Internet marketing that allows customers to easily communicate with marketers via digital channels. DMM refers to the practical and comprehensive use of the Internet, digital media platforms, and marketing tools to achieve total business success in the context of multichannel marketing [1, 2]. Because of technological advancement and the development of communication technologies, real-world relationships have been transferred to the virtual periphery. This progressive movement of free-world and cross-border relationships via the Internet paves the way for marketers to reach their target audiences [3, 4]. According to recent statistics, there are 4.80 billion internet users worldwide today, accounting for nearly 61% of the global population (Datareport.com). In the last year, the number of social media users increased by more than 13%, and there are now 4.48 billion social media users worldwide, accounting for nearly 57 percent of the world’s total population.

Consumer preferences are shifting away from traditional forms of media and toward digital media consumption. People are spending more time each day on digital rather than traditional forms of media. With the emergence of domestic and international Over-the-Top (OTT) players, consumers now have a plethora of options for content consumption. The spread of the COVID-19 pandemic was game-changing for the media and entertainment industries, hastening the growth of OTT platforms exponentially. Today, there are more than 40 OTT platforms in India including the OTT platforms in regional languages. It goes on to say that the Indian OTT market will grow from $1.5 billion in 2021 to $4 billion in 2025, and then to $12.5 billion by 2030 [5]. Consumer attitudes are shifting away from content ownership and toward having easy access to a vast library at any time and from any location. It enables two-way interaction, allows services to be tailored to each customer, and allows purchases to be created and influenced online.

The usage of the internet, the growth in smartphone users, a high number of young populations, a wide variety of content, attractive offers of OTT platforms, and rising disposable income are major drivers of increasing consumption and spending on OTT platforms. Considering these advantages, the present study was aimed to examine the relationship between digital media marketing, consumer engagement, brand image, and purchase intention of OTT platforms in the Indian context. The researchers will also investigate the role of consumer engagement and brand image in mediating the relationship between digital marketing practices and OTT platform purchase intention. The present study’s findings will be useful for marketers and DMM professionals in developing appropriate promotional and social media strategies, in particular, to influence consumer purchase intentions in this emerging economy.

2. Literature Review and Hypothesis Development

2.1. Digital Media Marketing and Purchase Intention of OTT Platforms

The effects of digital and social media marketing can result in several positive and negative outcomes for organizations. Several studies have found that digital marketing practices have a positive effect on customer acquisition, customer retention, brand image, brand sustainability, brand loyalty, and purchase intention in the context of hotels, luxury fashion brands, lifestyle products, e-commerce, tourism destinations, and education institutions [4, 6–10]. [11] realized that the structure of digital marketing content (interactivity, formality, and immediacy) has a significant impact on consumer behavior, such as brand attitude, corporate trust, and purchase intention. [12–14] examined the future direction of digital media and concluded that digital media can have a significant impact on brand loyalty, sustainability, and business effectiveness. Authors like Zhao and Chen [15] indicated that it has a strong effect on perceived value, and Wang et al. [16] indicated perceived usefulness of product. It is believed by some scholars that perceived benefits are based on trust toward the shopping channels concluded from a review of the literature on the impact of digital marketing published in the previous eight years (2012–2020) that the majority of researchers believe that digital marketing efforts influence the customer’s purchasing intention [17]. They also believe that the distinction between “marketing” and “digital marketing” will soon blur, as every type of marketing activity will include an element of “digital marketing.” Both online and offline channels boast their own advantages, and consumers can choose different channels at different purchasing stages. But current researches can hardly clarify the complexity on studying consumer channel choice in a theoretical way. It is hypothesized that H1: DMM has a significant influence on the purchase intention of OTT platforms.

2.2. Digital Media Marketing and Consumer Engagement

DMM has long been regarded as an important medium for consumer engagement. According to [18], engagement should be considered a psychological state of mind distinct from interactive behavior such as liking and sharing content. While the majority of studies focus on the impact of social media marketing and digital marketing on commercial businesses, some studies focus on nonprofit organizations’ outcomes. Various studies have found a link between DMM and consumer engagement [19–21]. Smith [22], Islam and Rahman [23], Rasool et al. [24], Kaur et al. [25], and Islam et al. [26] investigated the use of Facebook and Twitter in the context of nonprofit organizations, as well as the outcomes and impact on user engagement, and concluded that users respond differently to social media activities across platforms. Consumer interaction and engagement are critical components in assisting marketers in maintaining long-term customer relationships. DMM provides opportunities for participation that foster trust, goodwill, and commitment to the formation of relationships between individuals and brands [27]. Lee et al. [28] examined 106,316 Facebook messages from 782 businesses and discovered that the inclusion of humor and emotion can lead to greater consumer engagement. Fans of brand pages can see posts and interact with them by liking, sharing, and commenting [29–31]. As a result, the information presented with a high level of interactivity generates a high level of online activity. As a result, it is hypothesized that H2: the higher the influence of DMM, the higher the customer engagement towards OTT platforms.

2.3. Digital Marketing Practices and Brand Image of OTT Platforms

Brand image is an important competitive advantage that aids in the creation and maintenance of value by differentiating the brand, forming purchasing justifications, developing a sense and beliefs, and providing significant value to organizations [32, 33]. Brand image is the collection of a customer’s beliefs, ideas, and impressions about a brand. Brand image is built over time through consistent advertising campaigns, and it is authenticated through direct consumer experience. [7, 34, 35] found that digital marketing contents and communication are crucial elements of online marketing strategy and add to brand image and the purchase behavior of shoppers. The brand image of the OTT platform has become important in the present digital era, and every business must have its unique online presence. Thus, OTT platforms must build a positive brand image by staying active on digital media platforms like Instagram, Twitter, and Facebook to keep consumers updated with what is trending. Today, several OTT platforms have partnered with telecom providers to come up with attractive offers, which has helped OTT platforms in improving their brand image and customer base. Social media and digital marketing are increasingly being used as strategic tools for increasing brand recognition and executing marketing campaigns. Moving away from the period of traditional or mass media, marketers may follow brand competitors and have more measurable campaign results in terms of brand image and buy intent by employing social media and digital marketing [36]. These considerations lead to the possibilities listed as follows: H3: DMM has a positive influence on building the brand image of OTT platforms. H4: the brand image of OTT platforms mediates the relationship between DMM and purchase intention of OTT platforms.

2.4. Consumer Engagement and Purchase Intention of OTT Platforms

Customer engagement has been defined as an emotional bond between a firm and its customers that focuses on interaction and participation from customers. Several authors [20] indicated the importance of consumer engagement for building brand communities, developing positive brand image, and influencing consumer purchase intention. Gupta and Singharia [37]examined the Consumption of OTT Media Streaming under COVID-19 Lockdown and discovered that consumer engagement gives a chance for OTT platform providers to leverage on the perceived shift to their benefits. Rhom et al. [38] identified five major reasons that motivate consumers to interact with businesses through social media and affect their purchase intention: amusement, brand engagement, access to consumer services and content, product knowledge, and product promotions. Priya et al. [39] analyzed the particular case of online customer engagement and its influence on subscription intention of OTT platforms by exploring the relationship between OTT, social gratification, and customer engagement towards OTT platform, and subscription intention. In one of the studies undertaken by Bright Local (2014), it was found that more than 80% of small and large businesses use online social media to improve their business performance. According to a study by [20], 88% of surveyed customers affirmed that they follow online reviews to make purchase decisions and consider them to be reliable. The study helps understand whether customer engagement on intention to use OTT platform in the industry matches the international experience. Several authors [40–42] also found a close relationship between technology acceptance, consumer engagement, and purchase intention towards OTT platforms. Thus, it is hypothesized that H5: consumer engagement has a significant influence on purchase intention towards OTT platforms. H6: consumer engagement mediates the relationship between digital marketing practices and purchase intention towards OTT platforms.

To conclude the existing literature review related to study variables and hypothesize the relationship among digital media marketing, consumer engagement Brand image, and purchase intention, a conceptual framework has been designed to show the proposed relationships among the variables (Figure 1).

3. Research Methodology

In the present research work, descriptive research design was used. Both the primary and secondary data were collected to achieve the stated objectives. Secondary data was collected from the various published sources like books, journals, magazines, Internet sources, etc. Primary data was collected from the customer using survey instrument. A well structured questionnaire was designed covering various dimension of the study. To ensure the validity of the survey instrument, the questionnaire was given to a panel of experts (two industry professionals and two marketing academics) who judged the validity of its content, the clarity of its item meaning, and its connections to the research goals. After ensuring the validity, initially, the questionnaire was pilot-tested with 45 respondents, representing 10% of the overall sample size, who were believed to be typical of the research population, to confirm its reliability. Cronbach’s alpha was determined to be 0.893, indicating that the questionnaire had an adequate level of reliability. After assuring the reliability and validity, a full-scale survey was carried out. Nonprobability sampling (convenient and snowball sampling) technique was used to collect the data. Snowball sampling is where research participants recruit other participants for a test or study. It does not have the probability involved, say, simple random sampling. Rather, the researchers used their own judgment to choose participants. Once you have the ball rolling, it picks up more “snow” along the way and becomes larger and larger. Primary data for the present study were collected from Indian customers using online survey questions developed on Google Forms over three months (May–July 2021). Initially, the questionnaire was sent to 500 respondents who were the members of various social media sites like Facebook, LinkedIn, ResearchGate, Tweeter, etc., and further, it was requested to forward this questionnaire to their known one. Variables for digital media marketing, brand image, and customer engagement and purchase intention were identified through the review of relevant literature. The survey questionnaire consisted of three sections. The first part consisted of questions related to the demographic profiles. The second part of the questionnaire was related to consumer viewing patterns of various advertisements in different media and consumer preference of different OTT platforms. The third part of the questionnaire consisted of variables of digital media marketing, consumer engagement, brand image, and purchase intention, developed on the Likert scale (where 1 indicates strongly disagree, and 5 indicates strongly agree). Dimensions of digital product awareness, consumer convenience, personal privacy, feedback and customer compliance, and consumer brand relationship are based on previous works of [7, 43–47]. The measurement variables were further refined and employed for the survey.

Researchers collected 450 replies, and after editing, 417 were judged appropriate and utilized in this study, eliminating 33 responses that were untrustworthy or insincerely addressed. The collected data was carefully organized, tabulated, and analyzed using SPSS 22. To investigate the link between digital media marketing, consumer engagement, brand image, and purchase intention of OTT platforms, data analysis includes descriptive statistics using SPSS 22 and structural equation modeling using Smart-PLS 3.0.

4. Results

Table 1 indicates the demographic information of respondents. 18.47% of respondents represented the age group of fewer than 20 years, 39.09% respondents were found in the age group of 21–25 years, and 31.65% respondents were in the age range of 26–30 years. The remaining 6.47% and 4.32% respondents represented the age group of 31–35 years and more than 35 years, respectively. Male respondents account for 58.99%, and the remaining 41.01% respondents were females. Regarding educational qualification, 29.74% of respondents were less than graduate, 42.69% were graduate, 21.1% respondents were postgraduate, and the remaining 6.47% were professionally qualified.

The information presented in Table 2 indicates the DMM channel usage Pattern as indicated by respondents. The multiple responses thus received were processed, and it was found that search engine optimization (SEO) is used by the majority of respondents (80.6%). 60.7%, 57.6%, 32.9%, 53.7%, 50.4%, 29.0%, 36.2%, 39.6%, and 31.7%, respectively, indicated social media marketing, display/video marketing, e-mail marketing, blogging, web analytics, paid search/contextual advertising, affiliate marketing, apps marketing, and other DMM channels as their preferred channel for getting information about OTT platforms.

The information presented in Table 3 indicates the respondent’s preference of OTT platforms used for various purposes. It is observed that Amazon Prime, Hotstar, and Netflix are the most preferred OTT platform as indicated by 70.2%, 64.9%, and 62% of respondents in the sample. 59.9%, 60.6%, 30.5%, 29.8%, 24.8%, 25.7%, 52.6%, and 17.1% respondents indicated that they subscribe to ALTBalaji, Zee 5, Aha7, Voot, SonyLIV, Viu, Hoichoi, and others OTT platforms.

Data summarized in Table 4 indicate the descriptive statistics (mean and SD) of various factors of DMM influencing the customer to subscribe to OTT platforms. Information presented in Table 4 reveals that various factors of DMM reveal that the “Feedback and customer compliance” factor has received a maximum mean of 4.09 and SD = 0.646. The alpha (α) was found to be 0.789, composite reliability (CR) was found to be 0.856, and Average Variance Explained (AVE) was found to be 0.547. The next important factor of DMM as indicated by customers was Product Awareness, which has a score mean of 4.02 and SD = 0.765. The alpha (α) was found to be 0.695, CR was found to be 0.832, and AVE was found to be 0.623. Other factors include convenience with mean 3.94 and SD 0.673 (α = 0.830, CR = 0.879 AVE = 0.597), information security and personal privacy with mean 3.80 and SD 0.669 (α = 0.756, CR = 0.847, AVE = 0.587), and customer brand relationship with mean 3.88 and SD 0.643 (α = 0.732, CR = 0.849, AVE = 0.652).

Consumer engagement with the OTT platform continuously gains popularity among practitioners and academics. Based on organizational psychology, we adapted three important constructs of consumer engagement, namely, vigor, absorption, and dedication. Further measurement variables were developed, and respondents were asked to rate on a scale from 1 to 5. Descriptive statistics as presented in Table 5 indicate that “absorption” has a score maximum mean of 4.07 with SD = 0.552. Reliability and validity of the construct were found as α = 0.679, CR = 0.824, and AVE = 0.610. The “dedication” component of consumer engagement has scored a mean of 4.04 with SD = 0.649. Reliability and validity of the construct were found as α = 0.695, CR = 0.831, and AVE = 0.623. The “vigor” component of consumer engagement has scored a mean of 3.99 with SD = 0.517. Reliability and validity components of the construct were observed as α = 0.800, CR = 0.872, and AVE = 0.714.

The information presented in Table 6 indicates the perceived brand image as indicated by the respondents in the sample. Descriptive statistics as calculated for brand image measurement variables indicate that statements like “My willingness to become a customer of OTT platform is great” have scored the highest mean of 4.12 with SD 0.813. It is followed by the statement “I can reliably predict how this OTT platform will perform” with a mean of 4.09 and SD 0.863. The combined mean of the brand image was found to be 4.012 and SD 0.666. Reliability and validity of brand image are within the acceptable range (α = 0.758, CR = 0.845, and AVE = 0.578).

Information presented in Table 7 indicates the descriptive statistics calculated for consumer purchase intention. It is observed that the variable “Digital marketing of OTT platforms helps be in identifying the domain” has scored a mean of 4.28 and SD = 0.760. It is followed by the statement “My affinity towards OTT platform is enhanced through digital marketing platforms” with mean = 3.99 and SD = 0.852. The combined mean of the brand image was found to be 4.04 and SD = 0.654. Reliability and validity components of purchase intention are found within the acceptable range (α = 0.758, CR = 0.845, and AVE = 0.578). In addition, the information presented in Table 8 indicates the Discriminants Validity of each construct. Discriminant Validity was calculated with help of smart pls software using Fornell-Larcker Criterion. Note that Discriminant Validity ensures that each model construct is distinct from the other, where one construct is not represented by another in the model.

5. Structural Model and Hypotheses Testing

The structural model fitness and hypothesis testing were carried out using PLS-SEM, which is different from CB-SEM. PLS is widely used in various research disciplines. Its capacity to represent both factors and composites is valued by researchers across disciplines, making it a potential technique for new technology research and information systems research in particular. Whereas factors may be used to represent latent variables in behavioral research, such as attitudes or personality characteristics, composites can be used to model strong ideas, such as the abstraction of objects such as management tools, inventions, or information systems [48]. As a result, PLS route modeling is a popular statistical method for success factor research [49]. The fitness of a structural model is evaluated in PLS-SEM using the Variance Inflation Factor (VIF), R², and standardized path coefficients [50]. VIFs should be less than 3.0 to rule out the potential of multicollinearity among variables; nevertheless, it should be noted that even VIF values between 3 and 5 may suggest a multicollinearity concern [51]. R² should be within acceptable limits, and standardized path coefficients should be statistically significant [50]. All VIFs were above in the range of 1.174 to 3.598, with the highest VIF being 3.598, which were within the acceptable range of 3.0 except DED 1 = 3.326 and AB1 = 3.598 (Table 2). It showed that there was no multicollinearity issue. As a result, Hair et al. [50] noted that even VIF values between 3 and 5 may suggest a multicollinearity concern when assessing the VIF number more conservatively [51, 52]. Buy intention had an R² estimate of 0.544, indicating that the other components in the structural model accounted for 54.4% of the variation in purchase intention. These criteria, taken combined, attested to the structural model’s strong match to the data.

Table 9 presents the results of the path coefficients and values for all the proposed hypotheses. The first hypothesis proposed that DMM has a significant influence on the purchase intention of OTT platforms. The standardized path coefficient from technology acceptance to purchase intention of OTT platforms (β = 0.069, ) was insignificant, and test statistics do not support the proposed first research hypothesis. In other words, digital media marketing has no significant influence on the purchase intention of OTT platforms. Test statistics confirm that DMM practices have positive influence on consumer engagement (β = 0.008, ). Further, test statistics indicate that the impact of consumer engagement has a significant effect on purchase intention of OTT platform (β = 0.139, ), thus supporting the research hypothesis 3. Looking at the relationship between digital marketing practices and brand image of OTT platform, test statistics support the research hypothesis that DMM practices have a significant influence on the brand image of OTT platform (β = 0.351, ), indicating that digital marketing practices have a significant influence on brand image. Test statistics also confirm that the impact of brand image on purchase intention is significant (β = 0.634, ) supporting hypothesis 5, indicating that brand image towards OTT platform has a significant influence on purchase intention. Figure 2 presents the final measurements and structural model.

The information presented in Table 9 indicates the test outcomes of Smart PLS that were conducted to evaluate the effect of mediating variable consumer engagement and Brand Image) of a given independent variable (digital marketing practices) on a given dependent variable (Purchase intention). To start with, the path model was estimated via bootstrapping, without the interaction of a mediator (Figure 1). The results reveal that direct paths are statistically insignificant. Therefore, inclusion of customer engagement and brand image as a mediator is meaningful. We require the significance of indirect paths in order to verify that customer engagement mediates the relationship between digital marketing practices and purchase intention via OTT. To ascertain the significance of these indirect paths, the samples table from bootstrapping was copied and pasted into MS Excel. Here, we computed the t-value of the indirect paths. The t-value of the indirect path Digital Marketing Practices ⟶ Consumer Engagement is 2.408 with . Similarly, the t-value for Consumer Engagement ⟶ Purchase Intention path is 2.252 with .The t-value for Digital Marketing Practices ⟶ Brand Image is 6.969 with , and t-value for Brand Image ⟶ Purchase Intention is 19.500 with , which is significant at 5% level of significance. These test statistics support the hypothesis that customer engagement and brand image mediate the relationship between digital marketing practices and purchase intention via OTT platforms.

6. Discussion

DMM is highly dependent on online media like social media, the Internet, e-mail, affiliate marketing, etc. The study outcome indicated that consumers give more weightage to DMM ability in giving feedback and customer compliance followed by its ability in enhancing product/brand awareness. Customized communication and personal privacy is also an important factor of DMM effectiveness. Brand image-based marketing may be used to communicate with potential customers in a timely and effective manner. An ordinary human being concentrates his attention on a picture in a fraction of a second; the image should have a powerful influence on his thinking. As a result, visual content provided him with brand information in a couple of seconds. To build a successful brand image for their OTT platform, businesses need to place a larger focus on digital media marketing. The current study’s findings are likewise consistent with and consistent with Dholakia and Bagozzi’s earlier work [53].

Marketers to strengthen consumer engagement and build positive purchase intention towards OTT platforms have been extensively using digital marketing practices. The findings reveal that digital marketing practices have a significant influence on consumer engagement, and consumer engagement has an impact on the purchase intention of the OTT platform. The current study emphasizes the mediating role of consumer engagement and brand image in the relationship between DMM practices and OTT platform purchase intention, demonstrating the greater relevance of operating intention having an impact on subscribing Intention. Companies must prioritize their digital marketing strategy to schedule promotions and advertising based on location, demography, and customer preferences to maximize engagement and possibilities. Customer experience and engagement are the most important aspects of a digital media offering. Customers and their engagement on an OTT platform essentially determine the long-term profitability of the participants. To drive engagement, it is important to understand every facet of the customer, from how he or she navigates the platform and what material he or she loves seeing to anticipating what sort of content will appeal to the target audience. To reach customers, businesses are managing DMM and advertising in a more targeted and defined approach. As a result, OTT platforms must continually be on the lookout for new methods to develop and provide more appealing and engaging content that is not accessible elsewhere. The sad difficulty in this situation is that not all OTT platforms have the financial resources to explore new video content development, making it nearly hard for newer and smaller OTT platforms to create and generate new content that caters especially to OTT platforms and devices.

DMM has brought significant change in the consumer uses of a pattern of OTT platforms. The present study investigates the interaction of many factors that influence customer attitudes about OTT platforms and their desire to utilize these services. From a theoretical standpoint, the study contributes to our knowledge of the constructs examined and explains the links between them that have been established in the marketing literature. The current study effort provides a beginning point for context-based theory adaptation in line with the altered situation by evaluating consumers’ media consumption behavior in light of the shift produced by DMM techniques. The study establishes its theoretical usefulness by pointing towards the relevance of addressing the specific factors that exert an influence on consumers’ engagement, building brand image and influencing consumer behavior in the current situation. In addition, an investigation on the potential mediation role of brand image induced by DMM contributes to the existing body of study. On the practical front, the findings show that consumer engagement and brand image have a significant influence on the relationship between DMM and OTT platform purchase intention. To leverage this relationship, service providers must pay close attention to elements that improve engagement and brand image. The study’s findings have several important implications, which are described below.

6.1. Implications for the Theory

The study serves as the foundation for researchers to find crucial characteristics contained in secondary data on OTT platforms, allowing them to bypass the obstacles associated with questionnaire and survey datasets and data gathering. Variables revealed here may be investigated further, particularly as OTT platforms continue to replace conventional marketing, despite various constraints and anxieties. The dynamics of pricing’s impacts on consumer and buy decision-making are not novel in the literature, but it is critical to reexamine how price works to define purchase intention via OTT platforms. It is proposed that OTT platform service providers work on building a brand image among those who are interested in the OTT and its offerings. To do this, an emphasis must be placed on providing original content via DMM and other network marketing platforms in order to engage consumers and establish a favorable brand image. Businesses should consider the specific needs of their consumers while engaging them. A combination of these activities could aid companies in not just keeping their consumers engaged in terms of time spent using the service, but also providing advocacy and continuing visibility to purchase intention.

7. Managerial Implications

It is argued that customers are better engaged by videos (audio-visuals). With the adoption of live streaming, practitioners can leverage this study’s outcomes to the real-time video experience of OTT platform streaming to improve customer engagement towards constructive transactional and nontransactional benefits. It is also an indication that all proxies used in measuring customer engagement demand equal attention in building purchase intention, unlike in traditional commerce, where comments are the focal points of measuring customer engagement. Based on the theoretical explanations provided above, we have offered a set of managerial implications to be integrated into this theoretical framework to assist in guiding effective marketing management practice in the digital media age. We concentrate on how companies may fulfil the social, hedonic, and utilitarian motivations of digital media consumers by focusing on important organizational objectives such as branding and public relations, CRM and sales, and market research facilitation. An integrated typology may be used to show the marketing synergy that can be produced by cross-fertilizing social media customer motives and management approaches. Once a significant degree of purchase intent has been reached, efforts should be made to encourage consumers to subscribe to an OTT platform and automatically consume these streaming services. In conclusion, the study assists service providers in better understanding changes in consumer media consumption patterns and suggests practical approaches to adapting OTT service offerings to reflect these changes.

8. Conclusion

This study examines the impact of DMM on customer engagement and purchase intent via an OTT platform. This paper investigates the impact of this channel on customer purchase intention in the Indian market. The researcher using online questionnaires carried out the study. In conclusion, our presented hypothesis may be confirmed in the Indian market. The findings of this study show that the five independent variables of DMM have a beneficial impact on customer purchasing decisions. Personal privacy and customer brand relationship is the most essential aspect in consumer purchase choice via OTT among the five DMM factors. Furthermore, we can see that consumer engagement mediates the relationship between DMM and consumer-purchasing intention. As a result, a greater focus must be placed on identifying comprehensive methods of increasing customer engagement in order to foster positive purchase intention.

DMM have opened up a window for marketers to identify the consumer cognitions, attitudes, behaviors, and lifestyles. The study presented a paradigm shift in the way customer engagement is seen and how it is measured. India remains one of the countries with the earliest and higher adoption rate for DMM and extensive uses of OTT platform in e-commerce. We are seeing significant growth in a company’s capacity to gather and cross-reference user-generated demographic, psychographic, geodemographic, physiological, and other personal information on its customers as new digital technologies. It is expected that OTT platform and its various application continue as a marketing tool to be introduced in the mutual interest of consumer and marketer. Even though this scenario appears to be a marketing intelligence with an excellent opportunity, there are social risks associated with an information security breach. Future studies on DMM should carefully address risk and trust associated with DMM, how to enhance consumer trust, and build purchase intention in public interest. The goal of digital media marketing is to encourage people to visit your website and then convert those visitors into prospective consumer. That is what web marketing is all about. It has the same set of goals, including establishing and growing brand awareness, building brand image, and influencing consumer-purchasing behavior.

Data Availability

Basic data supporting the study results can be obtained upon request to the corresponding author.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

References

D. Chaffey and F. Ellis-Chadwick, Digital Marketing, Pearson uk, London, UK, 2019.
N. Morris, Understanding Digital Marketing: Marketing Strategies for Engaging the Digital Generation, Springer, Berlin, Germany, 2009.
M. T. P. M. B. Tiago and J. M. C. Veríssimo, “Digital marketing and social media: why bother?” Business Horizons, vol. 57, no. 6, pp. 703–708, 2014.
View at: Publisher Site | Google Scholar
N. Ruparel, A. Dhir, A. Tandon, P. Kaur, and J. U. Islam, “The influence of online professional social media in human resource management: a systematic literature review,” Technology in Society, vol. 63, Article ID 101335, 2020.
View at: Publisher Site | Google Scholar
https://www.businesstoday.in/technology/news/story/indias-video-ott-market-to-hit-125-bn-2030-says-report-301661-2021-07-18.
M. T. Alansari, N. Velikova, and T.-M. C. Jai, “Marketing effectiveness of hotel Twitter accounts: the case of Saudi Arabia,” Journal of Hospitality and Tourism Technology, vol. 9, 2018.
View at: Publisher Site | Google Scholar
D. Kala and D. S. Chaubey, “The effect of eWOM communication on brand image and purchase intention towards lifestyle products in India,” International Journal of Services Economics and Management, vol. 9, no. 2, pp. 143–157, 2018.
View at: Publisher Site | Google Scholar
M. C. Morra, V. Gelosa, F. Ceruti, and A. Mazzucchelli, “Original or counterfeit luxury fashion brands? The effect of social media on purchase intention,” Journal of Global Fashion Marketing, vol. 9, no. 1, pp. 24–39, 2018.
View at: Publisher Site | Google Scholar
I. Stojanovic, L. Andreu, and R. Curras-Perez, “Effects of the intensity of use of social media on brand equity: an empirical study in a tourist destination,” European Journal of Management and Business Economics, vol. 27, 2018.
View at: Google Scholar
P. Wong, D. Lee, and P. M. Ng, “Online search for information about universities: a Hong Kong study,” International Journal of Educational Management, vol. 32, 2018.
View at: Google Scholar
M. Kang and B. Park, “Sustainable corporate social media marketing based on message structural features: firm size plays a significant role as a moderator,” Sustainability, vol. 10, no. 4, p. 1167, 2018.
View at: Publisher Site | Google Scholar
B. Ibrahim and A. Aljarah, “Dataset of relationships among social media marketing activities, brand loyalty, revisit intention. Evidence from the hospitality industry in Northern Cyprus,” Data in Brief, vol. 21, pp. 1823–1828, 2018.
View at: Publisher Site | Google Scholar
T. Veseli-Kurtishi, “Social media as a tool for the sustainability of small and medium businesses in Macedonia,” European Journal of Sustainable Development, vol. 7, p. 262, 2018.
View at: Publisher Site | Google Scholar
S. Habib, N. N. Hamadneh, S. Al wadi, and R. e. Masa’deh, “Computation analysis of brand experience dimensions: Indian online food delivery platforms,” Computers, Materials & Continua, vol. 67, no. 1, pp. 445–462, 2021.
View at: Publisher Site | Google Scholar
S. Zhao and L. Chen, “Exploring residents’ purchase intention of green housings in China: an extended perspective of perceived value,” International Journal of Environmental Research and Public Health, vol. 18, no. 8, p. 4074, 2021.
View at: Publisher Site | Google Scholar
M. Wang, L.-L. Sun, and J.-D. Hou, “How emotional interaction affects purchase intention in social commerce: the role of perceived usefulness and product type,” Psychology Research and Behavior Management, vol. 14, pp. 467–481, 2021.
View at: Publisher Site | Google Scholar
K. Dunakhe and C. Panse, “Impact of digital marketing-a bibliometric review,” International Journal of Innovation Science, 2021.
View at: Google Scholar
H. A. Syrdal and E. Briggs, “Engagement with social media content: a qualitative exploration,” Journal of Marketing Theory and Practice, vol. 26, no. 1-2, pp. 4–22, 2018.
View at: Publisher Site | Google Scholar
R. Aswani, A. K. Kar, P. V. Ilavarasan, and Y. K. Dwivedi, “Search engine marketing is not all gold: insights from Twitter and SEOClerks,” International Journal of Information Management, vol. 38, no. 1, pp. 107–116, 2018.
View at: Publisher Site | Google Scholar
L. D. Hollebeek and K. Macky, “Digital content marketing’s role in fostering consumer engagement, trust, and value: framework, fundamental propositions, and implications,” Journal of Interactive Marketing, vol. 45, pp. 27–41, 2019.
View at: Publisher Site | Google Scholar
J. Järvinen and H. Taiminen, “Harnessing marketing automation for B2B content marketing,” Industrial Marketing Management, vol. 54, pp. 164–175, 2016.
View at: Google Scholar
J. N. Smith, “The social network?: nonprofit constituent engagement through social media,” Journal of Nonprofit & Public Sector Marketing, vol. 30, no. 3, pp. 294–316, 2018.
View at: Publisher Site | Google Scholar
J. U. Islam and Z. Rahman, “Linking customer engagement to trust and word-of-mouth on Facebook brand communities: an empirical study,” Journal of Internet Commerce, vol. 15, no. 1, pp. 40–58, 2016.
View at: Publisher Site | Google Scholar
A. Rasool, F. A. Shah, and J. U. Islam, “Customer engagement in the digital age: a review and research agenda,” Current Opinion in Psychology, vol. 36, pp. 96–100, 2020.
View at: Publisher Site | Google Scholar
H. Kaur, M. Paruthi, J. Islam, and L. D. Hollebeek, “The role of brand community identification and reward on consumer brand engagement and brand loyalty in virtual brand communities,” Telematics and Informatics, vol. 46, Article ID 101321, 2020.
View at: Publisher Site | Google Scholar
J. U. Islam, S. Shahid, A. Rasool, Z. Rahman, I. Khan, and R. A. Rather, “Impact of website attributes on customer engagement in banking: a solicitation of stimulus-organism-response theory,” International Journal of Bank Marketing, vol. 38, 2020.
View at: Publisher Site | Google Scholar
S. D. Vivek, S. E. Beatty, and R. M. Morgan, “Customer engagement: exploring customer relationships beyond purchase,” Journal of Marketing Theory and Practice, vol. 20, no. 2, pp. 122–146, 2012.
View at: Publisher Site | Google Scholar
D. Lee, K. Hosanagar, and H. S. Nair, “Advertising content and consumer engagement on social media: evidence from Facebook,” Management Science, vol. 64, no. 11, pp. 5105–5131, 2018.
View at: Publisher Site | Google Scholar
K.-Y. Lin and H.-P. Lu, “Why people use social networking sites: an empirical study integrating network externalities and motivation theory,” Computers in Human Behavior, vol. 27, no. 3, pp. 1152–1161, 2011.
View at: Publisher Site | Google Scholar
T. Araujo and P. Neijens, “Friend me: which factors influence top global brands participation in social network sites,” Internet research, vol. 22, 2012.
View at: Google Scholar
C. Ruiz-Mafe, J. Marti-Parreno, and S. Sanz-Blas, “Key drivers of consumer loyalty to Facebook fan pages,” Online Information Review, vol. 38, 2014.
View at: Google Scholar
D. A. Aaker, Building Strong Brands, Simon & Schuster, New York, NY, USA, 2012.
K. L. Keller, “Managing the growth tradeoff: challenges and opportunities in luxury branding,” Advances in Luxury Brand Management, Springer, Berlin, Germany, pp. 179–198, 2017.
View at: Publisher Site | Google Scholar
S. Bambauer-Sachse and S. Mangold, “Brand equity dilution through negative online word-of-mouth communication,” Journal of Retailing and Consumer Services, vol. 18, no. 1, pp. 38–45, 2011.
View at: Publisher Site | Google Scholar
D. Langaro, P. Rita, and M. de Fátima Salgueiro, “Do social networking sites contribute for building brands? Evaluating the impact of users’ participation on brand awareness and brand attitude,” Journal of Marketing Communications, vol. 24, no. 2, pp. 146–168, 2018.
View at: Publisher Site | Google Scholar
S. Silvia, “The importance of social media and digital marketing to attract millennials’ behavior as a consumer,” Marketing, vol. 4, 2019.
View at: Publisher Site | Google Scholar
G. Gupta and K. Singharia, “Consumption of OTT media streaming in COVID-19 Lockdown: insights from PLS analysis,” Vision: The Journal of Business Perspective, vol. 25, no. 1, pp. 36–46, 2021.
View at: Publisher Site | Google Scholar
A. Rohm, V. D. Kaltcheva, and G. R. Milne, “A mixed-method approach to examining brand-consumer interactions driven by social media,” The Journal of Research in Indian Medicine, vol. 7, 2013.
View at: Publisher Site | Google Scholar
R. Priya, D. Pias Mondal, and T. Paldon, “Understanding the intentions of students to use OTT platforms,” International Journal of Innovative Research in Technology, vol. 8, pp. 671–677, 2021.
View at: Google Scholar
M. A. Camilleri and L. Falzon, “Understanding motivations to use online streaming services: integrating the technology acceptance model (TAM) and the uses and gratifications theory (UGT),” Spanish Journal of Marketing-ESIC, vol. 25, 2020.
View at: Google Scholar
U. Cebeci, O. Ince, and H. Turkcan, “Understanding the intention to use Netflix: an extended technology acceptance model approach,” International Review of Management and Marketing, vol. 9, no. 6, pp. 152–157, 2019.
View at: Publisher Site | Google Scholar
D. Dasgupta and D. Grover, “Understanding adoption factors of over-the-top video services among millennial consumers,” International Journal of Computer Engineering &Technology, vol. 10, 2019.
View at: Publisher Site | Google Scholar
U. Bokde and S. Seshan, “To study the impact of digital marketing on purchase decision of youth in Nagpur city,” International Journal of Advance Research, Ideas and Innovations in Technology, vol. 5, pp. 105–112, 2019.
View at: Google Scholar
S. Budiman, “The effect of social media on brand image and brand loyalty in generation Y,” The Journal of Asian Finance, Economics and Business, vol. 8, pp. 1339–1347, 2021.
View at: Google Scholar
A. Dhore and S. Godbole, “A descriptive study of the effectiveness of internet advertising on consumer buying behavior in nagpur city,” International Journal of Latest Engineering and Management Research, vol. 3, 2018.
View at: Google Scholar
S. C. e Silva, P. Duarte, J. C. Machado, and C. Martins, “Cause-related marketing in online environment: the role of brand-cause fit, perceived value, and trust,” International Review on Public and Nonprofit Marketing, vol. 17, no. 2, pp. 135–157, 2020.
View at: Publisher Site | Google Scholar
S. Habib, N. N. Hamadneh, and M. A. Khan, “Influence of electronic word of mouth (eWOM) and relationship marketing on brand resonance: a mediation analysis,” Sustainability, vol. 13, no. 12, p. 6833, 2021.
View at: Publisher Site | Google Scholar
K. Höök and J. Löwgren, “Strong concepts: intermediate-level knowledge in interaction design research,” ACM Transactions on Computer-Human Interaction, vol. 19, pp. 1–18, 2012.
View at: Google Scholar
S. Albers, “PLS and success factor studies in marketing,” Handbook of Partial Least Squares, Springer, Berlin, Germany, pp. 409–425, 2010.
View at: Publisher Site | Google Scholar
J. F. Hair, J. J. Risher, M. Sarstedt, and C. M. Ringle, “When to use and how to report the results of pls-sem,” European business review, vol. 31, 2019.
View at: Google Scholar
R. Johnston, K. Jones, and D. Manley, “Confounding and collinearity in regression analysis: a cautionary tale and an alternative procedure, illustrated by studies of British voting behaviour,” Quality and Quantity, vol. 52, no. 4, pp. 1957–1976, 2018.
View at: Publisher Site | Google Scholar
M. Turanlı and M. Yolsal, “An empirical research on human resource practices affecting innovative work behavior,” Balkan and Near Eastern Journal of Social Sciences, vol. 6, 2020.
View at: Google Scholar
U. Dholakia and R. P. Bagozzi, “Consumer behavior in digital environments,” Digital Marketing: Global Strategies from the World's Leading Experts, John Wiley & Sons, NJ, USA, pp. 163–200, 2001.
View at: Google Scholar

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Copyright © 2022 Sufyan Habib et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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