Received: 09/08/2024 --- Accepted: 09/30/2024 --- Published:  10/21/2024

EYE-FIXATION STRATEGIES AND BRAND LOVE: GENDER INFLUENCE IN GENERATION Z

ESTRATEGIAS DE FIJACIÓN OCULAR Y AMOR HACIA LA MARCA: INFLUENCIA DEL GÉNERO EN LA GENERACIÓN Z

 Coral Cenizo: San Pablo CEU University. Spain.

correoelectronico@dominio.com 

 

How to cite this article:

Cenizo, Coral (2024). Eye-fixation strategies and brand love: gender influence in Generation Z [Estrategias de fijación ocular y amor hacia la marca: influencia del género en la Generación Z]. Revista de Comunicación de la SEECI, 57, 1-37. https://doi.org/10.15198/seeci.2024.57.e893 

ABSTRACT

Introduction: This study explores gender differences in the visual processing of images and their relationship with brand love among Generation Z on social media. Methodology: A mixed-method approach combining eye-tracking and surveys was employed. Results: Complex backgrounds divert attention from the product, whereas abstract backgrounds focus the gaze on the product. The presence of humans, particularly celebrities, reduces attention on the products. Brand elements and identifiers are often overlooked in favor of contextual details. The relationship between visual fixation variables and brand love varies significantly between men and women, although a homogenization of genders is observed in certain variables. Additionally, a higher number of fixations and more dynamic visual exploration are positively correlated with brand love, while longer fixation duration is negatively associated. Discussion: The findings suggest that while gender differences in visual processing persist, these are evolving toward a convergence in cognitive strategies between men and women in Generation Z. Furthermore, the study emphasizes the importance of active visual dynamism in fostering an emotional connection with brands, with nuanced considerations about the effectiveness of prolonged attention. Conclusion: The findings highlight the need to adapt marketing strategies for Generation Z, taking into account the new dynamics of visual processing and their impact on emotional connection with brands.

Keywords: visual attention; consumer behavior; gender differences; Generation Z; digital marketing; neuromarketing.

RESUMEN 

Introducción: Este estudio explora las diferencias de género en el procesamiento visual de imágenes y su relación con el amor hacia la marca en la Generación Z en las redes sociales. Metodología: Se utiliza una metodología mixta que combina seguimiento ocular y encuestas. Resultados: Fondos complejos desvían la atención del producto, mientras que fondos abstractos concentran la mirada en el producto. La presencia de figuras humanas, especialmente celebridades, reduce la atención en los productos. La marca y sus elementos identificativos suelen ser ignorados en favor de detalles contextuales. La relación entre las variables de fijación visual y el amor hacia la marca varía significativamente entre hombres y mujeres, si bien se percibe una homogeneización de géneros en ciertas variables. Así mismo, un mayor número de fijaciones y un mayor dinamismo en la exploración visual están positivamente correlacionados con el amor hacia la marca, aunque un aumento en la duración de las fijaciones tiene una asociación negativa. Discusión: Se sugiere que, aunque persisten diferencias de género en el procesamiento visual, estas están evolucionando hacia una convergencia en las estrategias cognitivas de hombres y mujeres de la Generación Z. Además, se destaca la importancia de un dinamismo visual activo en la conexión emocional con las marcas, pero introduciendo matices sobre la efectividad de la atención prolongada. Conclusión: Los hallazgos sugieren la necesidad de adaptar las estrategias de marketing para la Generación Z, considerando las nuevas dinámicas de procesamiento visual y su impacto en la conexión emocional con las marcas.

Palabras clave: atención visual; comportamiento del consumidor; diferencias de género; generación Z; marketing digital; neuromarketing.

1.     INTRODUCTION 

In the contemporary digital ecosystem, social networks have established themselves as key platforms for the mass dissemination of visual and textual information. This environment, characterized by a constant and overwhelming flow of content, poses significant cognitive challenges, especially in terms of information processing. The information overload experienced by users can exceed their cognitive capacity, causing mental fatigue and affecting the quality of their attention and memory (Parra-Medina & Álvarez-Cervera, 2021; Roetzel, 2019). Generation Z, which consumes digital media intensively and simultaneously, faces these challenges in a relatively severe way (IPMARK, 2023). This highlights the relevance of the concept of selective attention (SA).

Previous studies have shown that SA allows individuals to filter and prioritize certain visual stimuli over others (Broadbent, 1958; Cherry, 1953). Still, factors such as items in working memory (WM) (Eghdam et al., 2020), frontal eye field, long-term priming and parallel processing of objects (Bichot & Schall, 1999), visual markup (Watson et al., 2003), the location of a target (Theeuwes & Burg, 2007), or the observer's experience and history (Theeuwes, 2018), significantly influence this visual selection.  

In this regard, gender also represents an important influencing factor of SA apparent in various contexts. Thus, for example, females show greater range in ERP components in attention-shifting tasks, indicative of early maturation in brain areas related to visual spatial attention (Feng et al., 2011). In contrast, men outperform women on tests of visual perception in midlife and older, suggesting a more prominent decline in women (Shaqiri et al., 2016).

In the specific field of advertising, there are also significant differences in how men and women process visual stimuli. For example, men show variations in their attention and attitudes towards advertisements, while women do not (Boscolo et al., 2020). In erotic contexts, men focus more on opposite-sex figures, whereas women distribute their attention more evenly (Lykins et al., 2008). 

These findings reflect how gender roles and expectations influence the response to visual stimuli, underscoring the importance of gender in the study of SA, as has already been evidenced in other contexts (Barrientos-Báez, 2022). However, most studies to date have focused on traditional contexts and adult populations, leaving a significant gap in understanding how these differences are manifested in Generation Z within the specific environment of social networks. 

In addition, there has also been no in-depth study of the consequences that these possible differences have in terms of marketing and, more specifically, with respect to brand love (BLV), understood as the intense and lasting emotional relationship that a customer develops with a brand, transforming initial satisfaction into a deep affective bond that goes beyond mere loyalty (Fournier, 1998; Carroll & Ahuvia, 2006).

1.1.         Visual information processing

In today's digital ecosystem, social networks have become true repositories of information and images, with a huge volume of content being published on a daily basis. Every second, thousands of images, videos, texts and other types of data are shared by users around the world, contributing to a constant and overwhelming flow of information (Metricool, 2023).

This visual and textual saturation not only reflects the diversity and dynamism of contemporary communication, but also poses significant challenges in terms of cognitive processing.

Indeed, the amount of visual and textual information that users must process simultaneously can exceed their cognitive capacity, generating mental fatigue and reducing information processing efficiency (Roetzel, 2019). This phenomenon not only affects the quality of attention and memory but can also influence the user's overall satisfaction with the social networking experience (Parra-Medina & Álvarez-Cervera, 2021). For Generation Z, this overload may be especially severe, given that their digital media consumption is high and characterized by extended exposure to multiple platforms at the same time (IPMARK, 2023).

In this sense, the concept of SA has been widely used in the field of cognitive psychology to explain how individuals handle and process this overwhelming amount of stimuli to which they are exposed in their environment.

The SA supports that human beings do not uniformly process all available stimuli; instead, they focus their attention on certain specific elements while filtering out or ignoring others (Broadbent, 1958; Cherry, 1953). This selective approach to attention allows people to manage the large amount of information to which they are exposed, prioritizing what is most relevant and minimizing other information (Treisman, 1965). 

In this context, several studies have shown that specific visual characteristics play a crucial role in attracting human attention.

In particular, the object orientation within an image emerges as a dominant factor for visual attentional engagement, suggesting that humans may be biologically biased to become responsive to the arrangement and alignment of visual elements (Eghdam et al., 2020). Other studies have shown that visual attention is also influenced by the presence of unique objects (Jeck et al., 2019), which may imply that the human brain is tuned to detect anomalies or novelty in the visual environment. Also, the inclusion of humans increases visual attractiveness (Al-Maqbali et al., 2022). Indeed, Morin-Duchesne and Kennedy (2015) highlight that faces and gaze directions are able to attract and maintain attention, indicating a willingness to process socially relevant information.

However, in their classic formulation, SA theories were developed and validated in contexts that reflect the cognitive and environmental dynamics of generations prior to the advent of pervasive digital technologies. In contrast, generations immersed in these technologies-such as Generation Z and beyond-have grown up in a very different context, which may have led to a different adaptive process that could influence how they focus their attention and which elements they choose to filter or ignore.

1.1. Gender in the visual selection process

SA in the visual system is not random, but is influenced by a number of factors, such as prior knowledge of the visual setting and the defining characteristics of the target (Serences & Yantis, 2007), external feedback (Libera & Chelazzi, 2006), rewards (Chelazzi et al., 2013), or statistical and informational aspects (Dayan et al., 2000), among others. In other words, attention becomes an active and dynamic mechanism, which not only corresponds to intrinsic characteristics of the stimulus, but it is also shaped by social and cultural standards (Merritt et al., 2007). 

In this sense, gender is also an important factor influencing SA, as it has been documented in several empirical studies, which reinforces the need to consider this factor in the analysis of selective attention. For example, it has been shown that females tend to show greater amplitude in ERP components during visual attention switching tasks, which could be related to broader signaling effects and earlier maturation in brain areas involved in visual spatial attention (Feng et al., 2011).

These differences are not only linked to biological factors, but also to evolutionary and cultural influences that have shaped cognitive functions differentially between sexes (Vanston & Strother, 2017). In addition, it has been observed that men tend to perform better on tests of visual perception in middle-aged and older adults, suggesting a greater decline in women's performance as they get older (Shaqiri et al., 2016).

The literature also indicates that there are differences in how men and women respond to visual stimuli in specific contexts. Studies on visual attention and attitudes toward advertising suggest that men show significant differences in their visual attention and attitudes toward advertisements compared to women, who show no such variations (Boscolo et al., 2020). This could reflect a differential bias in how each gender processes and responds to visual stimuli, possibly reflecting deeply ingrained gender roles and expectations.

In this regard, research has shown that men pay more attention to opposite-sex subjects in erotic and non-erotic images, whereas women distribute their attention more equally between same-sex subjects, which reinforces the idea that there are significant gender differences in the way visual stimuli are processed, both in terms of erotic valence and overall attention (Lykins et al., 2008).

Although the existing literature has documented gender differences in the processing of visual information, most of these studies focus on traditional contexts or adult populations. However, there is a notable lack of research examining how these gender differences manifest themselves in Generation Z and, particularly, in the context of BLV. This gap in the literature is critical to better understand gender differences in Generation Z and their implication for the consumption and production of visual content on social platforms.

1.2.         Brand Love (BLV)

BLV is defined as an intense and lasting emotional connection that a consumer establishes with a brand, manifested through feelings of affection, passion and loyalty (Fournier, 1998; Carroll & Ahuvia, 2006). This concept is intertwined with brand attitude, as it directly influences consumer perceptions and behaviors, thus promoting a positive disposition and lasting commitment to the brand.

Several studies have explored the relationship between visual patterns and brands, demonstrating how visual attention can play a crucial role in creating and strengthening this emotional bond. Eye fixations, which are defined as the length of time the eyes remain fixed on a given point, are essential for analyzing visual attention. Their duration and frequency reflect the level of attention a person directs toward certain visual elements in an advertisement or image (Sharma & Dubey, 2014).

Previous research has shown that fixation frequency is positively related to brand recognition, although the duration of these fixations does not always have the same impact (Zhou & Xue, 2021). This variability suggests that increased visual exposure, facilitated by recurrent fixations, may enhance memory and, consequently, brand recall, which is critical for cultivating BLV (Pertzov et al., 2009).

However, the effectiveness of these visual patterns in promoting AM may be subject to several modulating factors. Rizvi (2020) introduces the concept of Brand Visual Eclipse (BVE), which describes how the appearance of celebrities in advertisements can divert attention away from the brand, diminishing its visibility and, therefore, its ability to generate BLV. This phenomenon can complicate the relationship between visual attention and advertising effectiveness by altering attitudes towards the brand and the ad itself (Felix & Borges, 2014).

Likewise, it has been found that redirecting the first fixation to a specific option does not always affect the probability of that option being selected. This reveals that, although the total timing of fixations is conditioned by the purpose of the decision, it is also influenced by the preference formation process (Laan et al., 2015). 

Another essential visual factor in the dynamics of visual perception and, therefore, in the way consumers process information related to a brand, are saccades, defined as involuntary movements that refocus the viewer's gaze (Giannotto, 2009).

The relevance of saccades in the context of branding becomes evident when considering their ability to compress the perception of space, time and number, suggesting the existence of a common perceptual scale that is reset before each saccade (Burr et al., 2010). The underestimation of perceived number during a saccade, especially in complex visual contexts, reinforces the idea that saccades affect not only the spatial but also the quantitative perception of items in an advertisement (Binda et al., 2011).

This effect is intensified when considering that saccade preparation enhances the processing of high spatial frequency information, which implies that transacadic integration, or the way the brain combines information before and after a saccade, significantly influences the perception and processing of the details of a brand image (Li et al., 2016). 

In addition, saccades are associated with cognitive suppression that increases reaction times in comparative judgments, suggesting that complex cognitive evaluations, such as the assessment of a mark in a dynamic visual environment, may be altered by the interference that occurs in the dorsal pathway during a saccade (Irwin & Thomas, 2007). 

Finally, saccades are linked to anticipation and enhanced perceptual performance, indicating that the generation of a saccade is intimately related to changes in attention, a crucial aspect in BLV (Rorden et al., 2002). 

2.     OBJECTIVES 

The main objective of this research is to analyze gender differences in the visual processing of brand stimuli among Generation Z youth, as well as to examine how visual exploration patterns influence the formation of brand love in this group. Ultimately, through this study, it seeks to better understand gender dynamics in the context of visual processing, taking into account the particularities of the contemporary digital environment.

The following hypotheses are proposed:

• H1: The frequency of eye fixations has a positive impact on BLV, such that a higher number of fixations is associated with an increase in the consumer's emotional attachment to the brand.
• H2: The duration of eye fixations negatively influences BLV, suggesting that prolonged fixation times may reduce the consumer's level of affection towards the brand.
• H3: The number of eye saccades is positively related to Brand Love, such that a higher number of saccades is associated with an increase in the consumer's emotional attachment to the brand.

This relationship of hypotheses is shown graphically in Figure 1.

Figure 1. 

Conceptual framework of the study.

Source: Elaborated by the authors.

3.     METHODOLOGY 

This research was designed with the aim of exploring possible gender differences in the visual patterns presented by Generation Z with respect to social network images and analyzing their implications for BLV.

For this purpose, a study structured in two phases was carried out: the first phase consisted of an eye tracking experiment and the second phase consisted of a moderated regression analysis. 

The same sample was used in both phases. However, in order to ensure the relevance and applicability of the results obtained, meticulous selection criteria were established for the participants: 1) a specific age range was defined, corresponding to Generation Z, i.e., born between 1996 and 2012 (Dimock, 2019). 2) it was considered essential that participants had a basic familiarity with social networks, in order to avoid possible biases (Childers et al., 2001; Francis & Hoefle, 2018).

For the recruitment of participants, a mixed sampling strategy was chosen. Initially, the social network X was used to contact potential subjects. Purposive sampling was the predominant technique at this stage, selecting individuals who explicitly matched the inclusion parameters of the study. Direct interaction with candidates through private messages and comments facilitated effective and personalized communication, which contributed significantly to improved participation rates.

Subsequently, snowball sampling was implemented, leveraging already recruited participants to expand the sample. Initial participants recommended other individuals within their networks who met the study criteria, which provided access to a more diverse group potentially interested in participating (Goodman, 1961; Dragan & Isaic-Maniu, 2022; Bailey, 2019). 

This technique was effective in achieving an optimal number of participants -30 individuals, 15 men and 15 women, all of them Spanish-, in line with the recommendations of the Nielsen Norman Group (2021), which suggests between 20 and 40 participants for eye tracking studies. 

The demographic characteristics of the sample are shown in detail in Table 1, offering a breakdown by age, gender, previous experience with technologies and social networks, among other relevant factors for subsequent data analysis.

Table 1. 

Demographic characteristics of the sample.

VARIABLE	CATEGORY	N	(%)
Gender	Man	15	50%
	Woman	15	50%
Age	15-19	11	36.66%
	20-24	10	33.33%
	25-30	9	30%
Occupation	Worker	19	63.33%
	Student	11	36.66%
Frequency of use of social networks	More than once a day	18	60%
	Once a day	6	20%
	Once a week	4	13.33%
	Once a month	2	6.66%

Source: Elaborated by the authors.

3.1.         Eye tracking experiment

In order to ensure the integrity and quality of the data collected during the eye tracking experiment, several crucial steps were taken to ensure the scientific accuracy and relevance of the results obtained.

First, the environment in which the eye tracking sessions were to be conducted was prepared. For this purpose, a specific space designed to minimize any type of external distraction that could influence the visual behavior of the participants was selected. This space was conditioned with adequate lighting and ergonomic furniture, seeking to ensure that participants were comfortable and that their interaction was focused exclusively on the stimuli presented.

Second, a pilot study was conducted with three individuals who were not part of the main sample before proceeding with full-scale data collection. This was essential to validate the experimental setup, allowing us to adjust the layout of the space, verify the clarity of the instructions provided to the participants, and confirm the correct functioning of the eye tracking equipment.

Third, prior to the start of the eye-tracking sessions, each participant received a detailed explanation of the study procedure. This information included a description of the specific objectives of the research and how each individual's participation would contribute to the advancement of knowledge in the area under study. In addition, a detailed description was provided about the types of data that would be collected and how they would be analyzed to meet the objectives of the study. 

Likewise, to ensure the ethics of the study, each participant signed an anonymous informed consent form. This document not only detailed the study process and reaffirmed the willingness of participation, but also underscored the confidentiality with which personal data would be treated, ensuring that only the research team would have access to them for purposes specifically related to the study.

Once these measures were established, the eye tracking experiment was carried out with the selected sample, using the Tobii TX 300. Each participant underwent individual calibration using a 9-point test, which allowed us to adjust the software to the ocular particularities of each person, thus ensuring the accuracy of the data collected.

During the experiment, participants were shown fifteen carefully selected images from social networks. To ensure the visual consistency of this content, and to avoid possible biases motivated by stylistic differences, visual content published by a single brand was used.

In this case, the French brand Louis Vuitton was chosen for three reasons: 1) Louis Vuitton is one of the most recognized and valued luxury brands worldwide. Its prominence in the global market ensures that it is known to a broad spectrum of consumers. This allows the results of the study to have greater applicability and relevance in terms of consumer behavior and brand recognition; 2) luxury brands prioritize visually sophisticated and engaging content in their marketing campaigns (Jin & Ryu, 2019; Lee et al., 2018), thus ensuring the quality and relevance of the images chosen; 3) finally, Generation Z is showing a prominent interest in luxury brands to the point that much of the sector's current consumption falls on this cohort. In this regard, the French brand leads the Luxury & Premium 50 ranking of Brand Finance (2023), which is an indication of its relevance in this sector.

The selected images were published by Louis Vuitton on its social profiles -X, Instagram and Facebook- between July 2023 and December 2023. During this period, the brand published a total of 135 posts on this social media platform, so the selected sample represents 11.11% of the total. 

To ensure the heterogeneity of the content, three types of photographs were chosen: 1) photographs with brand products; 2) photographs with anonymous models showing brand products; 3) photographs with House Ambassadors of the brand. The breakdown of the final images used in the eye tracking experiment is detailed in Annex 1.

3.1.1.     Analysis of variables

Each eye tracking session was limited to a maximum of one minute per image, recording in detail the eye movements of the participants. More specifically, three ocular metrics were taken into account: Total Number of Fixations (TNF), Average Fixation Duration (AFD) and Mean Number of Saccades (MNS), as they are the most determinant in the previous literature (Jacob & Karn, 2003; Goldberg et al., 2002; Renshaw et al., 2003).

During the experiment, a fixation was considered each time the participants' eyes remained immobile for at least a certain period of time -between 100 and 200 milliseconds, following the established standards. As for the AFD, this was obtained by first calculating the duration of each individual fixation and then averaging these durations across all fixations recorded for a participant. Finally, MNS was calculated by summing all saccades recorded during the observation of a stimulus. 

Each of these metrics was averaged per participant, allowing for a broader and more representative view of visual behavior throughout the experiment.

3.2.         Moderated regression analysis

To carry out the regression analysis, the data obtained during the eye tracking experiment were complemented with a post experimental survey. 

As during the first phase of the study, the post-survey was also subjected to a pretest with a small group of individuals (N = 4) who were not part of the main study sample, the main objective of this pretest was to assess the comprehension of the questions asked and to ensure that the language used was clear and precise for the participants. During this preliminary phase, possible ambiguous terms were identified and questions that could induce biased responses or that were not clearly understood by the individuals in the pretest group were reformulated (Ifinedo, 2011; Alegre & Chiva, 2013).

Once the questionnaire was adjusted after the pretest, it was given in physical format, immediately after the participants completed the eye tracking experiment. Considering that the study group included individuals of different nationalities, it was decided to offer the questionnaire in two languages: Spanish and English to maximize the comprehension of the questions and minimize the risk of misinterpretation due to language barriers. The original version of the questionnaire was written in Spanish, and its translation into English was carried out by a professional translator, thus ensuring accuracy and semantic equivalence between both versions of the questionnaire.

Following collection of the completed questionnaires, a thorough review of each questionnaire was conducted to verify the completeness and accuracy of the responses. All 30 questionnaires received were confirmed to be complete and error-free, which is a positive indicator suggesting that participants adequately understood the questions and were engaged in the response process.

Additionally, to address possible non-response bias, a comparative analysis was carried out following the methodology proposed by Armstrong and Overton (1977). This analysis consists of comparing the responses obtained at different times during the data collection period to identify if there are significant variations that could indicate a bias. In this case, the comparison of questionnaires collected at different stages of the process did not reveal significant discrepancies.

Finally, analysis of the data collected through the survey was performed using IBM SPSS Statistics 25 software.

3.2.1.     Analysis of variables

The BLV variable was measured using the scale developed by Carroll and Ahuvia (2006), a tool widely validated in the scientific literature to assess the emotional affection and personal connection that an individual feels towards a brand (Baena, 2016). The use of this scale in the study ensured that the content of the instrument was valid (Cronbach, 1971).

Carroll and Ahuvia's scale has several dimensions of BLV, such as passion for the brand or emotional connection, as can be seen in Table 3. To capture the responses related to this variable, a 5-point Likert scale was used, where 1 corresponded to “strongly disagree” and 5 to “strongly agree”.

Table 3. 

Constructs and measures used in the research.

Source	Item	Construct
Carroll and Ahuvia (2006)	BLV1	The brand is wonderful.
	BLV2	The brand makes me feel good.
	BLV3	The brand is totally awesome.
	BLV4	I have a neutral feeling towards the brand.
	BLV5	The brand makes me very happy.
	BLV6	I love the brand.
	BLV7	I don't have any special feelings towards the brand.
	BLV8	I love the brand.
	BLV9	I am passionate about the brand.
	BLV10	I am very connected to the brand.

Source: Elaborated by the authors.

On the other hand, the dependent variables in this research were the visual metrics captured during the eye tracking experiment: TNF, AFD and MNS. Additionally, and given that the research focuses on Generation Z, a control variable was introduced, in this case age. With this, the goal is to obtain a more precise estimate of the effect of the independent variables on the dependent variable, ensuring that the resulting associations are not simply the result of differences in age.

3.2.2.     Measurement model

Once the items were designed, an Exploratory Factor Analysis (EFA) was performed to evaluate the factor structure of the instrument and ensure the reliability of the constructs that were identified. The SPSS software was used to carry out this analysis, using principal component analysis with Varimax rotation. The results are shown in Table 4.

First, Bartlett's test of sphericity and the Kaiser-Meyer-Olkin (KMO) test were performed to determine the sample adequacy of the data. The KMO value obtained was 0.909, a result well above the recommended minimum threshold of 0.6, indicating excellent sample adequacy to proceed with the factor analysis. This result suggests that the data are sufficiently robust to extract significant factors. Also, Bartlett's test of sphericity was statistically significant (<0.001), which allowed the rejection of the hypothesis that the variables are orthogonal in the factor space, indicating that the correlations between the variables are sufficiently high to justify the use of factor analysis.

The reliability of the instrument was evaluated using Cronbach's alpha. In this case, the value obtained for all constructs (0.980) exceeded the value of 0.7, which is indicative of high reliability, as established by Nunnally (1978). Additionally, the item-total correlation statistics also exceeded the 0.3 threshold for all constructs being analyzed, providing further evidence of the instrument's robustness and consistency, as noted by Hair et al. (2008).

The constructs demonstrated a composite reliability (CR) above the minimum desirable threshold of 0.60, which, according to Bagozzi and Yi (1988), is indicative of good internal consistency among the items that make up each construct.

Convergent validity, assessed through the analysis of factor loadings and average variance extracted (AVE), showed that the factor loadings of each item exceeded the threshold of 0.70, indicating a high correlation between the items and their respective construct. In addition, the AVE values were greater than 0.50, which confirms that most of the variance of the items is explained by the constructs and not by random errors, following the criteria established by Fornell and Larcker (1981).

Table 4. 

Elements of measurement and validity assessments.

Item	Factor loadings	Cronbach's alpha	Composite Reliability (CR)	Average Variance Extracted (AVE)	Item-Total Corrected Correlation
BLV1	0.925	0.980	0.983	0.856	0.907
BLV2	0.853				0.820
BLV3	0.945				0.932
BLV4	0.949				0.935
BLV5	0.880				0.852
BLV6	0.960				0.949
BLV7	0.919				0.898
BLV8	0.902				0.879
BLV9	0.952				0.939
BLV10	0.961				0.951

Note: All factor loadings are significant at p < 0.001. Method of extraction: Analysis of the main components.

Source: Elaborated by the authors.

4.     RESULTS 

4.1.         Eye tracking experiment

Through the analysis of the scan paths and heat maps extracted from the eye tracking experiment, a structured division of the images was made into three Areas of Interest (AOIs), comprising: 1) background; 2) human figure; 3) products. This classification has allowed a detailed and comparative analysis of how Generation Z users visually interact with each section. 

Figure 2 provides a graphical representation of these areas in the ID10 image.

Figure 2.

Distribution of AIPs in post ID10.

Source: Louis Vuitton.

The results derived from the study indicate significant differences in the amount of attention and time spent by users on each of the AOI

According to the data reflected in Table 2, the human figure is established as the area of maximum visual interest, being the point where participants fixed their gaze for the longest time. In contrast, backgrounds were identified as the area of least visual interest.

Table 2. 

Visualization percentage and duration of the AOI.

	% of participants viewing the AIP	Average total fixation duration
Human figures	100%	10.68
Products	62.32%	1.04
Background	30.45%	0.76

Source: Elaborated by the authors.

4.1.1.    Area of interest 1: Backgrounds

The results of the eye-tracking experiment show that images that place the product on backgrounds with a lot of contextual information tend to divert attention to secondary elements of the environment, reducing fixation on the main product. In contrast, images that present the product against an abstract background or one devoid of contextual information are more effective in focusing attention. 

This difference is seen not only in attractiveness but also in retention, as can be seen in the heat maps presented in Figure 3. On the contrary, participants' attention was equally distributed between the surrounding landscape and the product, indicating that participants divided their attention between secondary and main elements. In contrast, in the image on the right - in which contextual information is lower - the areas of higher temperature are concentrated on the main product and to a lesser extent on the surrounding environment.

Figure 3. 

Heat maps of images ID01 and ID02.

Source: Louis Vuitton.

According to the results here, Generation Z could be developing switch-tasking cognitive strategies -which allow them to quickly switch from one focus of attention to another (Napier, 2018)- to efficiently deal with information overload (Chamorro-Premuzic, 2014; Sweller, 1988). Thus, attentional dispersion in the presence of complex backgrounds could be an adaptive strategy to grasp the essence of a scene holistically, allowing individuals to extract relevant information from different parts of the visual environment without spending too much time on a single element.

However, this strategy could also have implications for the depth of information processing. By dispersing attention among multiple elements, Generation Z may be sacrificing the ability to stay focused on a single point for long periods of time, which could affect long-term memory and depth of understanding of the information being processed, as shown in previous studies (Rogers & Monsell, 1995; Gopher et al., 2000; Mayr & Kliegl, 2000).

4.1.2.    Area of interest 2: Humans

Eighty percent of the images that were analyzed had a human presence. In this regard, the results of the eye-tracking experiment reveal specific patterns in the visual attention directed towards photographs that include models, especially when they are well-known celebrities.

As illustrated in Figure 4, when the product is presented together with human elements, there is a significant decrease in fixation. In these cases, participants' attention tends to be dispersed towards the physical characteristics or facial expressions of the people present in the image, which competes directly with the product for visual attention and reduces the time of observation focused on the latter.

In contrast, images that show the product in isolation or without the inclusion of human elements manage to retain attention for longer periods of time, favoring a more detailed observation. Here, the heat map shows a more intense and sustained focus on the product itself, with a clear decrease in dispersion to other areas of the image. This behavior suggests that the absence of bodily stimuli allows a more effective focus on the main object, enhancing its visibility and highlighting its importance in the viewer's visual perception.

Figure 4. 

Heat maps of images ID03 and ID04.

Source: Louis Vuitton.

The results suggest that human presence in social network images acts as a crucial component of visual salience for Generation Z, meaning that these elements automatically stand out and engage attention as a priority (Treisman & Gelade, 1980; Desimone & Duncan, 1995).

From a neurological perspective, this phenomenon is logical. Humans have developed a natural predisposition to pay attention to other humans, especially their faces and facial expressions (Schindler & Bublatzky, 2020; Palermo & Rhodes, 2007). This ability to quickly detect and interpret faces is a crucial adaptation for survival, as it facilitates nonverbal communication, understanding emotions, and identifying potential threats or allies in the environment (Adams et al., 2017). This visual attention mechanism has been maintained throughout evolution and is still relevant in modern contexts, where social interactions and emotional cues remain critical for everyday life (Pritsch et al., 2017).

However, in the case of Generation Z, this natural predisposition to focus on human faces and bodies is amplified by their generational characteristics.

Indeed, individuals not only perceive and interpret information based on its intrinsic characteristics, but also according to its meaning and relevance within a social context (Cantor, 1990; Smith & Collins, 2009). For Generation Z, which is highly attuned to social dynamics and collective consciousness (Singh, 2014; Sakdiyakorn et al., 2021), images that include human figures may resonate more deeply because they represent interactions, emotions, and situations that are part of their everyday lives.  

These human stimuli are not only processed visually, but also trigger cognitive and emotional associations that reinforce the relevance of the content. Thus, an image showing a person using a product can be interpreted not only in terms of the product's usefulness, but also in terms of the experience and human connection involved in its use, which amplifies its emotional impact. Thus, the presence of people in images can work as an implicit validator of the content, suggesting that it is worthy of attention and emotionally relevant.

In the images starring celebrities, participants showed a more noticeable tendency to focus on the faces of these celebrities, relegating the brand's products to the background in terms of attention. 

This phenomenon is clearly observable in Figure 5. In general, the image on the left shows areas of greater visual focus. However, the element that attracts almost all of the recorded fixations is the face of the actress Emma Stone. In contrast, the dress worn by the actress -designed by Louis Vuitton for the premiere of the film “Poor Things” in New York- hardly receives any attention.

In contrast, the image on the right in the same image shows a different attentional behavior when the models are not well-known people. In this case, both the wardrobe and the Louis Vuitton products captured the attention of the participants in a more balanced way, indicating that the absence of a celebrity allows the brand elements to gain more visual relevance.

Figure 5.

Heat maps of images ID05 and ID06.

Source: Louis Vuitton.

This effect is intensified in close-up photographs, where the celebrity's face dominates the visual attention. Figure 6 illustrates this phenomenon clearly: in the image on the left, the face of actress Ana de Armas is the main focus of the participants' attention, while the rings and earrings she wears go virtually unnoticed. In contrast, the image on the right, which shows an anonymous model, shows a more equal distribution of visual fixation between the model's face and the products she is wearing, although, in this case, the necklace she is wearing does not attract the same amount of attention.

Figure 6. 

Heat maps of images ID07 and ID08.

Source: Louis Vuitton.

This finding is consistent with the idea of BVE enunciated by Rizvi (2020), according to which the presence of celebrities in advertising contexts eclipses the brand. This diversion of attention not only limits product visibility but can also hinder the relationship between visual attention and advertising effectiveness (Felix & Borges, 2014). In this context, the visual predominance of the actress's face could reduce the positive perception of the product, as the focus of attention shifts from the brand to the celebrity, affecting the connection that the ad aims to establish between the audience and the brand.

On the other hand, the greater fixation observed on the celebrity's face could also be interpreted as an indication of confusion on the part of the viewer. In situations where the audience spends a disproportionate amount of time fixating on a specific element, as in this case, it may suggest that the visual message is not being clearly understood (Goldberg & Kotval, 1999; Just & Carpenter, 1976). The high fixation on Emma Stone's face could indicate that participants are either trying to process the relevance of the celebrity within the context of the advertisement or to identify the actress in the image, which could generate ambiguity as to the main focus of the advertising message.

4.1.3.    Area of interest 3: The brand

Regarding AIP3, it is striking that, in many cases, the participants' attention was not focused on the identifying elements of the brand that appear in the images. On the contrary, the visual concentration was derived towards other contextual details. 

The heat map analysis of image ID14 illustrates this disconnect between brand and visual attention. The heat map in Figure 7 shows a dispersion of fixations, with a remarkable focus on the model's face and wardrobe, while the bag -despite being designed with a characteristic and identifying Louis Vuitton pattern-, appears surrounded by areas of low visual intensity, represented in cold tones.

Figure 7. 

ID14 image heat maps.

Source: Louis Vuitton.

Therefore, for Generation Z, the mere presence of brand identification elements is not enough to ensure that they become the focus of visual attention. 

The particular skepticism that this generation exhibits toward advertising elements-differential from previous cohorts (Mangleburg & Bristol, 1998; Conlin & Bauer, 2021; Gajanova et al., 2023)-may be causing young people of this generation to subconsciously prioritize those visual elements they consider more relevant or emotionally resonant, relegating to the background, or even ignoring, traditional branding elements, such as logos or specific products, by way of ad-blocking (Sádaba & Sánchez-Blanco, 2019).

This behavior can also be linked to this generation's growing preference for content perceived as more authentic or experiential, rather than that which is directly associated with brand promotion (Bilonozhko & Syzenko, 2020; Singh, 2023). Thus, the lack of attention to logo or product can be interpreted not only as a competition between visual stimuli, but also as an indication of a change in consumption priorities and in the way this generation interacts with advertising messages.

4.2.         Moderated regression analysis

4.2.1.    Descriptive analysis

TNF has a mean of 38.387 fixations, suggesting that, on average, participants made about 38 fixations during the experiment. The high standard deviation (18.288) indicates considerable variability in the number of fixations between individuals, with some making few fixations (minimum 10.26) and others many more (maximum 64.90). 

The AFD has a mean of 0.394 seconds, indicating that, on average, participants keep their eyes on a point for slightly less than half a second. The variability, indicated by the standard deviation of 0.209 seconds, is moderate, with some fixations as short as 0.10 seconds and others much longer, up to 0.70 seconds. 

The MNS, with a mean of 27.915, indicates that participants made, on average, about 28 rapid eye movements –saccades- during the experiment. The standard deviation of 13.201 suggests that there is considerable dispersion in the number of saccades among participants, like the NFT. 

Descriptive data are presented in Table 5.

Table 5. 

Descriptive statistics

	Minimum	Maximum	Mean	Standard deviation
TNF	10.26	64.90	38.387	18.288
AFD	0.10	0.70	0.394	0.209
MNS	10.48	53.49	27.915	13.201
BLV	1.398	4.611	3.176	0.877

Source: Elaborated by the authors.

Regarding visual metrics, females present a significantly higher NFT (44.15) compared to males (32.62). This suggests that, on average, women perform more visual fixations than men when looking at a stimulus, which could indicate a more detailed or thorough visual exploration by women. However, men have a higher AFD (0.55 seconds) compared to women (0.24 seconds), implying that men tend to keep their gaze fixed on a point for longer than women.

Similarly, males make a greater number of saccades (32.42), indicating a more dispersed or less focused visual exploration, while females, with a lower number of saccades (23.41) could be performing a more concentrated exploration in specific areas of the visual stimulus.

The gender differences in visual patterns are shown in Table 6.

Table 6. 

Gender differences in visual patterns.

		TNF	AFD	MNS
Gender	Man	32.62	0.55	32.42
	Women	44.15	0.24	23.41

Source: Elaborated by the authors.

4.2.2.    Regression analysis

Before performing the regression analysis, a Chow test was carried out to evaluate whether there were significant statistical differences in the relationship between the independent variables -AFD, TNF and MNS- and the dependent variable -BLV- between the different demographic groups considered in the study -men and women.

The test results -presented in Table 7- confirmed that the relationship between AFD, TNF and MNS and brand love is not uniform among the groups. 

In the case of TNF (F = 5.618; p = 0.009) the sum of squares of the contrast is 1.167, indicating that a wide variability of BLV is explained by the differences between the groups. The root mean square of the contrast (0.583) is relatively high, suggesting that a significant amount of the observed variability in MA can be attributed to differences in visual fixation patterns between groups. In turn, the root mean square of the error (0.104) is low compared to the root mean square of the contrast, indicating that a relatively small portion of the total variability is due to internal variability within groups.

Regarding AFD (F = 29.988; p = 0.000) the sum of squares of the contrast (13.875) and the corresponding root mean square (6.937) indicate a large variability explained by differences between groups. This suggests that, as in NFT, a considerable part of the variability in BLV is related to differences in the influence of AFD between groups. On the other hand, the sum of squares of the error (6.015) and its root mean square (0.231) reflect within-group variability that is not explained by differences in the regression coefficients.

Finally, in the MNS, the F-statistic is 2.982 with a p-value of 0.068. This significance value is slightly above the common threshold of 0.05, indicating that no statistically significant differences in the relationship between MNS and BLV between the groups can be stated with 95% confidence. Although the results suggest a trend toward differentiation-given that p is close to 0.05-the evidence is not strong enough to reject the null hypothesis that there are no significant differences.

Table 7. 

Results of the Chow Test.

	Sum of squares of the contrast	Root mean square of the Contrast	F	Sig.	Sum of squares of the error	Root mean square of the error
TNF	1.167	0.583	5.618	0.009	2.700	0.104
AFD	13.875	6.937	29.988	0.000	6.015	0.231
MNS	1.070	0.535	2.982	0.068	4.663	0.179

Source: Elaborated by the authors.

Once the significant differences between the analysis groups were verified, regression analysis was performed. For this purpose, three models were carried out: Model 1 included only the control variable. Model 2 included the independent variables and the dependent variable. Finally, in Model 3, the interactions were also added.

The results showed that only Model 2 (F(5. 24) = 50.001, p = <0.001, R² = 0.912, Adjusted R² = 0.894) and Model 3 (F(8.21) = 62.850, p = <0.001, R² = 0.960, Adjusted R² = 0.945) were significant. In contrast, Model 1 (F(1. 28) = 1,564; p = 0.221, R² = 0.053, Adjusted R² = 0.019) was not significant. 

The three interactions presented in Model 3 were significant, two of them -TNF and MNS- were positive and one -AFD- was negative. The results are shown in Table 8.

Table 8. Standardized regression estimates.

	Brand Love
	Model 1	Model 2	Model 3
TNF		0.731 (0.006)*	-0.267 (0.014)
AFD		0.004 (0.412)	0.136 (0.428)
MNS		-0.119 (0.009)	-0.970 (0.020)*
Gender		0.217 (0.177)*	-1.120 (1.279)
TNF x Gender			1.212 (0.015)*
AFD x Gender			-0.527 (1.159)*
MNS x Gender			1.031 (0.020)*
Age	0.230 (0.035)	0.163 (0.012)*	0.127 (0.009)*
R2	0.053	0.912	0.960

Source: Elaborated by the authors.

The positive coefficient of 0.042 suggests that an increase in NFT is associated with an increase in BLV. In practical terms, this indicates that as participants engage in more visual fixations, their emotional attachment to the brand tends to increase. This finding can be interpreted as increased visual exploration reinforcing interest or connection to the brand, possibly due to greater exposure to and processing of the visual elements that make up the brand identity.

The negative coefficient of -3.368 indicates that as AFD increases, BLV decreases. This result is particularly interesting, as it suggests that longer fixations could be associated with critical evaluation or cognitive overload that reduces emotional attachment to the brand. It is possible that participants who spend more time at each fixation are encountering visual aspects that generate doubt or are not entirely appealing, which could reduce their affinity for the brand.

The positive coefficient of 0.063 indicates that an increase in MNS is associated with an increase in BLV. This result suggests that greater dynamism in visual scanning, characterized by more rapid eye movements between fixations, is related to a greater emotional connection to the brand. This could be interpreted as indicating that participants who actively examine different elements of a visual stimulus find more aspects that they like or that reinforce their connection to the brand.

5.     DISCUSSION 

5.1.         Theoretical implications

This research makes important contributions at a theoretical level.

First, the study provides a more nuanced view of how demographic differences impact the relationship between visual attention and brand love.

Traditional theories of visual processing and gender differences have argued that men and women differ in the way they process visual stimuli, which in turn affects their emotional and behavioral responses to certain stimuli (Feng et al., 2011; Vanston & Strother, 2017; Shaqiri et al., 2016; Boscolo et al., 2020). The present study confirms that these patterns remain relevant in the context of Generation Z, showing that gender differences in visual processing play a crucial role in how young people of this generation respond emotionally to brands. 

However, while the study confirms certain parallels with previous generations, it also reveals significant discrepancies that challenge established theories about visual processing and gender differences. These discrepancies are particularly apparent in the MNS analysis, which introduces new complexity in understanding how visual scanning patterns influence BLV in Generation Z.

Indeed, the lack of significant gender differences suggests that, at least in this respect, men and women of this generation may be using similar visual and cognitive strategies when interacting with branded stimuli. This could reflect a convergence in the visual experiences shared by this generation, which may be diluting gender differences that were more prominent in previous generations.

One possible explanation for this phenomenon could lie in the digital environment that Generation Z has been exposed to from an early age. Digital technologies-by promoting a more uniform and accessible consumption of information through various platforms (Łobejko & Bartczak, 2021)-could be progressively contributing to a decrease in gender differences in the way visual stimuli are processed and responded to. This phenomenon can be understood within media socialization, where media act as socialization agents that shape individuals' perceptions and behaviors, thus reducing traditional distinctions between men and women (Bandura, 2001).

This finding would suggest a possible evolution towards more fluid and less rigid gender identities, where traditional categories lose relevance in certain social contexts. This aspect is aligned with contemporary theories that advocate a conception of gender as a dynamic social construct, subject to variations according to the sociocultural context (Kessler & McKenna, 1978; Smith et al., 1999).

Second, the study confirms that visual patterns are closely related to BLV in Generation Z, again drawing a parallel with previous generations (Zhou & Xue, 2021; Pertzov et al., 2009; Burr et al., 2010; Binda et al., 2011; Li et al., 2016). More specifically, the positive regression coefficients obtained for the TNF and MNS variables indicate that young people of this generation tend to develop greater emotional attachment toward brands when they engage in more active and dynamic visual exploration.

This second match is important because it demonstrates that Generation Z - like previous generations - appears to use visual dynamism as a strategy to effectively process and evaluate visual information: by actively engaging with a visual stimulus, Generation Z is able to cognitively connect with the brand, which reinforces their affinity and potentially strengthens their BLV. This process of cognitive and emotional integration is essential to the development of lasting relationships with brands, as it allows individuals to not only understand what the brand stands for, but also to feel emotionally connected to it.

However, the study also clarifies this assertion. 

Historically, it has been hypothesized that longer fixations are linked to deeper and more detailed cognitive processing of visual information, which was considered a positive indicator in terms of understanding, retention and, in the marketing context, building emotional attachment to a brand (Goldberg & Kotval, 1999). However, the results obtained in this study indicate that this process may not be as linear or as beneficial as previously thought in the Generation Z context. 

The negative regression coefficient for AFD suggests that long fixations could be associated, in some cases, with a more critical evaluation or even a cognitive overload experience. This implies that, rather than deepening emotional attachment, long fixations could be related to a less favorable reaction to the brand, possibly because individuals are identifying aspects of the stimulus that do not meet their expectations or that are confusing or ambiguous.

This phenomenon may be particularly relevant in the context of Generation Z, which has proven to be a highly critical and demanding group with brands (IPMARK, 2023). Their broad range of visual stimuli familiarity and ability to process information quickly could mean that, when they encounter visual elements that do not meet their high standards, they spend more time evaluating those elements, which could lead to a decrease in emotional engagement rather than an increase.

5.2.         Practical implications

This research also has important practical considerations.

First, brands should consider that traditional patterns of gender differentiation in visual and emotional perception are evolving, and that younger generations, such as Generation Z, may not adhere to the same schemes as previous generations. 

Companies may need to reevaluate how they use gender as a segmentation criterion, choosing an approach based more on individual behaviors and preferences rather than rigid demographic divisions. This aligns with a trend towards greater customization of the consumer experience, where the use of advanced data analytics tools allows brands to deliver content that is more relevant to each individual, without relying solely on their gender.

This aspect may be particularly relevant for omnichannel strategies, where branded content is distributed uniformly across different platforms and devices. Companies operating in highly digitized sectors should take advantage of this phenomenon to create visual experiences that are consistent and accessible to all genders, thus promoting greater consumer identification with brands, regardless of gender. This opens the door to more inclusive marketing strategies that focus less on gender stereotypes and more on creating engaging visual content for a diverse audience.

Second, the positive correlation between active visual exploration and emotional attachment to brands reaffirms the importance of designing visual stimuli that encourage dynamic interaction. Companies should consider that Generation Z, like previous generations, responds favorably to visual environments that invite active cognitive processing, which facilitates a deeper emotional connection with the brand. This suggests that, in a context where visual dynamism is key, advertising campaigns that use engaging, easy-to-navigate visual images and content could significantly enhance consumer affinity with the brand, thereby strengthening long-term loyalty.

However, the study also introduces a critical perspective on the relationship between prolonged fixations and emotional attachment to the brand. Companies must take into account that a visual stimulus that does not meet the expectations of this generational group could not only fail to generate greater emotional attachment, but also lead to a negative evaluation of the brand. This implies that brands must be especially careful to create visual content that is clear, consistent and aligned with Generation Z's high expectations. Visual design that is not intuitive or that generates confusion could backfire, leading to less emotional attachment and a possible weakening of brand loyalty.

5.3.         Limitations and future research

This research offers valuable contributions to knowledge about visual processing and the construction of emotional engagement with brands in Generation Z. However, it is important to recognize certain limitations that could influence the interpretation of the results and, therefore, suggest guidelines for future research.

First, the sample used in the study may not be fully representative of the diversity within Generation Z, especially with regard to socioeconomic, cultural, and educational variables. This limits the generalizability of the findings to the total population of this generation, suggesting the need to broaden the samples in future research to encompass greater heterogeneity and explore how these differences may influence patterns of visual processing and emotional attachment toward brands.

Another significant limitation concerns the controlled experimental environment in which the visual attention measurements were conducted. While this approach allows for strict control of variables, it may not fully reflect the natural conditions in which individuals interact with branded stimuli in their daily lives. Consequently, future studies should consider more ecological research designs, such as field experiments or longitudinal studies, that allow us to monitor how visual attention patterns and emotional responses develop in more realistic contexts and over time.

Finally, the study suggests that Generation Z's familiarity with digital visual stimuli may be mitigating gender differences in visual processing. However, this aspect requires further study to better understand the underlying mechanisms. Future research could investigate how factors such as media saturation, digital multitasking or the use of social networks influence the way this generation processes visual information and establishes emotional connections with brands. Exploring these areas could not only shed light on the identified phenomena, but also provide companies with a more robust understanding to adapt their marketing strategies to the specifics of Generation Z, addressing the complex interactions between technology, gender and consumer behavior.

6.     CONCLUSION

This research makes a meaningful contribution to the field of marketing and consumer psychology, focusing on the interplay between visual processing and emotional attachment to brands in Generation Z. The main objective was to explore how gender differences influence these dynamics, as well as to examine the relationship between patterns of visual exploration and the development of brand love in this demographic.

The study confirms the relevance of gender differences in visual processing, but introduces new complexities that challenge some traditional conceptions. The observed discrepancies around MNS suggest a convergence in the visual and cognitive strategies of Generation Z men and women, possibly as a result of a digital environment that standardizes their interactions with visual stimuli.

In addition, the research validates the relationship between active visual exploration and emotional attachment to brands, replicating patterns that were identified in previous generations. However, it challenges the assumption that more prolonged visual processing is always beneficial, finding that prolonged fixations may be associated with less emotional connection in Generation Z. This finding suggests that, rather than deepening emotional attachment, such fixations may reflect critical evaluation or cognitive overload, highlighting the demanding and critical nature of this demographic. These results provide a much more explained understanding of effective strategies for connecting with Generation Z in marketing.

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AUTHORS’ CONTRIBUTIONS, FUNDING AND ACKNOLEDGMENTS

Funding: This research received no external funding.

AUTHOR:

Coral Cenizo

San Pablo CEU University.

Coral Cenizo holds a PhD cum laude in Information Sciences and a degree in Journalism and Advertising and Public Relations. Her professional work has been focused on the marketing and advertising sector over the last ten years, specializing in strategy, entrepreneurship and digital transformation. She has worked in international companies such as El Corte Inglés or Grupo Munreco, owner of the brands Viceroy, Mark Maddox and Sandoz, where she also worked as marketing manager. Currently, she is a professor at the San Pablo CEU University and coordinator of the Digital Marketing and Social Networks master's degree. 

coral.cenizoruizbravo@ceu.es 

Orcid ID: https://orcid.org/0000-0003-1484-6763 

 

Annex 1. Publications that were part of the study

ID	Heat Map	Text	Publication date
ID01		Fei Fei Sun for Louis Vuitton: Horizons Never End. Backdropped by the vertiginous mountains of Chamonix, the emblematic Horizon suitcase is captured in the Maison’s latest travel campaign. Discover the collection via link in bio.	November 8, 2023
ID02		Louis Vuitton x Frank Gehry. Showcased at Art Basel Miami Beach, Frank Gehry’s exclusive collection combines new pieces with audacious reinventions of the timeless Capucines, unveiled across four themes inspired by his design codes: Architecture and Form, Material Exploration, Animals, and Twisted Box. Explore the limited-edition handbags via link in bio.	December 6, 2023
ID03		The Book 16. Discover the dazzling world of the LV Volt Fine Jewelry Collection by @FrancescaAmfitheatrof, revealing a series of creations that glow in the pureness of their dynamic lines in Louis Vuitton's latest edition of its magazine, exclusive to the LV App. Read the article via link in bio.	July 21, 2023
ID04		Ombre Nomade. Inspired by the changing reflections of the desert, the emblematic perfume by Master Perfumer Jacques Cavallier Belletrud is encapsulated in a Marc Newson designed, black bottle pierced by light – reminiscent of the golden dunes at dusk….	November 22, 2023
ID05		Holiday Season. The Louis Vuitton Holiday Gift Guide unveils a wondrous array of Women's designs, from the latest ready-to-wear pieces to iconic handbags – perfect for the season's celebrations. Discover the gift selection via link in bio.	December 8, 2023
ID06		Emma Stone in Louis Vuitton. To attend the @poorthingsfilm premiere in New York City, the House Ambassador was dressed by @NicolasGhesquiere in a custom embroidered yellow gown and glistening flower necklace.	December 7, 2023
ID07		Holiday Season. Elevate festive looks with a dash of sparkle from the Maison's glistening gift selection of Fine Jewelry pieces. Discover the effervescent creations via link in bio.	December 9, 2023
ID08		Louis Vuitton Blossom. Capturing the new creations' radiant optimism, House Ambassador Ana de Armas showcases the Monogram star-shaped Flower through the stackable designs by @FrancescaAmfitheatrof. Discover the pieces via link in bio.	August 18, 2023
ID09		Holiday Season. In a display of elegant enchantment, Louis Vuitton's seasonal selection of Women's leather goods and sunglasses showcases eye-catching designs alongside a collection of signature icons. Discover the Holiday Gift Guide via link in bio.	November 11, 2023
ID10		Women's Fashion Campaign. Evocative of a contemporary French aesthetic, signature quilting and gilded finishes accentuate @NicolasGhesquiere’s emblematic GO-14 with distinctive sophistication. Discover the reimagined handbag showcased by House Ambassador Hoyeon via link in bio.	December 17, 2023
ID11		Felix for Louis Vuitton. The Maison and @NicolasGhesquiere are pleased to welcome @yong.lixx, the celebrated South Korean vocalist-rapper-dancer and @realstraykids' band member, as a House Ambassador.	August 22, 2023
ID12		Men's Pre-Fall 2024 Show. Bathed in deep blues and luminous yellows, @pharrell's new collection embraces a vibrant array of oceanic shades from striking motifs to sleek monochromatic accents. Watch the full show via link in bio.	December 3, 2023
ID13		RIIZE for Louis Vuitton. Embodying the audacious spirit of the Maison, House Ambassadors RIIZE lend their bold attitude to the graphic pieces of Louis Vuitton menswear.	December 11, 2023
ID14		Men's Pre-Fall 2024 Show. Naval signatures permeate @pharrell's debut Pre-Fall collection, transforming the dandy silhouette into sailor-inspired creations with maritime stripes and delicate pearl adornments. Watch the full show via link in bio.	November 30, 2023
ID15		The new Tambour watch. Unveiled by House Ambassador Bradley Cooper, the latest iteration of the Tambour symbolizes a new chapter of Louis Vuitton watchmaking, its signature codes and understated elegance. Discover the redefined timepiece via link in bio.	September 1, 2023

 

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