1. Introduction

In the digital era, the social media platform has redefined the norms for how brands engage with consumers by presenting new possibilities for communication and persuasion. One of these platforms, YouTube, has been identified as the most potential means to achieve this goal because of its inherent visual and narrative capabilities that enchant and captivate the global audience [1,2]. The killer role of digital media is gradually increasing and becoming a shaping factor for consumer opinion. This tightens the need for brands and buying people to understand which methods brand owners use to connect with consumers through social media.

With cutting-edge digital advertising techniques, the US brand Niandurite, an international brand with cutting-edge products and cutting-edge athletic gear, has been able to enhance its brand identity and become closer to a wider range of consumers. Nike is claimed to create advertisements showing masterly storytelling based on pictures. It is the harmonious blend of these two factors that drags the audience into the story world and grabs their emotions [3]. Nike's campaign, A Feel For Every You, is not an exception; instead, it could be named as the prime sample of this type of marketing that is about emotional connection with consumers and customized fitness training.

Nike has anchored its marketing on the concept of personalized advertising, which means making suitable content that conforms to the characteristics of the person or people and that conforms with the preferences and self-concepts of the individuals [4]. This concept is bolstered by volumes of research showing that personalization can deliver a noteworthy return on investment by increasing engagement and retention because the messages become more relevant and meaningful to the audience [5,6]. Personalized marketing seeks to utilize data-driven intelligence to deliver bespoke content that corresponds to the peculiarities of the individual buyer and harbours a propensity for the audience's consumption and brand association.

'A Feel For Every You' promotes this personalized highlight by creating different varieties of fitness experiences while, at the same time, it deals with an inclusive narrative, which appeals to a wider audience. Mood raiser Keenly International's ad campaign on body positivity and self-empowerment depicts a new phenomenon in advertising: breaking barriers of beauty stereotypes and embracing every part of society in the process [7]. Nike challenges the existing notion of beauty and prioritizes individuality by creating a more engaging message, which will finally cater to the audience's wishes.

Having identified a potential strategy that aligns with the contemporary values of awareness and audience engagement, questions still need to be answered about how the intellectual ideas of 'grit' and 'human' affect the viewers' reactions and discussions on YouTube. Analysing YouTube comments provides a decisive moment to capture consumers' perspectives on how they deal with and perceive adverts, offering an uncompromising view of the influence of digital media on consumer attitudes and perceptions [8]. Previous studies on user-generated content, like online reviews and comments, brought to the fore the indispensable nature of this kind of content in branding and its influence on consumer decision-making [9].

This paper is developed to examine Nike's brand 'A Feel For Every You' campaign for body image and fitness-related perceptions based on the collected YouTube audience views. This focuses on recognizing the commonalities and differences found in the comments of the audience in order to derive a more detailed and comprehensive view of how the portrayal of body image and fitness in the campaign resonates with its audience [10]. Through the assessment of language and the emotional tone expressed in comments, it will provide a deeper understanding of the public's opinion of the advertisement and the message they are meant to convey.

These aims will use a mixed-methods approach comprising the thematic analysis and sentiment analysis methodologies. Sentiment analysis will be employed to establish the emotional mood of viewer comments so that general sentiment trends can be traced and correlates between those trends and the campaign's themes can be determined [11]. The thematic analysis will also support the study by pointing out the predominant ideas and similarities in the content of the comments, thereby providing a detailed outlook on how viewers feel about the various crucial aspects of the campaign [12]. This will include a complete consideration of the whole campaign, giving a broader perspective on how it influences consumers' attitudes and perceptions.

In addition to research contributions to the academic and market practice of digital marketing and the psychology of customers engaging in the advocated digital media advertising, this study is also practically relevant to Nike and other players using the same advertising methods. The knowledge gained after performing sentiment analyses of customer reviews can be integrated into brands` marketing strategies. This will be of great importance as brands will be able to adjust their strategies to align with customer expectations, thus increasing the effectiveness of their campaigns [13,14]. The issue of advertising's power to shape body perceptions is highly relevant for advocating the use of media that communicate body acceptance and positive influence on self-esteem through media [14,15].

In the final analysis, our research will be used to strengthen our comprehension of how the integration of advertising theory can be a propellant of consumers' buying behaviour. By scrutinizing the YouTube feedback, the analysis will offer an eye-catching and in-depth view of the efficacy of personalized marketing strategies amid changing consumer outlooks. The outcomes will contribute to forming an elaborate framework that will provide us with information regarding the contribution of social media to brand-related perceptions and equip us with development recommendations. This research will expand our understanding of the more focused marketing approach used in the digital era and its interaction with customer feedback to gain insightful information.

2. Methodology

This study aims to evaluate the effectiveness of the Nike: A Feel For Every You video advertisement. By analyzing the feedback from viewers in the video comments after the ad was released, this study reveals the effectiveness of this ad in terms of emotional resonance, brand awareness, and consumer intention. Generally speaking, the effectiveness of an ad usually includes several dimensions, such as the audience's emotional response, the accuracy of the ad message, the increase in brand awareness, and the conversion effect of the ad on consumer behaviour. In order to comprehensively evaluate these effects, this study adopted a multi-method research design.

This study is designed as a mixed method study, including quantitative and qualitative analysis. The choice of mixed methods helps to reveal the complex effects of advertising fully. On the one hand, quantitative methods (such as sentiment analysis) can be used to perform statistical evaluations on large-scale data sets to understand the overall impact of the ad. On the other hand, qualitative methods (such as topic analysis and sentiment resonance analysis) can dig deeper into the potential meanings in the comments, reveal whether the ad has achieved its original design intention, and identify the audience's potential emotional reactions and attitudes.

Through sentiment analysis, understand the audience's emotional response to the ad. This helps determine whether the ad successfully inspires positive emotions in the audience, such as joy, emotion or excitement, or whether it triggers negative emotions, such as disgust and aversion. Analyzing the number and manner of mentions of brands, products or services in comments evaluates whether the ad effectively improves brand awareness. Whether the ad clearly conveys the core value of the brand and whether it helps the brand establish a positive image in the minds of the audience will be evaluated in this section. By identifying keywords and expressions in the comments that involve purchase behaviour or purchase intention, it is evaluated whether the ad successfully influences the audience's willingness to buy. This indicator will be combined with emotional response and brand awareness to evaluate the commercial effectiveness of the ad comprehensively.

2.1. Data collection

This study intends to collect data from multiple social media and video platforms, including YouTube, Facebook, Instagram, TikTok, etc. Advertising video comments are the main data source for the study because these platforms allow users to express personal opinions and feedback directly on advertising content. These comments often directly reflect the first-hand emotions and attitudes of the advertising audience. However, due to ethical issues of authority and privacy, this work will focus on videos on YouTube. At the same time, it should be noted that this study only collected data with English as the main language for analysis, and other related languages were not included in the analysis. In order to ensure the representativeness and diversity of the data, this study collected all 244 advertising comments under the Nike: A Feel For Every You advertising video. The time span of the data will start from the first day after the advertisement is released and continue to be collected for one year. This time span helps to capture the audience's initial reaction and the long-term impact that the advertisement may have in the subsequent time.

After the data collection is completed, the study will clean and filter the original comment data. Data cleaning includes removing irrelevant information such as advertisements, spam comments, non-target language comments, and duplicate content to ensure the validity and reliability of the data analysis results. In addition, the study will focus on analyzing comments that contain emotional expressions or opinions rather than just simple likes or single-word comments (such as "good", "great", etc.) to ensure the depth and quality of the research results.

2.2. Quantitative and qualitative research methods

The quantitative research will focus on sentiment analysis and the calculation of sentiment polarity scores. To achieve this goal, this study will use natural language processing technology (NLP) to automatically classify and score the sentiment of comments. Before sentiment analysis, the comment text will be standardized. This includes text cleaning (removing punctuation, emoticons, and irrelevant characters), stemming, part-of-speech tagging, and vocabulary standardization. The processed text will be more suitable for analysis by machine learning algorithms and reduce noise interference. In order to supplement the shortcomings of quantitative analysis, this study will also conduct a qualitative analysis of the specific content in the comments to explore the audience's emotions, thoughts, and attitudes in depth. Qualitative analysis will focus on content analysis and thematic analysis. Content analysis will focus on key expressions and emotional language in the comments to analyze the audience's specific reactions to the advertisement. For example, if the advertisement conveys information through humour, the study will evaluate whether the audience agrees with the humour of the advertisement and whether this emotion resonates. In addition, the narrative language in the comments will be classified into different emotional response types, such as humour, touching, anger, etc. The study will identify the most common themes in the comments. This helps to reveal the content and information of the advertisement that the audience pays attention to. For example, some viewers may focus on the music, visual effects, or storyline of the advertisement, while other viewers may pay more attention to the brand information conveyed by the advertisement. Thematic analysis can help researchers identify the core message conveyed by the advertisement and determine whether the advertisement successfully achieves its designed purpose. The quantitative and qualitative results will be combined to assess the advertising effectiveness comprehensively. For example, suppose the sentiment analysis results show a large number of positive emotions, and the qualitative analysis reveals that the audience has a positive reaction to the content and brand communication of the advertisement. In that case, the advertisement is successful in terms of emotion and brand perception. If negative emotions are dominant, the qualitative analysis will help reveal the reasons, such as misunderstanding or controversy of the advertisement's content. By combining the two analysis methods, the research will be able to provide a more comprehensive evaluation of advertising effectiveness.

3. Machine Driven Classification of Open-ended Responses (MDCOR)

MDCOR (Machine Driven Classification of Open-ended Responses) is an analysis tool specifically designed for processing open-ended text data. It is free software that does not require programming and is designed to classify text data in surveys and social media, especially for processing vertical and horizontal text responses. The main purpose of MDCOR is to automatically and systematically classify and encode text responses to open-ended questions, thereby improving the efficiency and accuracy of data processing.

MDCOR uses natural language processing (NLP) technology and combines machine learning models for text classification and sentiment analysis. Through its unique algorithmic framework, MDCOR can identify and organize complex text patterns and reconstruct contextual meaning, avoiding aggregation bias that may occur in traditional analysis. This approach helps reveal participants' true intentions and emotions, thereby providing researchers with more accurate and in-depth insights. In this study, I will use MDCOR as an analysis tool to obtain results.

The initial text mining output (see Figure 1) shows that the number of valid open responses in this data collection is 234. After screening, the number of documents used for analysis is 220, containing 469 independent terms. The data is 99% sparse, meaning most responses contain only a few terms (perhaps just a few words). The most common words were obtained after text mining and eliminating some possible invalid information. The high frequency of words such as "good", "much", and "amaze" may reflect the audience's optimism.

Figure 1: Initial text mining output

After initially screening out the keyword terms, the result obtained a set of model-fitting results under different indicators (see Figure 2), where the horizontal axis is the "number of topics", and the vertical axis is the score of each indicator. The figure shows the evaluation results under multiple different numbers of topics. As the number of topics increases, the score trends of different indicators change significantly. This shows that the performance of the model is different under different numbers of topics. In the work, it is able to find that Griffiths2004's score tends to be stable as the number of topics increases; CaoJuan2009 has apparent fluctuations in the first few topics, then drops rapidly and stabilizes; Arun2010's score continues to drop as the number of topics increases, showing significant changes, while Deveaud2014's change is relatively small and relatively stable, indicating that this indicator is not sensitive to changes in the number of topics.

Figure 2: Model fitting results under different indicators

Intertopic Distance Map (see Figures 3, 4, 5, and 6) shows the relative distances between different topics through multidimensional scaling (MDS). The different circles in the figure represent different topics, and the circle's size indicates the topic's marginal distribution (the distribution ratio of the marginal topic). Figure 3 shows four main topics, among which Topic 1 (red) is relatively far away from other topics, indicating that it may contain unique words and concepts. The distances between other topics (blue) are relatively close, indicating some connection between them.

Figure 3: Intertopic distance map of Topic 1

Keywords in Topic 1, such as "commercial", "diversity", "make", "love", "legal", etc., indicate that this topic is closely related to advertising content, legal issues, and diversity topics. High-frequency words such as "commercial" and "diversity" may imply that the commenters discussed commercial elements and diversity issues in advertising.

High-frequency words in Topic 2, such as "thch", "thng", "muito", "excelente", etc. These words seem to contain some non-English words, such as "muito" and "excelente", which may reflect that there are more multilingual discussions in the comments. In addition, the words "beautiful", "life", "advert", and so on also reflect the content related to emotions such as life and beauty in the advertisement. This kind of discussion may reflect the visual beauty of the advertisement, the emotional appeal and the overall impression of the advertising effect on the audience. At the same time, the linguistic diversity of this topic is noteworthy, which may reflect the multilingual influence of the advertisement in the international market.

Figure 4: Intertopic distance map of Topic 2

Keywords in Topic 3 include "Nike", "woman", "song", "Lisbon", "confession", "legging", and so on. These keywords reveal that this topic is related to brands (such as Nike), gender topics (woman), music, fashion (legging) and geographical locations (Lisbon). This shows that this topic mainly focuses on the brand impact, female consumers, musical elements and geographical cultural influences in the advertisement. This shows that the advertisement may significantly impact specific consumer groups (such as women) and enhance the brand's memory point through means such as music and fashion.

Figure 5: Intertopic distance map of Topic 3

Finally, the keywords of Topic 4 include "good", "amaze", "video", "wonder", "thch", "hope", "product", etc., which shows that this topic may be related to the visual effects of the advertisement and the emotional response of the audience. Words such as "amaze", "wonder", and "good" suggest that the audience's overall feelings about the advertisement are positive, and the product quality and effect of the advertisement may also be the focus of discussion. This theme reveals the advertisement's effectiveness on the emotional level, especially its ability to successfully arouse the audience's emotional resonance and generate positive evaluations. This theme provides positive feedback for the overall effectiveness of the advertisement, indicating that the advertisement may be very successful in terms of visuals and product presentation.

Figure 6: Intertopic distance map of Topic 4

Based on the analysis of the above four themes, we can summarize the following points:

1. Brand influence of the advertisement (Theme 3): Brands such as Nike occupy an essential position in the comments, especially in combination with female consumers and fashion elements.

2. Diversity of the advertisement (Themes 1 and 2): The comments discuss legal, diversity, and cultural elements, indicating that the advertisement may have aroused the audience's attention in these aspects.

3. Visual and emotional effects of the advertisement (Theme 4): The advertisement successfully aroused positive emotional reactions from the audience and received high evaluations, especially regarding visual effects and product presentation.

These analyses can help you further evaluate the specific effectiveness of the advertisement and adjust future advertising strategies based on feedback from different themes.

4. Conclusion

The conclusions drawn from this research provide some crucial information about how Nike's "A Feel For Every You" approach is performed in practice on media channels and from the perspective of consumer sentiment regarding brand awareness and purchase intent, manifested through YouTube comments. The combination of quantitative sentiment analysis and qualitative thematic analysis offered the research question, "What impact do Nike's customized ads bring by their audience questioning how they see the ads and if that can change audience perception or behaviour?" The sentiment analysis thus reveals a positive emotional response to the campaign as the overall fluorescence ted towards upbeat feelings. The mass demographic of the comments suggested feelings of inspiration, empowerment, and recognition for the message of inclusivity. This is consistent with previous results and shows that advertising that targets specific groups and elicits certain emotional responses is more successful. Among these emotions, the majority expressed their thoughts of empowerment and self-consciousness. One is to celebrate being your own beautiful. Consequently, all the persons giving their views regarding the advertisement commented that the message must be shared as it may not be easy to accept the way one is. Nevertheless, the sentiment analysis had its downsides in pointing out that a small percentage of comments involved people who wondered why Nike was making such a campaign and criticized the attire. This difference in sentiment again indicates the extent to which the features of the video determine the audience's emotional state. Although the viewers were mostly impressed by the video's content, they still had certain reservations. Such scepticism can often emanate from the tones of brand messaging not being consistent, hence not helping the message to be disseminated effectively. The qualitative analysis helped further brainstorm how the marketing campaign influenced brand perception. Moreover, the thematic analysis discovered that most viewers frequently commented on Nike being a brand that stands for certain values, particularly those associated with inclusivity and empowerment. Numerous remarks showed the harmonization of the promo message with the brand's overall identity and reflected the institution's stand among diversity and self-expression champions. In this respect, this work revisits the existing literature that shows that personalized advertising is an effective tool that produces brand loyalty by matching key communication messages with the values and self-concepts of consumers. Further, this work can argue that it is a targeted solution that helps get the brand closer to the various consumer segments within the market. Additionally, this work found that the advertising drove brand awareness to the previously unfamiliar group of people fixating on Nike and Body Positivity. "Smiles of commendation" were the norms of the comments generated by this audience, who were mutual in their regard for the brand. They often expressed admiration and respect towards the brand. As a result, this can be evidence that the campaign was perceived as effective since it managed to grab the attention of many people. This outcome further implies that niche advertising that appeals to consumers in unique and often emotional ways can extend the boundary of a particular brand and attract more clients. Furthermore, consumer intention was explored in this research, particularly consumer purchase behaviour. Evaluation of comments made by the viewers indicated a high degree of engagement and level of involvement. Some expressed that their feelings about purchasing were greatly influenced upon watching the advertisement. Such viewers were rarely shy about expressing the same factor about their decision-making process, especially regarding the value consensus between the campaign and themselves. This agrees with the general analysis of personalized marketing, which contends that consumption behaviours can be shaped through advertisements with an individual connection on both emotional and personal levels. Nonetheless, it should be made evident that while the commercial did make some purchase intentions positive for some of the racers, others of this same group retained scepticism increase caused by the commercialization of social issues. This presents brands willing to jump on the bandwagon as a potential danger; they might succeed at building brand loyalty and influencing buying behaviour but, at the same time, risk negative feedback for promoting a genuine social cause. Results of outstanding signification should be highlighted since they bring out new comprehensions of the effectiveness of personalization advertising in the advanced digital era. The findings state that similar to the "A Feel For Every You" campaign, advertising initiatives can effectively draw upon emotions and brand ideals to make audience responses that will ultimately impact brand sales and promotion. On the other hand, they push further the point that there is the quest for genuine brand communication, which is associated with any brand inconsistency, as it will deter from the campaigns. This study suggests a different way to assess the attribute, such as using mixed methods to assess the effectiveness of advertisements. While sentiment and thematic analysis could grab general emotion trends from viewer reception and the specific themes that have affected them, they also added synchronicity to the study. Thus, this careful methodology can be utilized in future research on consumer behaviour with digital advertising. The "A Feel For Every You" campaign proves that advertising leads in marketing in this digital age. The company addressed the issues of an all-encircling community and emotional influence. At the same time, it resonated with a different class and reinforced its symbol value. In the study, the respondents had a positive emotional response, which increased brand awareness, and finally, their behaviour changed since they were using personalized and empathetic promotion. The result can be convinced about the role of emotionally resonant advertising when it comes to being effective for companies. Here, it is necessary to highlight that the study warns against the outcomes of the perceived insincerity that calls for the companies to maintain the elevation of consistency and originality in the message. There is added value to the theory of digital marketing strategies, and it is also relevant theoretically for companies looking to use these strategies to woo customers in the marketplace.