Next Article in Journal
Location-Based Augmented Reality for Cultural Heritage Education: Creating Educational, Gamified Location-Based AR Applications for the Prehistoric Lake Settlement of Dispilio
Previous Article in Journal
When BERT Started Traveling: TourBERT—A Natural Language Processing Model for the Travel Industry
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:

Analyzing Brand Awareness Strategies on Social Media in the Luxury Market: The Case of Italian Fashion on Instagram

Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Via Giuseppe Ponzio, 34/5, 20133 Milano, Italy
Scuola di Ingegneria Industriale e dell’ Informazione, Politecnico di Milano, Via Raffaele Lambruschini, 15, 20156 Milan, Italy
Department of Informatics and Networked Systems, University of Pittsburgh, Pittsburgh, PA 15260, USA
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Digital 2023, 3(1), 1-17;
Received: 9 November 2022 / Revised: 12 December 2022 / Accepted: 21 December 2022 / Published: 31 December 2022


The rapid proliferation of social media has been redefining every facet of the old marketing and customer engagement tactics, not only for low-end and mass-market products but also for luxury brands. In this context, brands are dealing with the challenge of maintaining a balance between using mass marketing strategies concurrent with accentuating the exclusivity of their offerings. Social media can be considered beneficial if brands employ it to reach the right audience and use the right platform and incorporating the right content. In this work, we propose a sector-specific, integrated, and holistic investigation of the social media strategies of luxury brands together with the impact they generate in terms of the engagement level of the users as an indicator of their success. We provide empirical validation of the methods used in the Italian market of the luxury fashion sector, providing a qualitative and quantitative analysis of the content shared on social media, considering the type, timing, and modality of the sharing. We evaluate consumer-brand engagement in different contexts, including important live events in the field.

1. Introduction

The amount of social media content is snowballing, and the trend is not ending anytime soon. Social networks are, by nature, a democratic form of media accessible to everyone from anywhere. As the virtual landscape acts as a place in which content such as pictures, videos, and opinions are continually circulating regardless of brand ownership, the main agenda of brand managers has become setting strategic actions to control the digital transformation as much as possible and seize the opportunities linked to social media. In this sense, observing, collecting, and analyzing this rich and endless flow of user–brand-generated information will yield valuable information.
The data-driven approach for users’ behavioral analysis is based on the concept of the big data paradigm [1,2]. Indeed, the rapid proliferation of social media has been redefining every facet of old marketing and customer engagement tactics, not only for the low-end and mass-marketed products but also for luxury brands. Currently, customer behavior towards brands has been altered profoundly throughout the entire purchase process and decision-making stages from the awareness and recognition of needs to later stages and beyond. Social media provides the potential to communicate and interact with highly involved users [3] and build relationships and bonds between individuals, who will subsequently positively represent the brand to their social media communities [4,5]. Social media has a considerable effect on consumer behavior from the phase of information acquisition to later on in the post-purchase stage through interactions such as (dis)satisfaction statements [6].
Thanks to the growing enthusiasm for luxury goods within the era of the democratization of luxury, brands are dealing with the challenge of maintaining balance between using mass media (social networks and mass-marketing strategies) concurrent with accentuating the exclusivity aspect of their offerings. In other words, social media can be considered as beneficial if brands employ it to reach the right audience at the right time, using the right platform and incorporating the right content. In contrast, an incorrect marketing strategy implemented on these platforms can create a highly negative impact on the brand image and business.
Companies that implement social media marketing strategies must continuously monitor and analyze the large amount of information available to them and listen to conversations to determine the needs of the customers and identify what satisfies different audiences and sub-populations that will be most receptive to different tactics. Companies should also consider that the focus of social media is on content, and end users have an active role in generating it. If companies design their strategies appropriately, they can foster a social media transformation process [7] which leads a commercial message to be seen as a social source [8]. It is obvious that luxury brands have to craft an online experience that is just as proficient and artistic as their mainstream products. To do so, they have to make the most out of their social media presence and continuously share content to make it engaging and responsive.
At present, there is plentiful research and many reports that have been conducted to extract information from different social network platforms through methods such as studying the behavioral patterns of user demographics, the centers of attention, and the effects of influencers. The greater the depth of this knowledge, the greater the success of content marketing activities carried out by companies will be. In particular, according to Kapfererand and Bastien [9], there has been substantial attention from the research community directed toward the social media strategies of luxury brands and the business outcomes gained as a result of such initiatives. Many researchers have investigated the usage, content, and mechanics of using social media such as Instagram and Facebook, covering both business aspects and user perception. Nevertheless, a comprehensive sector-specific perspective on luxury brands considering the content, categorization, volume, and timing of social media publishing is still missing. Such a perspective is precious, as it would represent an objectification of marketing actions and define the relationship between different decisions and categories of content and their relative success in terms of user perception and engagement.

1.1. Objectives

In this paper, we propose a sector-specific, integrated, and holistic investigation of the social media content of luxury brands together with their impact on the users’ engagement level as an indicator of their success. In particular, the objective of this study is to definea general model for investigating the communication strategies of luxury brands and their impact on social media
To attain this objective, we propose a multi-dimensional qualitative and quantitative method to extract and analyze the content published by the brands and evaluate consumer–brand engagement in different contexts, including important live events. In practice, our method addresses the above objective by analyzing data collected from social media and responding to the following questions:
  • What is the frequency of posts by each brand?
  • Which roles are most used by the studied brands in their online content?
  • What are the most employed product categories by brands, and is there any relation between them and online users’ engagement?
  • Who are the main targets of the products?
  • What are the context categories that are most emphasized by each brand?
  • How successful are the different brands in engaging users with their online content?
  • How do brands benefit from mentions and hashtags?
  • How successful are the brands in terms of attracting attention to their events?
  • How are the events’ posts geographically distributed?
The integrated interpretation of all these dimensions leads to an understanding of the brands’ positioning, strategies, and their respective impacts.
To demonstrate the results of our approach, we apply our method to a real case study. We consider Italian luxury fashion brands and investigate the means by which they adopt and exploit social media platforms. We study their native profiles and analyze their publishing styles and approaches; correspondingly, we analyze online users’ response and engagement in fashion week events regarding the mentioned brands.

1.2. Structure of the Work

The rest of the work is organized as follows. In Section 2, we discuss the background and related work. Then, we briefly describe the Italian luxury fashion scenario and the sources we use as the case study. In Section 3, we present our approach and apply it to the case study. In Section 4, we report our results, and we discuss them in Section 5. Finally, we draw some conclusions in Section 6.

2. Background and Related Work

2.1. The Luxury Phenomenon

While the discussion around the social functions of luxury dates back to ancient Greece [10], luxury brand management is a relatively new concept [11]. Luxury brands’ goods and services vary incredibly, from automobiles to luxury apartments and watches [12]; however, they all share comparable intangible features such as prestige, distinction, and social status [9], driven by social and psychological needs such as self-enhancement or social esteem [13]. Until the 1990s, the market for luxury products was mainly formed by artisan family-based companies emphasizing premium quality, aesthetic value, and craftsmanship of the products [14]. Currently, however, superior quality and distinctiveness will not suffice to have a product to be considered to be a luxury; it must also convey symbolic meaning, storytelling, and intangible value according to macro-environmental, external, social, and cultural trends [12]. A noticeable expansion of the luxury market to include middle social classes has recently been observed. This is the result of the increasing disposable income of less wealthy consumers and the emergence of new luxury brands and more affordable lines of established fashion houses which join the perception of high prestige with less extravagant prices available to a broader range of income levels [15].
Chadha and Husband [16] introduced three different segments for luxury consumers, namely ‘gourmands’ (those consuming luxury products in large amounts and are always wearing designer tags all over themselves), ‘regulars’ (well-off people with financial assets over USD 100,000), and ‘nibblers’ (occasional buyers of luxury, typically young people with no savings but high-income thanks to a high-level of education and career).
Supporting the trends mentioned above, Amed et al. [17] classified the fashion industry into luxury, affordable luxury, premium/bridge, mid-market, value, and discount categories, and found a notable growth in the affordable luxury segment of 3.5%, which is in agreement with the ‘Democratization of luxury’ or the ‘Luxurification of social’ trends [18]. These trends are pushing luxury brands towards using mass marketing initiatives and, at the same time, accentuating the unique aspects of their offerings [19].

2.2. The Role of Celebrities

An example of a mass-market strategy applied to luxury brands is the celebrity endorsement in the realm of luxury, i.e., the use of celebrities to promote the brand [20] through a process of transfer of the symbolic properties associated with an endorser to a specific product or brand and then from the product to the consumers. Using celebrities is known to increase viewers’ attention, refine brand images, create brand awareness, reposition existing brands [21], enhance message recall [22], and generate a positive attitude [23]. On the other side, this may imply a diminished luxuriousness, as brand names would draw more attention from mid-level consumers than from high-end ones, as the latter are less subject to being affected by celebrity endorsements.

2.3. The Role of Social Media

Given that social media is founded on the principles of democracy, inclusion, and global access, many challenges for brand managers have been raised by the question of how luxury brands can combine a sense of exclusivity with the potential of the internet and social media. Social media touches almost every facet of our lives; therefore, it is imperative that it is an integral part of a brand’s strategy [24]. Social media is defined as a group of Internet-based applications built on the ideological and technological foundations of Web 2.0 which allow users to create, generate, and share content [3]. Social media has many benefits, as it helps connect businesses to consumers, develop relationships, and foster those relationships promptly and at a low cost. Web 1.0 was primarily focused on one-to-many relationships, whereas later on, Web 2.0 came into play, with a focus on many-to-many content. Web 2.0 then enabled users to generate content by setting up their own websites and blogs, posting videos, and filling the Web. Such practices have led to the democratization of technology, information, and knowledge, enabling the active participation of users as contributors, reviewers, and reporters. In order to be relevant, engaging, and desirable for users, brands must build their image in this space. Indeed, the brand image can no longer be achieved by only adopting a one-way communication strategy; it certainly requires engagement with social media and incorporation of consumers [25].
Uitz [26] categorized the main applications of social media. By understanding the different usages, functions, user-bases, and strategies provided by each social media platform, brands can capture, understand, and evaluate how different users influence others, are impacted by others, receive and perceive information, and interact with each other using social media. This can revolutionize existing marketing practices, such as advertising and promotion [27]. Whereas in the beginning, many businesses adopted social media as a broadcast media [6], the nature of social media goes well beyond this point, allowing consumers, rather than brands alone, to impact and contribute to the content. In this context, the brand itself can influence the conversations consumers partake in surrounding their brand. To realize this goal, marketers need to carefully manage what is being communicated and, even more notably, from whom that communication comes [28]. According to Constantinides [29], companies have two approaches to social media: a passive one, aiming to use social media to listen to the market needs, and an active one, implementing marketing initiatives in various forms (public relations and direct marketing, engaging personalities as product/brand advocates, personalizing the online experience and product customization, and engaging the customer in co-creation/innovation processes). Content marketing will not drive customer actions until an emotional connection is developed between the brand and the audience [30].

2.4. The Role of Instagram

Previously, luxury was the sphere of glamour and extravagance that was safeguarded exclusively for the elite, but today things have changed, thanks to digital communication and platforms. In the fashion ecosystem, Instagram has created an environment where luxury can be showcased through photo sharing, short videos, and stories in a visually pleasing and highly stimulating way. This is inherently valuable for fashion brands [31], engaging users in brand-related activities, loyalty [32], and higher brand purchase intention [33].

2.5. Social Media Measurement

One of the main challenges is measuring the impact of social media marketing activities on key brand success measures [34]. Kim and Ko [35] analyzed the use of social media marketing for supporting luxury fashion brands’ marketing actions. Through a self-administrated survey with visual stimuli to consumers, they confirmed the significance of using social media marketing for increasing customer relationships and purchase intention. The two main drivers considered were intimacy (closeness, connectedness, and bondedness) [36,37] and trust [38] as representatives of a positive customer relationship which will lead to increased brand performance and positive customer behaviors, such as purchase intention and positive word of mouth. Influence analysis on social media related to brands has also been explored extensively; Manikonda et al. [39] presented a qualitative analysis of the influence of social media platforms on different behaviors of fashion brand marketing. They analyzed the styles and strategies of fashion brands’ advertisements. The authors employed both linguistic and computer vision techniques. Kim and Ko [40] identified attributes of social media marketing activities and examined the relationships between those perceived activities, value equity, relationship equity, brand equity, customer equity, and purchase intention through a structural equation model. The findings of De Vries et al. [5] show that different factors influence the impact of posts, measured as the number of likes and comments on fashion posts. Namely, they found that vivid and interactive characteristics enhance the number of likes on brand posts. An analysis in [41] was conducted during the 2011 Victoria’s Secret Fashion Show, reporting a majority of idiosyncratic remarks, with many tweets containing evidence of social status comparisons to the fashion models. Based on two studies related to the fashion industry, Entwistle and Rocamora [42] examined one of its key institutions, London Fashion Week (LFW). They demonstrated how LFW visibly represents the boundaries, relational positions, capital, and habits at play in the field, reproducing critical divisions within it.

3. Method

3.1. Procedure

Figure 1 depicts a high-level view of the research process followed in this work. In the following, we describe each step of the process.

3.1.1. Brand Selection

To select the brands to be analyzed in our work, we considered the brand value and also tried to include companies with non-similar brand identity and user perception to ensure a comprehensive analysis and to obtain reliable results to generalize the findings.
To describe our method in practice, we select one use case and report on its analysis throughout the paper. In particular, we focus on the Italian luxury fashion industry, and we select 10 of the most successful brands in the sector. To select the brands for this study, we considered the brand value. Finance [43] provided a list of the top 50 Italian brands and placed our selected brands at the following positions: Gucci, 3rd; Prada, 9th; Giorgio Armani, 10th; Salvatore Ferragamo, 20th; Versace, 26th; Dolce & Gabbana (D&G), 34th; Valentino, 37th; and finally, Fendi, occupying 49th place. Besides the top eight mentioned brands, due to the fact that Roberto Cavalli is another successful well-known brand that succeeded in fitting itself in the list of the top 10 most successful Italian luxury brands on Instagram based on the number of followers, we included it in the analysis as well.

3.1.2. Event Selection

Thanks to the wide adoption of smartphones, which enable continuous information sharing with social network connections, the online response to popular real-world events is becoming increasingly significant [44].
Javadian et al. [45] introduced the concept of long-running live events (LRLEs) as “periodically repeated events like festivals that are held physically in some locations and are covered on social media.”
Studying these events provides useful insights to the brands for future decision-making purposes. Motivated by the LRLE’s potential as discussed in various works [45,46,47,48,49,50,51], we chose Milano Fashion Week, which is one of the “big four” fashion capitals.

3.1.3. Multi-Fold Data Collection

Platform: The next step consisted of choosing a social media platform to analyze. According to Statista (, accessed on 5 November 2022), Instagram ranks as the 4th most famous social network site worldwide, with more than 1478 million user bases. According to Instagram’s data, there are more than 25 million business profiles worldwide as of January 2022. The platform continuously improves and provides new features for business profiles to target their audience better and promote their offerings. Besides the stories, carousels, live videos, and photos which were the primary features initially offered by Instagram, there are now many possibilities for enabling the posts and stories to direct shopping and conversion capabilities by incorporating clickable URLs. Some benefits of using Instagram analytics are that they allow marketers to learn through experience and garner a continuous improvement in their campaign designs and content creation. The basis of the analysis before reaching any conclusion is the media posted on Instagram. We use the term media to refer to the posts (both images and videos) shared by brands on their Instagram profiles and the captions belonging to each of them.
As for luxury brands, the heritages and high values can be communicated by generating interactive visual content such as images, videos, and combinations of the two, leveraging the features offered by the platform in a way that evokes certain emotions and promotes dialogue between the brand and the users. A well-managed and well-designed social media presence is the only way to assure that a brand has a good presence on such inclusive media and to guarantee a well-orchestrated manifest of omni-channel digital communication.
Strategy: To design a reliable, complete, and consistent strategy, we extended the data collection strategy designed by Brambilla et al. [48] for LRLEs and set three different modes to collect the publicly available content and information from the Instagram API.
  • Brand activities:The data collected include all the posts that the brands uploaded from the beginning of the creation of the profiles until the date of extraction and the profile information such as the number of followers.
  • Event oriented: This strategy employs a set of hashtags, including general hashtags related to the events (Milan Fashion Week) such as #MilanFashionShow, #FashionWeekMilano, #MFW, and 37 more that cover all the events that happened in one year.
  • Brand event oriented: This strategy is conducted based on a set that contains a combination of event and brand hashtags to extract the share of voice for each brand. Some examples of Gucci event hashtags are #guccifw, #gucciss, #guccifashionshow. The same style has been applied to the other brands.

3.1.4. Data Preparation

To prepare data for the analysis, we applied the following steps.
  • Data pre-processing and data reduction: Because the obtained raw data are full of non-relevant information, we applied pre-processing techniques to formulate an appropriate set of data suitable for use in the next step of the study.
  • Data transformation: At this point, we stored the JavaScript object notation (JSON) files into the final desired structure to be usable for our later analysis in comma-separated values (CSV) format.
  • Media tagging: In order to perform the content analysis of the posts, the choice of the method was challenging given the fact that each alternative offered some drawbacks and advantages. Some tools and APIs provide the capability for tagging the content of the images. However, due to several limitations—including cost, a design primarily geared toward images rather than videos, and potential inaccuracies in the context of this study—the approach we took was manually tagging the posts by considering the contents of the posts, i.e., the caption, video, and image. The resulting assigned labels to the posts are presented in Table 1.

3.1.5. Entity Identification

Each social media platform is designed differently in terms of its features, user interface, and the expected behavior of participants. Thus, it is crucial to identify the main concepts that play a role in the social media platform, and, in particular, the ones that are relevant for the studied business case. To perform this task, we represent the entities and the associations between them in a conceptual model. Starting from the LRLEs’ core elements identified in [45], Figure 2 shows the high-level model describing the leading entities and the associations identified and extracted from the study.

3.1.6. Comparative Analysis

The analysis was designed with the following two main objectives:
  • The first objective was to target brands by analyzing their strategy in sharing posts on Instagram. We approached performing this analysis from two different perspectives:
    • A qualitative point of view investigating the details of the posts, extracting the information about each media, and classifying what they contain and are promoting.
    • A quantitative analysis of their approach using hashtags from 2013 to the date of extraction, together with their frequency of posting from the beginning of creating their profile.
  • Secondly, we added user-side information to the analysis to include brands’ user engagement. The study also examines the Instagram landscape in four time intervals, including four Milan Fashion Weeks, by analyzing event-specific and brand-related popular hashtags used by the users.
The purpose of this strategy is to provide a complete understanding of each brand strategy in posting on Instagram and stresses their differences and similarities. In other words, while we answer whether there are noticeable differences in the activities and strategies adopted by the brands in the study, we will identify which contexts will attract more attention to the brand. Consequently, the resulting information is twofold. From one perspective, it enables us to compare brands’ activities and provide a comprehensive evaluation of each brand’s performance using different content. From the other perspective, it also summarizes all the results into some figures that highlight which areas receive more attention from the brands and which areas receive more user engagement. This is valuable as a rich source of guidance for best practices in the sector, considering that the top nine brands’ activities are under the investigation of this very research.
Engagement rate (ER) is calculated by summing the number of likes and comments for each post, and for understanding the correlation of criteria with ER, we employed the Pearson correlation score (PCS). It should be noted that the PCS takes a value between 1 and + 1 , where a positive PCS value indicates that the criteria of the analysis are improving the ER and a negative PCS value indicates that the criteria are deteriorating the ER.
Having a practical standpoint, our conclusions can serve as an initial insight for the brands to examine and evaluate their social media strategies to measure their effectiveness in enhancing their future marketing outcomes. These findings allow luxury fashion bloggers and marketers to better design and adopt their SMMS to capitalize on the vast potential offered by different platforms to achieve their marketing goals and communicate their values effectively.

4. Results

This section is dedicated to reporting the results of the analyses performed by applying our approach to the use case. We cover each research question separately and we report the respective findings.

4.1. What Is the Frequency of Posts by Each Brand?

An overview of the frequency of posts by brands (see Figure 3) reveals that September, October, January, and February, with the greatest number of posts, create the highest peaks, likely due to the spring/summer and fall/winter international fashion weeks. On the other hand, December and August, with the least number of posts, are in the last two places. The three companies that published the most posts were D&G, Gucci, and Valentino.

4.2. Which Roles Are Most Used by the Brands of Study in Their Online Content?

Among the first notions that social media users will consider are the people that have a starring role in the photos or videos. Celebrities and luxury are inseparable, with one completing the other. Likewise, people have been classified into three categories in this study, as explained before. As shown in Figure 4, the model class has the highest share of the three roles for all brands, but D&G has the highest proportion of celebrities. The reason D&G has the highest share of celebrities is their launch of the millennial campaign, which included a group of the most popular Instagram influencers, inviting them to the stage on the runway and advertising campaigns. Versace has the lowest share of potential influencers, under 10 % , and Armani has the (not unprecedented) lowest share of celebrities among its published posts.
We studied the correlation of each of the roles to the ER, which revealed that using celebrities in the posts is the most favorable (PCS = 0.11 ), whereas surprisingly, the model role had a negative impact (PCS = 0.056 ) on the ER.

4.3. What Are the Most Employed Product Categories by Brands, and Is There Any Relation between Them and Online Users’ Engagement?

Considering the product range of the brands and the respective degree of followers’ engagement (average number of likes) as investigated in Figure 5, except for some slight differences, all the brands, more or less provide a full range, emphasizing more on their elegant outfits. Bags are presented more in Fendi and Prada’s Instagram pages. It is reasonable to expect that Ferragamo emphasizes its footwear more on its page. What is notable in our findings and deserves more attention is the considerable portion of casual outfits, which are eye-catching, in the cases of D&G, Fendi, Prada, and Valentino.
Gucci is one of the biggest and most highly valued fashion luxury brands globally, with around 20M followers. The average like trend (represented in pink) demonstrates that followers have engaged more with the other accessories category. A universal view on other brands reveals that Ferragamo, Roberto Cavalli, Valentino, and Prada pursue a steady trend in average likes, meaning that on average, they received an approximately equal amount of likes for all the categories. In contrast, Versace has some fluctuations between eyewear and casual outfits and peaks for the perfume and makeup categories.
Considering all the brands’ posts, among the product categories, Elegant Outfit obtained the highest PCS with the engagement rate of 0.079 , which demonstrates why brands have dedicated a significant share of their content to emphasizing this group of products.

4.4. Who Are the Main Targets of the Products?

As for the products targeted for men, women, and children, to determine which type of product is more addressed by the brands, we extracted the bar chart presented in Figure 6, which shows (as expected) that women’s products are represented much more frequently than men’s products except for the case of Armani, in which the representations of women’s and men’s products are balanced.
Computing the PCS between the ER and the product targets category, the Female target obtained the highest positive correlation equal to 0.084 , and the Male target resulted in a negative correlation of 0.033 .

4.5. What Are the Most Stressed Context Categories by Each Brand?

The context of the post has been under investigation to see which field is the most desirable for companies to stress. A comparison between brands in eight context categories has been addressed in Figure 7.
Regarding this diagram, runway and advertisement artworks are generally two noticeable categories to which companies have dedicated their posts. Narrowing down these results, Prada has invested more in company advertisements while Roberto Cavalli has leveraged magazines and journals more than others. On the other hand, D&G, thanks to the various fashion shows presented in September and June, has the maximum number of posts in the Runway category. Among the contexts, the Event context resulted in the highest PCS with an ER equal to 0.04 .

4.6. How Successful Were Brands in Engaging Users with Their Online Content?

We calculated the normalized engagement rate (NER), which is the engagement rate of each post over the total number of followers of the brand in four spectra for discretizing NER as follows. The first scale, called high, is for NER more than 0.9 ; the second one with the name mid-high explains the range of NER between 0.6 and 0.9 ; for mid-low, the range is between 0.3 and 0.6 , and the last one, the lowest level, the range is less than 0.3 . The results for each brand of the study are presented in Figure 8.
It can be concluded that for the High NER range Versace and Gucci have gained the best results, with 72 and Gucci with 55 posts, respectively. Although Prada achieved a reasonable NER, this conclusion is based on only one post. Interestingly, D&G and Prada, with remarkable and eye-catching campaigns, have a negligible share of high and mid-high levels of NER, while Versace and Gucci exploited the most valuable results. On the other hand, some brands’ accomplishments are mainly in the middle, regarding their total number of posts, such as Fendi and Roberto Cavalli.
Moreover, we have identified the most favorable and unfavorable features from the presented taxonomy in Table 1 by calculating the correlation of each of the features to the ER for each brand and all of them simultaneously, which is presented in Table 2.

4.7. How Do Brands Benefit from Mentions and Hashtags?

We tried to obtain a relatively complete classification of brand strategies using mentions and hashtags and capture their similarities. Mentions, having the same level of importance as hashtags, adds to a post’s credibility and are rooted in the nature of social media. The objective of tagging with a username is to attach another profile that is somehow relevant to the post. As reported in Figure 9, marketers of our study have used this notion mainly with relatively similar strategies. With an overall view of all brands, the profiles of photographers and art directors are the most mentioned, with D&G having the maximum share of photographers and art directors. As for the tagging frequency of the second most important group, celebrities and potential influencers, Versace and Ferragamo are first and second with 15 % and 9 % , respectively. From the magazine and journal perspective, Prada shows the maximum contribution with 31 % share of posts mentioning their profiles.
We grouped the top 20 hashtags with a similar approach and were able to classify them, as reported in Figure 10. Subsequently, Gucci, Prada, and Versace appear on the list. The evidence presented shows that the next most adopted category is campaigns and product labels. Indeed, D&G generated these hashtags considerably more than other brands. From another perspective, Armani and Prada have used branded hashtags with their names more frequently than the rest, while Gucci and Valentino have preferred to include creative directors or the face of their campaigns to enrich their content. Overall, a wide range of generated hashtags can be sufficient to attract audiences, but the most persuasive categories extracted from the top 20 hashtags are highlighted by different colors in Figure 10.

4.8. How Successful Were Each of the Brands in Receiving Attention from Users from the Events?

The next group of analyses extends our knowledge about the level of engagement rate during four Milan Fashion Weeks.
Figure 11 displays the events and the roles of brands in engaging users to share posts with their branded hashtags. It is evident that Gucci gained more attraction in both the February and September events than other brands, and Versace and D&G are following it.

4.9. How Are the Events’ Posts Geographically Distributed?

Figure 12 represents where Instagram users posted regarding the fashion week events in this study.
As is clearly evident from the figure, most of the posts have been made in Italy and other European cities. In addition, two other main high post density regions are over New York and Los Angeles, which can be interpreted as the interest of the citizens of these cities regarding the events in this study. It should be noted that both cities host their own fashion weeks.

5. Discussion and Interpretation

Based on the technical methods and results achieved, we now report a final discussion and interpretation of the findings. Broadly speaking, our primary objectives focused on evaluating the published content of the brands, identifying the main types of content employed by the marketers, and determining which brand obtains better impact and visibility results. Along these directions, we tried to identify some specific success and failure factors. The most appreciated information that permits us to conclude if a brand is performing better than others is theengagement rate KPI.
To ease the understanding of the metric, we classified results into four categories, i.e., low, medium-low, medium-high, and high engagement rate levels. We consider a post to be successful if its normalized engagement rate is either in the medium-high or high ranges. Accordingly, we conclude that the best performing brand is Versace, as 26 % of Versace’s posts performed very well, while the second-best brand is Gucci, with ∼ 20 % of posts performing well. The best brands adopted very different online strategies: Versace exploited the power of celebrity endorsement (we saw that the posts with celebrities gained more likes than other content by far). Yet, Gucci proves the power of well-designed campaigns, having the second highest frequency of content containing advertising, art, and video campaigns. Influencers and celebrities support Versace’s campaigns (∼ 30 % of all the posts). On the opposite side, Prada and Valentino have similar strategies to the first two but not excellent results with only 1.6 % and 0.7 % rates. Prada’s page is mainly about promoting products with storytelling and video campaigns (more than 33 % ) while having the maximum number of posts related to events, more than 13 % . Surprisingly, those were not effective enough in attracting the users’ attention. Valentino has the lowest number of well-performing posts, and it mostly displayed its runways ( 25 % in total). Fendi has a 16 % proportion of helpful posts with a moderate success rate and utilized more or less the average number of posts in all the categories. The performance of D&G is instead rather poor: despite having the second highest follower base and sharing five to six posts per day, only 6 % of them were engaging enough to gain above the average rate. This is in spite of the page being filled with celebrities and influencers together with the highest number of posts showing runways compared to other brands and the highest frequency of sharing company-related events.
As shown in the case studies of this research, in general, Gucci performs very well, having the highest number of followers. A total 20 % of its posts are gaining good attention, and as described in detail before, the blogger provides captions with straightforward, relevant, and appealing hashtags.
Overall, as the numbers show that content matters, especially for this one-of-a-kind sector, social media strategies have to be defined in a consistent approach. They must be aligned with overall brand strategy and with its roots, values, and signature. Furthermore, still many other variables affect success.

6. Conclusions

In this work, we presented a multi-dimensional analysis method for evaluating the role and effectiveness of brands online. Together with the method, we have provided a comprehensive analysis of nine famous Italian brand profiles in social media and during a famous long-running live event [45], i.e., Fashion Week, showcasing the functionality of the method.
Limitations of our study include the fact that we currently consider only organic content. Differently, comprehensive brand strategies often span a broader set of mechanisms, including paid advertising, which we currently do not consider. For instance, we did not consider how brands were using sponsored plans and paid media within the same platform or across many platforms, how they provided a seamless experience in approaching the market adopting different media and through different channels, and how advocates and opinion leaders produce good content. These mechanisms also play essential roles in the success of the brands and could be subject to future investigation and integration with the current method. The proposed methodology can be used by brands to improve their marketing strategies on social media. As a potential implication resulting from the proposed methodology, we propose analyzing the social conversation graphs, as designed by Brambilla et al. [49,50], to build conversational agents [52,53] that could potentially elevate users’ engagement.

Author Contributions

M.B.: supervision, funding acquisition, conceptualization, methodology, validation, investigation, writing—review and editing. H.B.: software, validation, investigation, data curation, writing—original draft, visualization. N.M.M.: software, validation, investigation, data curation, writing—original draft, visualization. A.J.S.: conceptualization, methodology, software, validation, investigation, data curation, writing—review and editing, visualization. All authors have read and agreed to the published version of the manuscript.


This work was partially funded by the European Union’s Horizon 2020 research and Innovation program “PERISCOPE: Pan European Response to the Impacts of COVID-19 and future Pandemics and Epidemics”, under the grant agreement N°101016233—H2020-SC1-PHE_CORON-AVIRUS-2020-2-RTD and the Regione Lombardia POR-FESR Project “FaST (Fashion Sensing Technology) —ID 187010”.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data subject to third party restrictions.

Conflicts of Interest

The authors declare no conflict of interest.


  1. Bessis, N.; Dobre, C. Big Data and Internet of Things: A Roadmap for Smart Environments; Springer: Berlin/Heidelberg, Germany, 2014; Volume 546. [Google Scholar]
  2. Brambilla, M.; Javadian Sabet, A.; Masciadri, A. Data-driven user profiling for smart ecosystems. In Smart Living between Cultures and Practices. A Design Oriented Perspective; Mandragora: Florence, Italy, 2019; pp. 84–98. ISBN 978-88-7461-496-7. [Google Scholar]
  3. Kaplan, A.M.; Haenlein, M. Users of the world, unite! The challenges and opportunities of Social Media. Bus. Horizons 2010, 53, 59–68. [Google Scholar] [CrossRef]
  4. Booth, N. Mapping and leveraging influencers in social media to shape corporate brand perceptions. Corp. Commun. Int. J. 2011, 16, 184–191. [Google Scholar] [CrossRef]
  5. De Vries, L.; Gensler, S.; Leeflang, P. Popularity of brand posts on brand and pages: An investigation of the effects of social media marketing. Interact. Mark. 2012, 26, 83–91. [Google Scholar] [CrossRef]
  6. Mangold, G.; Faulds, D. Social Media: The New Hybrid Element of the Promotion Mix. Bus. Horizons 2009, 52, 357–365. [Google Scholar] [CrossRef]
  7. Kilgour, M.; Sasser, S.L.; Larke, R. The social media transformation process: Curating content into strategy. Corp. Commun. Int. J. 2015, 20, 326–343. [Google Scholar] [CrossRef]
  8. Kietzmann, J.; Hermkens, K.; McCarthy, I.; Silvestre, B. Social media? Get serious! understanding the functional building blocks of social media. Bus. Horizons 2011, 54, 241–251. [Google Scholar] [CrossRef][Green Version]
  9. Kapferer, J.N.; Bastien, V. The Specificity of Luxury Management: Turning Marketing Upside Down. In Advances in Luxury Brand Management; Kapferer, J.N., Kernstock, J., Brexendorf, T.O., Powell, S.M., Eds.; Springer International Publishing: Cham, Switzerland, 2017; pp. 65–84. [Google Scholar] [CrossRef]
  10. Berry, C. The Idea of Luxury: A Conceptual and Historical Investigation; Cambridge University Press: Cambridge, MA, USA, 1994. [Google Scholar]
  11. Mazzalovo, G.; Chevalier, M. Luxury Brand Management: A World of Privilege; Wiley: Hoboken, NJ, USA, 2013. [Google Scholar]
  12. Yuri, S.; Margo, B. Luxury branding: The industry, trends, and future conceptualisations. Asia Pac. J. Mark. Logist. 2015, 27, 82–98. [Google Scholar]
  13. Nia, A.; Zaichkowsky, J. Do counterfeits devalue the ownership of luxury brands? J. Prod. Brand. Manag. 2000, 9, 485–497. [Google Scholar] [CrossRef]
  14. Jackson, T. International Herald Tribune fashion 2001 conference review. Fash. Mark. Manag. 2002, 6. [Google Scholar] [CrossRef]
  15. Truong, Y.; McColl, R.; Kitchen, P. New luxury brand positioning and the emergence of masstige brands. Brand Manag. 2009, 16, 375–382. [Google Scholar] [CrossRef]
  16. Chadha, R.; Husband, P. Cult of the Luxury Brand: Inside Asia’s Love Affair with Luxury; Nicholas Brealey International: Boston, MA, USA, 2010. [Google Scholar]
  17. McKinsey & Company. The State of Fashion; McKinsey Global Institute: Washington, DC, USA, 2017. [Google Scholar]
  18. Atwal, G.; Williams, A. Luxury brand marketing–the experience is everything! In Advances in Luxury Brand Management; Palgrave Macmillan: Cham, Switzerland, 2017; pp. 43–57. [Google Scholar]
  19. Okonkwo, U. Luxury Fashion Branding: Trends, Tactics, Techniques; Springer: Berlin/Heidelberg, Germany, 2016. [Google Scholar]
  20. McCracken, G. Advertising: Meaning Or Information. Adv. Cem. Res. 1987, 14, 121–124. [Google Scholar]
  21. Erdogan, B. Celebrity Endorsement: A Literature Review. J. Mark. Manag. 1999, 15, 291–314. [Google Scholar] [CrossRef]
  22. Friedman, H.; Friedman, L. Endorser Effectiveness by Product Type. Advert. Res. 1979, 19, 63–71. [Google Scholar]
  23. Atkin, C.; Block, M. Effectiveness of celebrity endorsers. Advert. Res. 1983, 23, 57–61. [Google Scholar]
  24. Qualman, E. Socialnomics: How Social Media Transforms the Way We Live and Do Business; John Wiley & Sons: Hoboken, NJ, USA, 2012. [Google Scholar]
  25. Phan, M.; Thomas, R.; Heine, K. Social media and luxury brand management: The case of Burberry. Glob. Fash. Mark. 2011, 2, 213–222. [Google Scholar] [CrossRef]
  26. Uitz, I. Social Media—Is It Worth the Trouble? J. Internet Soc. Netw. Virtual Communities 2012, 2012, 313585. [Google Scholar] [CrossRef][Green Version]
  27. Hanna, R.; Rohm, A.; Crittenden, V.L. We’re all connected: The power of the social media ecosystem. Bus. Horizons 2011, 54, 265–273. [Google Scholar] [CrossRef]
  28. Taylor, D.; Lewin, J.; Strutton, D. Friends, fans, and followers: Do ads work on social networks?: How gender and age shape receptivity. Advert. Res. 2011, 55, 258–275. [Google Scholar] [CrossRef][Green Version]
  29. Constantinides, E. Social Media/Web 2.0 as marketing parameter: An introduction. In Proceedings of the 8th International Congress Marketing Trends, Paris, France, 16–17 January 2009; pp. 15–17. [Google Scholar]
  30. Pulizzi, J. How to Know Content Marketing When You See It. EContent 2013, 36, 16–17. [Google Scholar]
  31. Lenhart, A.; Duggan, M.; Perrin, A.; Stepler, R.; Rainie, L.; Parker, K. Teens, Social Media, and Technology; Pew Research Center: Washington, DC, USA, 2015. [Google Scholar]
  32. Phua, J.; Jin, S.V.; Kim, J.J. Gratifications of using Facebook, Twitter, Instagram, or Snapchat to follow brands: The moderating effect of social comparison, trust, tie strength, and network homophily on brand identification, brand engagement, brand commitment, and membership intention. Telemat. Inform. 2017, 34, 412–424. [Google Scholar] [CrossRef]
  33. Kilambi, A.; Laroche, M.; Richard, M.O. Constitutive marketing: Towards understanding brand community formation. Int. J. Advert. 2013, 32, 45–64. [Google Scholar] [CrossRef]
  34. Schultz, D.; Peltier, J. Social Media’s slippery slope: Challenges, opportunities and future research directions. J. Res. Interact. Mark. 2013, 7, 86–99. [Google Scholar] [CrossRef]
  35. Kim, J.; Ko, E. Impacts of luxury fashion brands social media marketing on customer relationship and purchase intention. J. Glob. Fash. Mark. 2010, 1, 164–171. [Google Scholar] [CrossRef]
  36. Sternberg, R. Construct validation of a triangular love scale. Soc. Psychol. 1996, 27, 313–335. [Google Scholar] [CrossRef]
  37. Carroll, B.A.; Ahuvia, A.C. Some antecedents and outcomes of brand love. Mark. Lett. 2006, 17, 79–89. [Google Scholar] [CrossRef]
  38. Chaudhuri, A.; Holbrook, B. The chain of effects from brand trust and brand affects to brand performance: The role of brand loyalty. Marketing 2001, 65, 81–93. [Google Scholar] [CrossRef][Green Version]
  39. Manikonda, L.; Venkatesan, R.; Kambhampati, S.; Li, B. Trending Chic: Analyzing the Influence of Social Media on Fashion Brands. arXiv 2015, arXiv:1512.01174. [Google Scholar]
  40. Kim, J.; Ko, E. Do social media marketing activities enhance customer equity? An empirical study of luxury fashion brand. J. Bus. Res. 2012, 65, 1480–1486. [Google Scholar] [CrossRef]
  41. Chrisler, J.; Fung, K.; Lopez, A.; Gorman, J. Suffering by comparison: Twitter users’ reactions to the Victoria’s Secret Fashion Show. Body Image 2013, 10, 648–652. [Google Scholar] [CrossRef]
  42. Entwistle, J.; Rocamora1, A. The Field of Fashion Materialized: A Study of London Fashion Week. J. Sociol. 2006, 40, 735–751. [Google Scholar] [CrossRef][Green Version]
  43. Finance, B. The Annual Report on the Most Valuable ITALIAN Brands; Brand Finance Italy: Milano, Italy, 2017. [Google Scholar]
  44. Brambilla, M.; Ceri, S.; Daniel, F.; Donetti, G. Spatial Analysis of Social Media Response to Live Events: The Case of the Milano Fashion Week. In Proceedings of the 26th International Conference on World Wide Web Companion, Perth, Australia, 3–7 April 2017; pp. 1457–1462. [Google Scholar]
  45. Javadian Sabet, A.; Brambilla, M.; Hosseini, M. A multi-perspective approach for analyzing long-running live events on social media. A case study on the “Big Four” international fashion weeks. Online Soc. Netw. Media 2021, 24, 100140. [Google Scholar] [CrossRef]
  46. Sabet, A.J. Social Media Posts Popularity Prediction During Long-Running Live Events a Case Study on Fashion Week. Master’s Thesis, Politecnico di Milano, Milan, Italy, 2019. [Google Scholar]
  47. Calisir, E.; Brambilla, M. The Long-Running Debate about Brexit on Social Media. In Proceedings of the International AAAI Conference on Web and Social Media, Atlanta, GA, USA, 8–11 June 2020; Volume 14, pp. 848–852. [Google Scholar]
  48. Brambilla, M.; Javadian Sabet, A.; Hosseini, M. The role of social media in long-running live events: The case of the Big Four fashion weeks dataset. Data Brief 2021, 35, 106840. [Google Scholar] [CrossRef]
  49. Brambilla, M.; Javadian, A.; Sulistiawati, A.E. Conversation Graphs in Online Social Media. In International Conference on Web Engineering; Springer International Publishing: Cham, Switzerland, 2021; pp. 97–112. [Google Scholar] [CrossRef]
  50. Brambilla, M.; Javadian Sabet, A.; Kharmale, K.; Sulistiawati, A.E. Graph-Based Conversation Analysis in Social Media. Big Data Cogn. Comput. 2022, 6, 113. [Google Scholar] [CrossRef]
  51. Hosseini, M.; Sabet, A.J.; He, S.; Aguiar, D. Interpretable Fake News Detection with Topic and Deep Variational Models. arXiv 2022, arXiv:2209.01536. [Google Scholar]
  52. Gao, J.; Galley, M.; Li, L. Neural approaches to conversational AI. In Proceedings of the The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, Ann Arbor, MI, USA, 8–12 July 2018; pp. 1371–1374. [Google Scholar]
  53. Scotti, V.; Tedesco, R.; Sbattella, L. A Modular Data-Driven Architecture for Empathetic Conversational Agents. In Proceedings of the 2021 IEEE International Conference on Big Data and Smart Computing (BigComp), Jeju Island, Republic of Korea, 17–20 January 2021; pp. 365–368. [Google Scholar] [CrossRef]
Figure 1. Overview of the research procedure.
Figure 1. Overview of the research procedure.
Digital 03 00001 g001
Figure 2. High-level overview of the case study’s main entities and their associations. Extended from [45].
Figure 2. High-level overview of the case study’s main entities and their associations. Extended from [45].
Digital 03 00001 g002
Figure 3. Post frequency per month by each brand.
Figure 3. Post frequency per month by each brand.
Digital 03 00001 g003
Figure 4. Share of each role (celebrity, potential influencer, and model) by each brand of the study.
Figure 4. Share of each role (celebrity, potential influencer, and model) by each brand of the study.
Digital 03 00001 g004
Figure 5. Number of posts for each brand by product categories vs average likes.
Figure 5. Number of posts for each brand by product categories vs average likes.
Digital 03 00001 g005
Figure 6. Share of each target (women, men, children) by brands.
Figure 6. Share of each target (women, men, children) by brands.
Digital 03 00001 g006
Figure 7. Share of each different context category for each brand.
Figure 7. Share of each different context category for each brand.
Digital 03 00001 g007
Figure 8. Normalized engagement rate for each brand discretized in different spectra as high, mid-high, mid-low and low.
Figure 8. Normalized engagement rate for each brand discretized in different spectra as high, mid-high, mid-low and low.
Digital 03 00001 g008
Figure 9. Share of top 10 mentioned profiles in 6 categories by brands.
Figure 9. Share of top 10 mentioned profiles in 6 categories by brands.
Digital 03 00001 g009
Figure 10. The most persuasive hashtag categories by brands, based on frequency of appearance.
Figure 10. The most persuasive hashtag categories by brands, based on frequency of appearance.
Digital 03 00001 g010
Figure 11. Frequency of appearance of brands in the different events throughout the year.
Figure 11. Frequency of appearance of brands in the different events throughout the year.
Digital 03 00001 g011
Figure 12. Geographical distribution of social media reaction to the Milan Fashion Week events.
Figure 12. Geographical distribution of social media reaction to the Milan Fashion Week events.
Digital 03 00001 g012
Table 1. Taxonomy of assigned labels to the posts.
Table 1. Taxonomy of assigned labels to the posts.
ContextMagazine; Brand/Store Relevant; Runway; Advertisement campaign; Event; Other LoB
PeopleCelebrity/Influencer; Potential influencer; Anonymous model
ProductFoot-Wear; Eye-Wear; Watch/Jewelry; Dress/Outfit; Perfume/Beauty; Bag; Other accessories
Product TypeElegant; Casual
Product TargetWomen; Men; Kid
Table 2. Most correlated features with the engagement rate (both positive and negative) for each brand considering all together obtained from Pearson correlation score (PCS).
Table 2. Most correlated features with the engagement rate (both positive and negative) for each brand considering all together obtained from Pearson correlation score (PCS).
BrandTop PositivePCSWorst NegativePCS
G. ArmaniCelebrity0.24Runway−0.21
PradaFemale0.26Male and Casual−0.16
R. CavalliCelebrity0.41Runway−0.21
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Brambilla, M.; Badrizadeh, H.; Malek Mohammadi, N.; Javadian Sabet, A. Analyzing Brand Awareness Strategies on Social Media in the Luxury Market: The Case of Italian Fashion on Instagram. Digital 2023, 3, 1-17.

AMA Style

Brambilla M, Badrizadeh H, Malek Mohammadi N, Javadian Sabet A. Analyzing Brand Awareness Strategies on Social Media in the Luxury Market: The Case of Italian Fashion on Instagram. Digital. 2023; 3(1):1-17.

Chicago/Turabian Style

Brambilla, Marco, Hoda Badrizadeh, Narges Malek Mohammadi, and Alireza Javadian Sabet. 2023. "Analyzing Brand Awareness Strategies on Social Media in the Luxury Market: The Case of Italian Fashion on Instagram" Digital 3, no. 1: 1-17.

Article Metrics

Back to TopTop