Influence and Relationship between Branded Content and the Social Media Consumer Interactions of the Luxury Fashion Brand Manolo Blahnik

Abstract

Social networks are particularly significant in marketing and advertising because they provide platforms that offer interactive network channels to develop consumer brands. Among the most useful platforms of this type for capturing leads for businesses of the business to customer are Facebook^®. In this sense, this research aims to analyze the degree of influence and relationship between Branded Content and the social media consumer interactions of the luxury fashion firm Manolo Blahnik in the mentioned network. This analysis allows us to see what type of content is more effective in social networks. To do this, an exploratory study was implemented with a review of the literature, followed by a correlation study, with hypothesis set to be contrasted through ANOVA analysis with SPSS software. The conclusion is that social networks facilitate interaction between brands and their followers, allowing the content and messages disseminated to achieve greater impact and commitment to the public and, therefore, increase the engagement between the brand and followers.

1. Introduction

The fashion industry, formed around large business groups and different commercial brands, is applying a logic typical of the network company to operate on a global scale and distribute its products throughout the planet [1]. Only one of the big commercial brands can produce as many models as all the haute couture houses in Paris in the ’50 s [2].

From a business point of view, the fashion industry constitutes an activity with significant weight in a country’s economy. Its structure is made up of all those companies that are dedicated to or collaborate in the creation of “fashion products”, which includes firms specialized in haute couture, ready-to-wear, or “early fashion”, and those that contribute directly or indirectly to the elaboration of the fashion product [3].

The purpose of this research was established to analyze to what extent the brand content disseminated in social networks is related to the interactions of the followers of luxury brands in the textile sector; specifically, we analyze the degree of influence between Branded Content and social media consumer’s interactions with the luxury fashion firm Manolo Blahnik. An exploratory study was implemented with a literature review, followed by a correlational study, with hypotheses to be contrasted utilizing ANOVA analysis with the SPSS software. One of the main original contributions of this work is that it contributes to the literature and guides community managers in relation to what type of content is more effective in social networks in the context of luxury fashion.

1.1. Social Media and Fashion Marketing

The advent of Web 2.0 and the development of ICTs have changed the way organizations communicate with their audiences [4], finding in social networks the ideal platforms to expand relationships beyond physical contact and install, or offer the possibility of doing so, other types of applications to attract and retain users [5]. Thanks to them, communication is now direct, two-way, and in real time. In this sense, social networks have become a communication channel that makes possible dialog, cooperation, and content creation. Consumers 2.0 do not usually go to the corporate site when they want to obtain information about a product. They aspire to find that information on their Facebook timeline without having to do an exhaustive search. This demands a continuous presence and interaction in networks by the brand almost individually. In this way, actively listening to the client is a factor that must be considered by brands, incredibly fashionable ones, to know their target audience and create personalized campaigns that manage to call their attention above that of the competition [6].

The fashion sector has changed its ways of accessing an increasingly massive, complex, and demanding public. As a social interpretation system and as a relevant economic sector for our community, it has been transformed and grown in a general way. The processes of analysis, projection, production, distribution, and consumption have changed due to the consolidation of this new global and connected context [7].

The increase in brand awareness and customer engagement is a direct and undeniable consequence of social media use. It is for this reason that companies are focusing their efforts on social media marketing strategies. The research results using Facebook [8] to observe the impact of user-generated social media communication on brand value, brand attitude, and purchase intent show that although company-generated content does not appear to influence consumer perceptions of brand value directly, it does affect consumer attitudes towards the brand. Company-generated social media content can create a viral response that helps spread original advertising to a broader audience. Ideally, consumers should be attracted or encouraged to generate content that reflects support for their company’s brands and products. Instagram^®, on the other hand, is a social network that has become a place to showcase and share the brand ideal, as well as to present beautiful product images [9].

Without neglecting traditional formats, fashion companies activate and reinforce an alliance with the protagonists of digital platforms while recognizing the need to offer a quick response and a credible image that captures the user’s confidence and potential customer. Now consumers are looking for people and institutions they can genuinely trust. Brands and companies have understood this and have become social actors in the networks and looking for connectors or people who can effectively expand their message, generating trust among their peers [10].

By 2015, 84% of the brands were planning to carry out a campaign involving influencers. It has been shown that it is well implemented within the range of communication and marketing professionals’ tactics. Influencer engagement is considered a handy tool for increasing brand awareness and, to a lesser extent, generating commercial opportunities and building customer loyalty. 75% think relationships with these figures to be useful or very effective in creating commercial opportunities and supporting sales, and 76% believe that they are effective in customer loyalty strategies. Branded content distribution is the preferred scenario for brands to interact with influencers (67%). Twitter^® was confirmed as the main channel for influencing engagement campaigns with 68% in terms of networks, followed by blogs with 54% and then Facebook with 51% [11]. These data indicate that many brands and agencies have become more adept at aligning influencer marketing strategies with their business strategy.

Fashion not only implies a search for personal beauty, but it is also linked to a desire to experiment with pleasure in which various sensory aspects are combined. Perceived hedonism has been shown to affect satisfaction, intention to interact, and actual interaction in a brand’s Instagram^® account. On the other hand, perceived originality is the most relevant content characteristic to develop perceived hedonism, which gives significant hedonism value to create a satisfying experience [12]. Desire is the most critical driver of consumer engagement; subjective well-being (SWB) acts as a result of consumer responsibility. Experience plays an essential role in the relationship between concentration and SWB [13]. It is considered that luxury must be something that the client must have earned because the more difficult the access to a piece is, the more desirable it is for the consumer. The most used marketing strategies in luxury fashion to increase customers’ Desire and make their purchase difficult are increasing the price of the product, limited production, and waiting for delivery times [14].

1.2. Research on Fashion Marketing and Social Networks

Digitalization and marketing have played a strategic role in the fashion sector [15] as well as the evolution of marketing, moving from product-based marketing (1.0) to consumer-centric marketing (2.0) to human-centered marketing (3.0) in which people are actively involved [16]. This industry’s worldwide circulation is produced and increased thanks to the emergence of the new information and global economy. The diffusion of this sector does not occur as a force or an abstract idea. Instead, it materializes through different agents’ actions, configuring itself according to a permanent interaction between them. Consequently, fashion results from a series of interconnected practices: market and economic, technological developments, and a series of more artistic techniques, such as marketing and design. Nowadays, images, articles, and styles are created and disseminated worldwide with speed previously unthinkable, being favored by international trade, information, communication technologies (ICT), international media, and global migration [1]. In this sense, the fashion industry has developed its form of communication which is crucial in understanding its commercialization [17]. Given this reality, researchers and professionals in the industrial sector have focused on developing studies that can offer relevant contributions, whose scope favors and guides the fashion marketing sector’s development.

The analysis carried out by Gürhan-Canli, Sarıal-Abi and Hayran was descriptive [18]. In the literature systematization, two fundamental research perspectives on fashion marketing were identified: the global-local brand and the influence of culture on consumer interactions. It was found that research on global and local brands is influenced by cross-cultural research. The review results showed that the literature was mainly condensed in information processing, “self” and identity, consumer culture theory, and psycholinguistics to investigate the relationship between culture, brands, and consumers.

Evaluating users’ emotional responses has become a crucial task in product design for the fashion industry. Several researchers have dedicated themselves to studying techniques for assessing and defining the best methodologies for designing and marketing fashion products. Luxury represents many consumers’ aspirations [17], so luxury brands are reinventing their marketing and business strategies to adapt and face the emerging markets eager to consume luxury fashion. They position digital marketing as an essential tool for communicating the leading luxury brands in the market with younger audiences [14]. Under this perspective, Gonzalez-Romo and Plaza-Romero carried out research focused on identifying the current digital marketing strategies applied by the brands in the luxury fashion sector and knowing the most significant aspects of the brands’ communication with their target audiences (stakeholders) in the virtual scenario. To achieve their objectives, they resorted to qualitative techniques, such as content analysis and in-depth interviews. This study showed that, among others, storytelling is one of the critical strategies in digital marketing. This format can be found in video strategies, social media, events, and exhibitions open to the public, searching for interaction with the public and showing its history.

The research implications extend to both the theory and practice of luxury fashion marketing in social media. The study presents a new perspective on the dynamics of business-to-consumer co-creation. It exhibits the application of a novel methodology for the “visual” analysis of luxury by facilitating the understanding of the meanings of images in the consumer (perceptions). In terms of practice and management, it yields new knowledge about user-generated content in social network marketing, especially related to product interaction.

The digital environments currently articulate new possibilities of a dialog in which advertising has a challenge and amplifies their messages to settings, even outside the so-called target [19]. As it happens with business organizations, as communication technologies have been evolving and prospering, social media has become an integral part of fashion consumers. The effect of social media on their interaction through digital platforms is not limited only to creating a “new paradigm” for buying fashion. It also aims to boost fashion marketing, including customer service, the vicarious experience, and the option of creative advertising and new business opportunities [20].

Despite the current interest in determining and understanding the relationships between social media and consumer behavior, few academic works focus on the fashion sector and the specific marketing strategy perspectives within this field, so some topics require further research [21]. “In the new marketing scenario, translating the conventional brand strategy to the digital environment is not enough” [22] (p. 12). It is necessary to identify the critical success factors of the social media strategy and how it affects organizational performance. To clarify these issues, Wu, Guaita-Martinez, and Martin–Martin developed a study that provides a comprehensive research framework for social media, environment, marketing strategy, and performance [23]. After analyzing 207 Taiwanese brands, the results confirmed that social media strategy is positively affected by an organization’s business, market, and innovation orientation. According to these authors, these findings suggest that fashion brands should focus on identifying opportunities, taking risks, producing proactive innovations, applying creativity, and developing new versions of their products.

A social network marketing strategy creates two-way communication (P2P) between organizations and current or potential consumers to improve customer relationship management (CRM). Consequently, the social media strategy provides brand visibility and supports market research. Companies have the opportunity to conduct market research, communicate with their customers, and collect feedback from them [23].

Social networks are particularly significant in marketing and advertising because of platforms that offer interactive network channels for the development of consumer brands. The most useful platforms of this type for capturing leads for business to customer (B2C) businesses are Facebook and Twitter since they share content in a non-intrusive way with advertising campaigns that provide information and content of interest to the user [24].

In this sense, Azar, Machado, and Vacas-deCarvalho point out that, although social media has been the focus of a progressive number of studies, there is still a need for empirical research on the interactions between consumers and brands on Facebook, especially about consumer motivations, to attract brands to social networks [25]. To that end, they conducted research that could provide brand managers with additional information on how to adapt their approaches and strategies to increase consumer interactions with brands on Facebook. The study, which included a convenience sample of 160 users, was based on the application of Katz’s gratification theory. The intention was to develop a new typology of consumers based on consumers’ motivations for interacting with brands in this network (social influence, information seeking, entertainment, trust, and reward), determining these interactions’ type and intensity. The new categorization created and exposed covers four different groups of consumers defined as the “independent brand”, the “brand profiteers”, the “brand partners,” and the “brand dependents”. This new classification provides brand managers with information to develop more effective strategies according to the consumer groups they are interested in.

De-Silva, to facilitate a framework for building relationships through customer participation in Facebook-branded pages (FBP), researched with a sample of 327 university users in Sri Lanka [26], whose results pointed to the finding that customer motivations positively influence customer engagement with FBP in terms of information, remuneration, social interaction and personal identity in clothing/fashion FBPs, but not about entertainment. Additionally, it was observed that customer engagement appears to be positively related to trust and commitment to the PBF.

The results of a study carried out by Klavech confirmed that there is a significant relationship between social influence and purchase intent. It also showed that the quality of electronic service, social impact, and electronic word of mouth (or) have a significant positive relationship with purchase intent. The substantial factor influencing purchase intent is the quality of the electronic service [27].

However, it is essential to note that research on customer opinions and tastes on Facebook still does not clarify the relevance of its role in different sectors. For example, customer reviews seem to be of great significance for technology products, but generalizing this to apparel and fashion is complex. Indeed, in the fashion industry, the question remains about how consumers build their exposure experience and social media interactions [28].

This reality has led to the imminent need to open up research spaces that allow the complex dynamics of the relationship between consumers and brands to be revealed. To this end, Bonilla, del-Olmo-Arriaga, and Andreu analyzed the interactions between fashion brands and their followers on social networks, focusing on empirically determining the relationship established between the fast-fashion company H&M and its users on the social network Instagram [29]. After the content analysis, whose purpose was to determine the commitment from the point of view of the message content, the company’s communication strategy, the formal aspects, and the category of products presented in the post, the results helped to clarify those aspects of H&M’s Instagram messages that generate a more significant number of interactions with users and those aspects that positively or negatively affect responses through comments and likes, having identified which attributes of the posts generate greater or lesser business of each of the three theoretical models for selecting them. Similarly, we determined those variables that generate asymmetric responses in comments and likes, which because of the variable degree of engagement they imply, pave the way for evaluating whether these differential impacts can be exploited to reformulate the digital communication strategies of the brands. From a practical point of view, this study helps managers of fast fashion brands make marketing decisions based on the evaluation of brand engagement and the understanding of social media activity’s impact to increase brand image and drive consumers to buy.

It is indisputable that the most recent research regarding marketing and communications is currently focused on the digital space, whose accelerated growth and innovation provide new interactivity options for consumers and businesses. Technology, including artificial intelligence (AI), predictive learning, and augmented reality, seems to define the paths marketing and advertising professionals must travel [30]. Specifically, in the field of fashion, in the analysis of trends in the sector made by Del Olmo, Paricio, and Sanchez (cited by Frutos-Torres), they highlight, in particular, the transformation that the Internet has represented for the fashion industry, both for the transactions that are made through this channel, as well as for the significant role it has played in the dissemination of products [17]. These authors share the concept that big data has become a fundamental element in the management of communication because of the property of easily converting data into information which helps to understand audiences’ profile, needs, and feelings and facilitates decision-making.

In this context, four hypotheses are put forward: The brand content influences the share (H1); brand content influences comments (H2); brand content influences the feelings of the follower towards the brand (H3); and brand content influences the positive and negative reactions of the brand follower (H4).

2. Materials and Methods

This research’s main objective is to analyze to what extent there is a relationship between the Branded Content disclosed in social networks and the interactions of the followers of luxury brands in the textile sector. The textile and clothing sector represents a well-established and significant industry as it exerts a dynamic impulse on the economy [31]. Specifically, we analyze the degree of influence between Branded Content in the most popular social networks and the social media consumer’s interactions with the luxury fashion firm Manolo Blahnik.

The social network analyzed in this study is Facebook because, in addition to being the most popular social network, it corresponds to a greater extent to the company’s current target, while Instagram—despite having a growing trend in popularity in recent times—corresponds to a greater extent to a potential target as it is habitually used by a younger audience than Facebook users [32]. Likewise, the process of adopting luxury products is more likely to occur in a more mature target as they have greater job stability and purchasing power than among a younger target in general.

This analysis allows us to see which type of content is more effective in social networks since it provokes more reactions from followers who, in turn, can be current or potential consumers of the brand.

The brand content variable was categorized into commercial, industrial, and corporate social responsibility. The following variables were considered for social media consumer interactions: share, comments (negative, neutral and positive), brand feelings (like, love, care, haha, wow, sad, angry), and reactions (negative and positive).

For this purpose, an exploratory study was implemented with a literature review, followed by a correlational study, with hypotheses to be contrasted utilizing ANOVA analysis with the SPSS software.

Primary data were collected from the Branded Content of each of the messages posted on the Facebook social network of the luxury fashion brand Manolo Blahnik during the quarter (March, April, and May) of 2020, coinciding with the first wave of the global pandemic caused by the COVID-19 as well as measuring each of the interactions that have caused each message in the followers of that brand in the same period.

One of this work’s original contributions is that the luxury fashion brand Manolo Blahnik was selected due to its brand awareness being an essential icon among luxury fashion brands, so the most popular influencers consume it. Likewise, it is one of the luxury brands chosen by the film industry as the case of the serial “Sex and the City,” where it is shown as a successful branded entertainment [33]. This brand currently has more than 300 stores worldwide, including 20 flagship stores in key cities such as New York, Hong Kong, Madrid, and Geneva. The firm has more than 328,000 followers on Facebook and more than 3,325,000 followers on Instagram.

3. Results

ANOVA analysis allows us to examine the variance within a data set to determine significant differences between the mean values of a dependent variable [34]. For this work, the dependent variables to be contrasted are each of the consumer interactions.

It is especially suitable for research that analyses behavior in a digital information context. In this way, it is analyzed the effect that each of the categories of the independent categorical variable brand content has on the dependent variable, consumer interactions [35].

In each of the following subsections, we analyze the Branded Content influences in the various possible interactions in social networks.

3.1. Analysis of the Relationship between the Brand Content and the Interaction in the Degree of Share of the Brand Follower

The most enthusiastic reaction of a follower is to share content from a commercial social network on his or her web, which makes him or her a recipient of content and an active disseminator of it [36]. The following hypothesis is therefore put forward.

Hypothesis 1 (H1).

The Brand Content influences the Share.

Table 1. Descriptive statistics of share according to brand content.

	N	Media	Standard Deviation	Standard Error	95% Confidence Interval for the Mean		Minimum	Maximum
					Lower Limit	Upper Limit
Industrial	9	16.67	16.793	5.598	3.76	29.57	6	60
Commercial	28	53.29	56.646	10.705	31.32	75.25	7	257
Social responsibility	25	49.12	35.279	7.056	34.56	63.68	1	142
Total	62	46.29	45.849	5.823	34.65	57.93	1	257

shows that out of a total of 9 messages published with industrial brand content by the firm Manolo Blahnik, the average share was 16.67, with a minimum of 6 and a maximum of 60 shares. On the other hand, of the 28 publications with commercial brand content, the followers had an average share of 53.29, with a minimum of 7 and a maximum of 257. On the other hand, in the case of publications concerning Social Responsibility, they had an average share of 46.29, with a minimum of 1 and a maximum of 142 in shares. For all categories of Branded Content, the standard deviation is very high, which is usual since followers’ behavior in social networks is very diverse.

However, in

Table 2. Share ANOVA statistics according to brand content.

	Sum of Squares	gl	Half a Quadratic	F	Next
Between groups	9468.420	2	4734.210	2.352	0.104
Within groups	118,764.354	59	2012.955
Total	128,232.774	61

, according to the F statistic of the ANOVA analysis for 95% confidence, the differences between the average consumer shares and the different categories of brand content are not significant, with F of 2.352 a Sig. 0.104 > 0.05, so the H1 hypothesis is rejected. This may be because the interrelations of followers concerning commercial publications and social responsibility publications have an average share of more than 46 claims in both cases, which is very favorable for brand diffusion. On the other hand, in the more industrial brand content, the interactions in terms of share are lower than in the two previous categories. Still, even so, the diffusion continues to be active.

3.2. Analysis of the Relationship between Branded Content and Interaction in the Brand Follower Comments

Another unusual behavior of a brand’s followers in social networks is their comments, since they become prescribers of the brand, especially when these comments are positive. Therefore, the following hypothesis is proposed to be contrasted.

Hypothesis 2 (H2).

Brand Content Influences Comments.

Table 3. Descriptive statistics of the comments according to the brand content.

		N	Media	Standard Deviation	Standard Error	95% Confidence Interval for the Mean		Minimum	Maximum
						Lower Limit	Upper Limit
Positive comments	Industrial	9	3.56	4.746	1.582	−0.09	7.20	0	15
	Commercial	28	14.43	22.608	4.273	5.66	23.20	1	105
	Social responsibility	25	11.56	10.186	2.037	7.36	15.76	1	42
	Total	62	11.69	16.830	2.137	7.42	15.97	0	105
Neutral comments	Industrial	9	0.22	0.667	0.222	−0.29	0.73	0	2
	Commercial	28	1.43	1.894	0.358	0.69	2.16	0	7
	Social responsibility	25	2.52	4.602	0.920	0.62	4.42	0	18
	Total	62	1.69	3.257	0.414	0.87	2.52	0	18
Negative comments	Industrial	9	0.00	0.000	0.000	0.00	0.00	0	0
	Commercial	28	0.18	0.390	0.074	0.03	0.33	0	1
	Social responsibility	25	0.16	0.473	0.095	−0.04	0.36	0	2
	Total	62	0.15	0.399	0.051	0.04	0.25	0	2

shows that in a total of 9 messages published with industrial brand content by the firm, the average positive comments were 3.56, neutral 0.22, and zero harmful. On the other hand, in the face of the 28 publications with commercial brand content, the followers have had 14.43 positive comments on average, 1.43 neutral, and 0.18 negative. On the other hand, in the case of social responsibility publications, they have had 11.56 positive comments on average, 2.52 neutral, and 0.16 negative. Again, for all brand content categories, the standard deviation is very high, which is usual since the degree of participation in comments from followers in social networks is very diverse.

On the other hand,

Table 4. ANOVA statistics of comments according to brand content.

		Sum of Squares	gl	Half a Quadratic	F	Next
Positive comments	Between groups	805.938	2	402.969	1.443	0.244
	Within groups	16,471.239	59	279.174
	Total	17,277.177	61
Neutral comments	Between groups	38.525	2	19.262	1.867	0.164
	Within groups	608.653	59	10.316
	Total	647.177	61
Negative comments	Between groups	0.226	2	0.113	0.705	0.498
	Within groups	9.467	59	0.160
	Total	9.694	61

shows that according to the F statistic of the ANOVA analysis for 95% confidence, the differences between the average comments of the followers and the different categories of brand content are not significant, with an F of 1.443 a Sig. 0.244 > 0.05 in the case of positive comments, with an F of 1.867 one sig. 0.164 > 0.05 in the case of neutral words and an F of 0.705 one sig. 0.498 > 0.05 in the case of negative comments, so the H2 hypothesis is rejected. This may be because followers’ interrelationships concerning commercial publications and social responsibility publications are very similar since they publish comments with an average somewhat higher of 14 and 11 positive comments, respectively. Slightly more than 1 and 2 neutral average comments and scarcely 0.18 and 0.16 negative comments. On the other hand, in the more industrial brand content, the interactions in followers’ comments are lower than in the two previous categories. Still, even so, the diffusion continues to be active and positive.

3.3. Analysis of the Relationship between the Brand Content and the Interaction in the Feelings of the Follower towards the Brand

An expected behavior among brand followers is to share the emotions generated by each of the publications. Therefore, the following hypothesis is proposed.

Hypothesis 3 (H3).

Brand Content influences the feelings of the follower towards the brand.

In

Table 5. Descriptive statistics of feelings according to brand content.

		N	Media	Standard Deviation	Standard Error	95% Confidence Interval for the Mean		Minimum	Maximum
						Lower Limit	Upper Limit
Likes	Industrial	9	323.44	265.895	88.632	119.06	527.83	105	1000
	Commercial	28	817.36	678.256	128.178	554.36	1080.36	233	3000
	Social responsibility	25	875.88	550.066	110.013	648.82	1102.94	166	2100
	Total	62	769.26	605.791	76.935	615.42	923.10	105	3000
Love	Industrial	9	79.00	89.577	29.859	10.15	147.85	26	313
	Commercial	28	262.71	279.253	52.774	154.43	371.00	34	1200
	Social responsibility	25	237.48	212.189	42.438	149.89	325.07	24	893
	Total	62	225.87	239.049	30.359	165.16	286.58	24	1200
Care	Industrial	9	2.44	3.395	1.132	-0.17	5.05	0	10
	Commercial	28	4.46	8.934	1.688	1.00	7.93	0	37
	Social responsibility	25	2.84	4.059	0.812	1.16	4.52	0	13
	Total	62	3.52	6.640	0.843	1.83	5.20	0	37
Haha	Industrial	9	0.11	0.333	0.111	-0.15	0.37	0	1
	Commercial	28	0.75	1.236	0.234	0.27	1.23	0	5
	Social responsibility	25	0.64	0.907	0.181	0.27	1.01	0	3
	Total	62	0.61	1.030	0.131	0.35	0.87	0	5
Wow	Industrial	9	2.44	3.005	1.002	0.13	4.75	0	9
	Commercial	28	17.04	28.177	5.325	6.11	27.96	0	120
	Social responsibility	25	11.04	10.960	2.192	6.52	15.56	0	51
	Total	62	12.50	20.618	2.619	7.26	17.74	0	120
Sad	Industrial	9	0.00	0.000	0.000	0.00	0.00	0	0
	Commercial	28	0.07	0.262	0.050	-0.03	0.17	0	1
	Social responsibility	25	0.12	0.332	0.066	-0.02	0.26	0	1
	Total	62	0.08	0.275	0.035	0.01	0.15	0	1
Angry	Industrial	9	0.00	0.000	0.000	0.00	0.00	0	0
	Commercial	28	0.04	0.189	0.036	−0.04	0.11	0	1
	Social responsibility	25	0.24	0.436	0.087	0.06	0.42	0	1
	Total	62	0.11	0.319	0.041	0.03	0.19	0	1

, you can see that in a total of 9 messages published with brand content industrial by the brand Manolo Blahnik, the feelings spread by the followers were 322.44 likes media, 79 loves media, 2.44 care media, 0.11 haha media, 2.44 wow media, and no sad, nor angry feelings. In the case of the 28 publications with commercial brand content, the followers have had 817.36 likes on average (where a minimum of 233 and a maximum of 3000 likes were shared), 262.71 loves on average, 4.46 care on average, 0.75 haha on average, 17.04 wow on average, 0.07 sad on average and 0.04 angry. On the other hand, in the case of publications referring to Social Responsibility, it is worth noting that they have had an average of 875.88 likes, an average of 237.48 loves, an average of 2.84 care, an average of 0.64 haha, an average of 11.04 wow, an average of 0.12 sad and an average of 0.24 angry. Again, for all the brand content categories, the standard deviation is very high, which is usual since followers’ type of feeling in social networks is very diverse.

Table 6. ANOVA statistics of feelings according to the brand content.

		Sum of Squares	gl	Half a Quadratic	F	Next.
Likes	Between groups	2,137,732.580	2	1,068,866.290	3.115	0.052
	Within groups	20,248,179.291	59	343,189.480
	Total	22,385,911.871	61
Love	Between groups	235,517.013	2	117,758.507	2.138	0.127
	Within groups	3,250,293.954	59	55,089.728
	Total	3,485,810.968	61
Care	Between groups	46.937	2	23.469	0.524	0.595
	Within groups	2642.547	59	44.789
	Total	2689.484	61
Haha	Between groups	2.811	2	1.405	1.340	0.270
	Within groups	61.899	59	1.049
	Total	64.710	61
Wow	Between groups	1539.353	2	769.677	1.862	0.164
	Within groups	24,392.147	59	413.426
	Total	25,931.500	61
Sad	Between groups	0.100	2	0.050	0.654	0.524
	Within groups	4.497	59	0.076
	Total	4.597	61
Angry	Between groups	0.685	2	0.343	3.660	0.032
	Within groups	5.524	59	0.094
	Total	6.210	61

shows that according to the F statistic of the ANOVA analysis for 90% confidence, the differences between the average feelings of the followers and the different categories of brand content are significant with an F of 3.1153 one sig. 0.052 < 0.10 in the case of likes, and on the opposite side for angry, it has an F of 3.66 one sig. 0.032 < 0.05 at 95% confidence, so the H3 hypothesis is accepted. This may be because the feeling commonly shared in all social networks is like the one that is most shared by followers in social networks before the publications they like. Therefore, it is particularly striking that they want commercial publications and significantly like publications with a corporate social responsibility brand content. For its part, in the more industrial brand content, the interactions in terms of followers’ feelings are lower than the two previous categories. Still, even so, the spread of likes 323.44 times shared remains positive.

3.4. Analysis of the Relationship between the Brand Content and the Interaction in Reactions of the Follower towards the Brand

The followers’ responses to the brand can be positive or negative in each of the publications of brand content, so in this section of the work, we contrast the following hypothesis.

Hypothesis 4 (H4).

Brand Content influences the positive and negative reactions of the brand follower.

In industrial brand content, all responses were positive, with an average of 407.44 (see

Table 7. Descriptive statistics of the reactions of the follower according to the brand content.

		N	Media	Standard Deviation	Standard Error	95% Confidence Interval for the Mean		Minimum	Maximum
						Lower Limit	Upper Limit
Positive reactions	Industrial	9	407.44	360.675	120.225	130.21	684.68	132	1333
	Commercial	28	1102.32	988.640	186.835	718.97	1485.68	270	4325
	Social responsibility	25	1127.88	758.051	151.610	814.97	1440.79	190	2946
	Total	62	1011.76	859.619	109.172	793.46	1230.06	132	4325
Negative reactions	Industrial	9	0.00	0.000	0.000	0.00	0.00	0	0
	Commercial	28	0.11	0.315	0.060	-0.01	0.23	0	1
	Social responsibility	25	0.36	0.569	0.114	0.13	0.59	0	2
	Total	62	0.19	0.438	0.056	0.08	0.30	0	2

). On the other hand, for the commercial brand content, the positive reactions were significantly high on average at 1102.32 and with only 0.11 adverse reactions. Finally, the most increased average positive responses for the social responsibility brand content stand out, with an average of 1127.88 positive reactions and only 0.36 adverse reactions.

Table 8. ANOVA statistics of positive and negative reactions according to the brand content.

		Sum of Squares	gl	Half a Quadratic	F	Next.
Positive reactions	Between groups	3,853,510.402	2	1,926,755.201	2.758	0.072
	Within groups	41,222,150.969	59	698,680.525
	Total	45,075,661.371	61
Negative reactions	Between groups	1.239	2	0.619	3.501	0.037
	Within groups	10.439	59	0.177
	Total	11.677	61

shows how the positive and negative reactions according to the category of the brand content show significant differences at 90% confidence. In positive responses, the F statistic is 2.758 with a significance of 0.072 < 0.10, as well as the adverse reactions with an F of 3.501 and a significance of 0.037 < 0.10 even 0.037 < 0.05. Hence, it is accepted the hypothesis that the brand content influences the positive and negative reactions of the follower towards the brand.

4. Discussion and Conclusions

Social networks have been consolidated as a potential tool in transmitting Content between institutions, in this specific case, between brands and their audience. Studies on engagement processes have been very relevant and recurrent in recent years, to the extent that they have become one of the main objects of research on social networks both from the academic and business perspective since their impact affects various areas such as marketing, education, or media [37].

In this context, the purpose of this research has been established in analyzing to what extent the brand content disseminated in social networks is related to the interactions of the followers of luxury brands in the textile sector. The measurement of this type of Content tends to be done considering the variables present in digital platforms, such as the number of likes, comments, and the option of sharing a publication [37]. To this end, four hypotheses were formulated:

4.1. The Brand Content Influences the Share

Concerning this first one, it is worth mentioning that Share is the most dynamic behavior that one could wish for from a follower to be the most ambitious goal for brands. Based on the findings obtained, there are significant differences in the degree of Share of a Manolo Blahnik follower when he observes an industrial publication to when he attends a commercial publication, being in the latter case the interaction much more active since with the industrial publication he shares almost 17 times on average and with the industrial one he shares a little more than 53 times. Likewise, in the case of social responsibility publications, the interactions continue to be very considerable, with an average share of just over 49.

4.2. Brand Content Influences Comments

As for the second hypothesis, the followers’ comments are generally optimistic about the brand content of the firm Manolo Blahnik, with very few neutral comments and practically no negative ones. Therefore, the word of most followers contributes positively to the diffusion of the brand. However, as in previous studies, the conversation is the least widespread reaction on Facebook. In this sense, the user tends to prefer interacting with the content through likes or replies or even sharing it rather than writing comments, since the latter activity is usually more common in other types of networks such as Instagram, where there are a greater preference and tendency to generate conversation through the option of comments [38].

4.3. Brand Content Influences the Feelings of the Follower towards the Brand

Regarding the third hypothesis of the study, it is essential to note that the brand content with social responsibility content generates a high number of likes significantly over the rest of the brand content categories. It is also very high the number of likes caused by the commercial contents. On the other hand, although they also generate a significant number of likes, industrial contents are significantly lower than the two previous categories. For its part, love is the most extreme feeling of pleasure, being very considerable, as they are more than 200 times on average that is shared as a feeling both in the commercial brand content and social responsibility. Negative emotions are, however, practically negligible in all types of brand content. However, in line with previous research in the fashion sector, it is worth noting the confirmation of the supremacy of the majority use of “like” in all categories, above all other possible reactions offered by Facebook [39,40], indicating that this option is the most widespread among users who decide to interact through the function of the reaction buttons in the various publications of the brand.

4.4. Brand Content Influences the Positive and Negative Reactions of the Brand Follower

On this path and concerning the fourth and last hypothesis, the results show that an upbeat assessment of the followers of Manolo Blahnik of the brand content published on Facebook can be seen, which fundamentally causes positive reactions from the most industrial brand content, being highlighted the positive reactions caused by the commercial brand content and above all the positive responses to publications on corporate social responsibility brand content. Therefore, the results of this work contribute not only to the literature but also to orient the brand content of luxury fashion brands published on Facebook.

From the conclusions reached, it is essential to emphasize that it is undeniable, therefore, that digital platforms, such as in this specific case, social networks, facilitate the processes of interaction between brands and their followers, allowing the contents and messages disseminated to achieve more significant impact and commitment to the public and, therefore, increase the engagement between the brand and its followers. These types of resources provide users with the possibility to dialogue, participate and interact with content creators and transmitters [37], favoring two-way communication and benefits for both parties [41]. However, it also implies challenges for both the audience and brands, since on the one hand, users require the knowledge, skills, and attitudes necessary to critically address the messages received through these media, as well as for brands, which have to adapt to the continuous changes, trends, tastes and characteristics offered by social networks, to achieve more significant commitment and reach of their publications. It should not be forgotten that brands use communication strategies, among which is the commercial one. Hence, many of the journals they share with the community are for sales purposes [42].

Hence, commercial publications have the interaction much more active than the industrial publications respect to share. The findings show that Manolo Blahnik’s followers have an optimistic assessment of the brand content published on Facebook, which provokes positive reactions to the industrial brand content, to a greater extent, the commercial brand content provokes positive reactions and highlights the positive responses of the followers to the publications on corporate social responsibility brand content. Regarding the interactions of the followers’ consumer comments, they are generally optimistic about the brand content of the firm Manolo Blahnik, with very few neutral comments and practically no negative ones regardless of the type of content published. In relation to interaction feeling, the brand content with social responsibility content generates a high number of likes significantly over the rest of the brand content categories.

The findings show that Manolo Blahnik’s followers have an optimistic assessment of the brand content published on Facebook, which provokes positive reactions to the industrial brand content, to a greater extent, the commercial brand content provokes positive reactions and highlights the positive responses of the followers to the publications on corporate social responsibility brand content.

Another of the managerial implications of this paper is that it is recommended to take advantage of brand content in social networks as a communication strategy to reach the target audience, given that during the COVID19 pandemic period, users of social networks use them more for entertainment and socializing with their environment, making it more accessible to them through this medium than through conventional means during periods of confinement.

In future lines of research, firstly, the study can be extended to other social media profiles of the brand. Additionally, a comparative analysis of other luxury fashion brands can be established to compare communication management, Content generation strategies and the impact on interaction and engagement generated with the audience.

Similarly, it could be interesting to carry out a qualitative analysis concerning user comments, which would allow a more comprehensive view of the opinion that the public has about the brand, the way they express their ideas or points of view, and the interactions produced around the publications both aimed at the brand itself or with other users. In this line and even taking into account that the findings have shown a presence of significantly shallow adverse reactions, this approach could help to understand better the possible dissatisfaction of specific part of the followers of the brand and its forms of expression, which would imply an interesting approach taking into account that the opinions of the audience may favor, but also harm the brands [39].