AGORA International Journal of Economical Sciences, http://univagora.ro/jour/index.php/aijes ISSN 2067-3310, E-ISSN 2067-7669 Vol. 19, No. 1 (2025), pp. 341-356 341 SOCIAL MEDIA ADVERTISING: A STUDY ON MILLENNIAL PURCHASE INTENTIONS T. VUKASOVIĆ, L. WEIS, T. KRAMAR Tina Vukasović¹, Lidija Weis², Tina Kramar ³ ¹ ² ³ Ljubljana School of Business, Slovenia ¹ https://orcid.org/0000-0002-1434-5291, E-mail: tina.vukasovic@upr.si ² https://orcid.org/0000-0001-5193-5103, E-mail: lidija.weis@vsps.si ³ E-mail: tinka.kramar@gmail.com Abstract: Millennials represent one of the most significant consumer groups, combining high purchasing power, technological literacy, and a strong influence on the behaviour of other consumers. Despite their significance, the impact of social media advertising on their purchase intentions remains underexplored in the Slovenian context. The aim of this study was to examine how Slovenian millennials perceive advertisements on social media and how these ads influence their purchasing behaviour and intentions. Data analysis revealed that ad personalization has a positive impact on brand perception, primarily by reducing the perceived intrusiveness of advertising. A key factor influencing purchase intentions is the opinion and recommendations of other users, highlighting the role of social proof. The lack of statistically significant direct influence of advertising on purchasing decisions suggests the importance of long-term trust-building and meaningful user engagement. These findings emphasize the value of strategic approaches that prioritize relevant content and align with consumer values. The study enhances the understanding of millennials' digital behaviour and provides practical guidance for more effective use of social media in marketing. Keywords: millennials, social media, digital advertising, purchase intentions, personalisation, social influence, marketing strategies. 1 INTRODUCTION Over the last decades, the development of social networks has radically transformed the way individuals communicate, seek information and make purchasing decisions. As one of the most significant products of the digital age, social networks are now a central hub for social interaction and commercial communication. With their ability to enable the creation and dissemination of user-generated content, they have also become an indispensable part of modern marketing strategies (Kaplan and Haenlein, 2010; Novak, 2020). Due to their prevalence and influence on consumer decisions, social networks have quickly become one of the key advertising channels for businesses. Today, a large part of marketing budgets is directed to these digital platforms, as they allow for a high degree of audience segmentation and direct contact with consumers (Knoll, 2016; Arora and Agarwal, 2019; Kovačević, 2021). They are particularly prominent in advertising to millennials - Generation Y, born between 1981 and 1996 - who grew up in a digital environment and play an exceptional role in shaping market trends (Mittendorf, 2018; Cech, 2017). Millennials represent a strategically significant target group, as they are technologically savvy, highly educated and highly connected to digital technologies, including social networks (Helal and Ozuem, 2021). They are known for their orientation towards authenticity, sustainability and their ability to influence other consumers through online platforms (Dabija et al., 2018). This is why advertising on social networks is often based on engagement with https://orcid.org/0000-0002-1434-5291 mailto:tina.vukasovic@upr.si https://orcid.org/0000-0001-5193-5103 mailto:lidija.weis@vsps.si mailto:tinka.kramar@gmail.com SOCIAL MEDIA ADVERTISING: A STUDY ON MILLENNIAL PURCHASE INTENTIONS 342 influencers, who enjoy a high level of trust and credibility with this generation (Kovačević, 2021). However, millennials are also critical users of digital content. Their willingness to interact with advertisements is often conditioned by a sense of privacy, transparency and trust in brands (Abraham and Harrington, 2015; Aguirre et al., 2015). Studies show that personalised advertising, although effective, can raise concerns about the protection of personal data, which affects purchase intentions (Schumann et al, On the other hand, well-targeted content and two- way branded communication on social media can positively influence consumer engagement and decisions (Jereb, 2020; Zupančič, 2018). Modern algorithms based on user behavioural data enable targeted advertising that reflects the interests, location and demographic characteristics of consumers (Bayer et al, At the same time, they offer valuable insights for companies to understand more precisely the behaviour of their target audience and, consequently, optimise their marketing approaches (Kovač, 2018). In the context of millennials, these insights are crucial as they can help to increase the effectiveness of digital campaigns and boost sales. Given the increasing prevalence of social networks and the complex nature of millennials' behaviour, it is significant to understand what factors influence their response to advertising through these channels. The aim of this study is to explore the impact of social media advertising on millennials' purchase behaviour, focusing on the role of trust, privacy, content authenticity and user engagement. We analyse how different advertising strategies on these platforms influence their decisions to buy products and services. The research identifies the key factors that shape their purchasing behaviour and influence purchase intentions in relation to social media advertising. In doing so, we aim to contribute to a better understanding of millennials' thought processes, their attitudes towards brands and the factors that drive their consumption decisions in a digital environment. 2 SOCIAL NETWORKS The development and role of social networks Social networks have evolved from being the original tools for connecting and sharing content to key digital platforms for marketing and communicating with users. They are growing exponentially - with 5.24 billion active users at the beginning of 2025, representing almost 64% of the world's population (DataReportal, 2025). Platforms such as Facebook, Instagram, YouTube and TikTok now allow businesses to interact directly with audiences, personalise content and reinforce brands. With the development of mobile devices, artificial intelligence and algorithms for targeted advertising, social networks have become an indispensable tool for reaching users - especially millennials, who represent the digital natives generation (Kovačević, 2021; Tuten and Solomon, 2017). Their expectations for personalisation, authenticity and rapid responsiveness require companies to adopt innovative and ethically informed approaches (Boerman et al., 2017; Tucker, 2014). Advertising on social networks Social media advertising has become a central part of digital marketing over the last decade. In 2024, global spending on advertising on these platforms exceeded 234 billion dollars (Neal, 2024), while in Slovenia this segment already accounts for 20% of digital advertising budgets (iPROM and Valicon, 2024). The biggest focus is on display advertising, influencer marketing and content campaigns that harness the power of platforms such as Facebook, Instagram and TikTok (Statista, 2025). Personalised advertising allows companies to target users precisely based on behavioural, demographic and interest data. Research indicates that such approaches increase user engagement and purchase intentions (Alalwan et al., 2017; Ashley and Tuten, 2015), especially among millennials, who are more receptive to relevant Tina VUKASOVIĆ, Lidija WEIS, Tina KRAMAR 343 and authentic content. As a digital generation, millennials expect brands to communicate with them in a way that is meaningful, personalised and trustworthy (Mittendorf, 2018). The impact of ad personalisation on their purchase behaviour is strong, but also conditioned by their sensitivity to data privacy (Cole et al., 2017; Hall et al., 2017). Successful personalisation therefore requires a balance between message relevance and data collection transparency (Boerman et al., 2017). Advertising strategies and engagement Effective advertising strategies include personalisation, the use of influencers and content based on an emotional connection with users (Djafarova and Trofimenko, 2019; Hwang and Zhang, 2018). Millennials are looking for brands that reflect their values such as sustainability, social responsibility and innovation (Bart et al, Engagement is a key indicator of campaign success - ads that encourage interaction (e.g. quizzes, sweepstakes) have been shown to increase interest and purchase intentions (Duffett and Wakeham, 2016). Despite the advantages, companies face challenges such as ad blindness, user oversaturation and privacy concerns (Hall et al., 2017). Success on social networks thus depends on the ability of companies to understand their target audience, respect their values and build long-term trust. 3 MILLENNIALS AS A TARGET GROUP FOR DIGITAL ADVERTISING Definition and characteristics of generation The millennial generation, also known as Generation Y, comprises individuals born between 1981 and 1996 (Mittendorf, 2018; Dimock, 2019). The definition of generations is based on shared historical, social and technological circumstances that shape their values, habits and behavioural patterns (Pilcher, 1994; Scully, 2001). Millennials are the first generation to come of age with digital developments - the internet, smartphones and social networks - having a significant impact on their lifestyles and consumption behaviour (Howe and Strauss, 2000). Compared to previous generations, millennials express a greater openness to change, a high level of technological proficiency, a greater emphasis on individuality and values, and a desire for instant information and interaction (Rapp et al., 2013; Nye, 2017). These characteristics have made them a central focus of digital marketing. Values and behavioural patterns Millennials often value authenticity, brand responsibility, sustainability and social impact (Mittendorf, 2018; Dabija et al., 2018). They are not only concerned about price or product quality when making purchasing decisions, but also about the values a company stands for. In particular, they pay attention to socially responsible campaigns and transparent brand communication (Ledbetter and Mazer, 2014; Dabija et al., 2018). A large part of their decision- making takes place on social networks, where they seek the opinions, experiences and recommendations of other users. They actively create and share content (UGC), which has a significant impact on digital marketing and electronic word-of-mouth (eWOM) (Gallicano et al., 2012; Young, 2015). Privacy, personalisation and response to advertising While millennials value personalisation, they are also concerned about the use of personal data. Their response to ads is often conditioned by feelings of security, trust and privacy (Cole et al., 2017; Tucker, 2014). Research indicates that they are more receptive to ads that are relevant, authentic and tailored to their interests - but only if there is transparency in the use of data (Boerman et al., 2017; Ashley and Tuten, 2015). SOCIAL MEDIA ADVERTISING: A STUDY ON MILLENNIAL PURCHASE INTENTIONS 344 Research also demonstrates an increased incidence of "ad blindness", which results from the saturation of ads on social networks. This phenomenon reduces the effectiveness of traditional approaches, and companies are looking for new ways to reach millennials in more subtle and interactive ways (Hall et al., 2017; Arora and Agarwal, 2019). Technological behaviour and communication habits Millennials are strongly connected to digital devices and online platforms. Most of them use several social networks on a daily basis, in particular YouTube, Instagram, Facebook and TikTok, where they also actively follow and comment on brands (MMS media, 2024; Atkinson, 2025). They prefer to communicate through visual content - photos, videos, stories - and expect instant responses and personalised experiences (Content Science, 2024). Their digital engagement is not just about passive consumption of content, but often involves active participation, interaction and co-creation of brand messages. This interactivity allows companies to connect directly with them and increase the chances of building loyalty (Rapp et al., 2013). The millennial consumer as a strategic focus for business Increasingly, companies are designing advertising strategies based on an understanding of millennials as digitally literate, socially engaged and informed consumers (Arora and Agarwal, 2019; Smith et al., 2016). This generation not only influences their own purchases, but also the purchasing decisions of others - particularly through digital communities, ratings and recommendations. As a result, they are considered 'influential consumers' who can shape market trends (Diah et al., 2020). They are also significant because of their purchasing power. They represent a large part of the active population and have access to digital channels through which they can quickly compare offers and make informed decisions (Smind, 2020). 4 RESEARCH AND ANALYSIS Survey methodology and sample The research is based on a quantitative method, namely an online survey where we asked millennials in Slovenia about their use of and attitudes towards social media advertising. The target population was all residents of the Republic of Slovenia born between 1981 and 1996. For the closed-ended questions, responses were measured using rating scales from 1 to 5 (do not agree at all; strongly agree) and a frequency of use scale (never - every day). We also included structured dichotomous questions (yes/no), with some questions allowing multiple answers. The survey was conducted via an online questionnaire published on the 1ka website. The survey was carried out in the period from 10/12/2024 to 20/12/2024. The sampling was non-probability, ad hoc, and the survey was distributed to groups of millennials and through private channels. The collected data were processed using SPSS. In this study, the timeframe for millennials is set in line with the definition of Howe and Strauss (2000), which covers the period from 1982 to 2004, and the definition of Mittendorf (2018), which defines millennials as the generation born between 1981 and 1996. In survey, the age group between 25 and 34 years old is the best represented, with 71% of respondents in this age group. The second most represented age group, with 20%, is respondents aged between 35 and 44. The 18-24 age group is represented by 9% of respondents (Table 1). Table 1. Age of respondent Age class Frequency Share [%] 18-24 9 9 % 25-34 71 71,0 % 35-44 20 20,0 % 45-54 0 0 55 or more 0 0 % Tina VUKASOVIĆ, Lidija WEIS, Tina KRAMAR 345 The sample is 52% male, 44% female and 4% other sexes (Table 2). Table 2. Gender of respondent Gender Frequency Share [%] Men 52 52,0 % Women 44 44,0 % Other 4 4,0 % 5 RESULTS Use of social networks The results on the use of social networks show that Facebook is the most used platform, with 94% of respondents using this platform. Instagram is the second most used social network, used by 88% of respondents. TikTok, used by 49% of respondents, ranks third, while LinkedIn is used by 32% of respondents. Twitter is used by 26% of respondents and Snapchat by 17%. Among the social networks listed under 'other', 6% of respondents cite platforms such as Discord, Pinterest, Quora and Reddit (Table 3). Table 3. Use of social networks Social networks Frequency Share [%] Facebook 94 94,0 % Instagram 88 88,0 % Twitter 26 26,0 % Snapchat 17 17,0 % TikTok 49 49,0 % LinkedIn 32 32,0 % Other: ____________ 6 6,0 % The results on social media use further show that most respondents spend between 1 and 2 hours on social media per day, which is the case for 37% of all respondents. This is followed by the group that spends 2-4 hours daily on social networks, comprising 33% of the respondents. More than 4 hours a day are spent on social networks by 17% of respondents, while less than 1 hour a day is spent on social networks by 13% of respondents (Table 4). Table 4. Use of social networks daily Time of use Frequency Share [%] Less than 1 hour 13 13,0 % 1-2 hours 37 37,0 % 2-4 hours 33 33,0 % More than 4 hours 17 17,0 % Respondents confirm that they sometimes search for product information on social networks. As many as 29% of respondents search for product information on social networks frequently, while 27% do so occasionally. 16% of respondents search for product information very often. Rarely, 20% of respondents do so, while 8% never search for product information on social networks (Table 5). Table 5. How often do you search for product information on social networks? Frequency of information search... Frequency Share [%] Never 8 8,0 % Rarely 20 20,0 % Occasionally 27 27,0 % Often 29 29,0 % Very often 16 16,0 % SOCIAL MEDIA ADVERTISING: A STUDY ON MILLENNIAL PURCHASE INTENTIONS 346 Advertising and purchase intentions The main part of the survey was to determine the impact of advertising on purchase intentions. Most respondents, 33%, believe that advertising on social media occasionally influences their purchasing behaviour. 24% of respondents believe that advertising often influences their buying behaviour, while 20% believe that advertising rarely influences their buying behaviour. 15% of respondents believe that advertising never influences their buying behaviour and 8% believe that advertising always influences their buying behaviour (Table 6). Table 6. The impact of social media advertising on the purchasing behaviour of respondents The impact of advertising... Frequency Share [%] Never 15 15,0 % Rarely 20 20,0 % Occasionally 33 33,0 % Often 24 24,0 % Always 8 8,0 % We further asked respondents how significant it is to them that ads are personalised according to their interests. The findings indicate that personalisation of advertisements is significant for most respondents. 26% of respondents consider personalisation moderately significant, 21% consider it significant and 18% consider it very significant. 22% of respondents also consider personalisation to be of little importance and 13% even consider it to be of no importance (Table 7). Table 7. Relevance of personalisation of advertisements to respondents' interests The importance of personalisation of ads Frequency Share [%] It has no meaning 13 13,0 % Little important 22 22,0 % Moderately important 26 26,0 % Important 21 21,0 % Very important 18 18,0 % As regards the impact of social media advertising on increasing purchase intentions, the largest share of respondents, 32%, is undecided. 31% of respondents agree that social media advertising increases their purchase intentions and 13% strongly agree. 21% of respondents disagree that advertising increases their purchase intentions and 11% strongly disagree (Table 8). Table 8. Social media advertising increases respondents' purchase intent Advertising and purchase intent Frequency Share [%] I strongly 11 11,0 % I 21 21,0 % Undecided 23 23,0 % I 32 32,0 % I strongly agree. 13 13,0 % Respondents' engagement with brands is less frequent or occasional. Most respondents engage with brands on social media occasionally, or 34%. 31% of respondents interact with brands rarely, while 24% never interact with brands. 8% of respondents interact frequently with brands, while only 3% interact very frequently. Tina VUKASOVIĆ, Lidija WEIS, Tina KRAMAR 347 The opinions and recommendations of other network users play an significant role in purchasing decisions. The findings indicate that 46% of respondents consider the opinions and recommendations of other network users to be significant in purchasing decisions, while 26% consider them to be moderately significant. The opinions and recommendations of other users are very significant for 16% of respondents. 7% of respondents consider other users' opinions and recommendations to be of little importance, while 5% consider other users' opinions and recommendations to be of no importance for their purchasing decisions (Table 9). Table 9. Importance of other users' opinions and recommendations for respondents' purchasing decisions Relevance of opinions and recommendations Frequency Share [%] It has no meaning 5 5,0 % Little important 7 7,0 % Moderately important 26 26,0 % Important 46 46,0 % Very important 16 16,0 % Finally, we looked at whether respondents believe that customising ads makes social media advertising strategies more effective. In this respect, most respondents, or 79%, believe that adapting social media advertising strategies increases their effectiveness. Only 21% of respondents believe that adapting strategies does not improve the effectiveness of advertising (Table 10). Table 10. Increasing the effectiveness of social media advertising strategies through customisation Effectiveness of adaptation strategies Frequency Share [%] Yes 79 79,0 % No 21 21,0 % Respondents gave a wide range of comments and suggestions on social media advertising, reflecting their personal views and experiences. Over-aggressiveness, irrelevant content and repetitive adverts are common criticisms, causing resistance and reducing effectiveness. Some point out that intrusive advertising discourages them from buying, while others stress the need for more sustainable and responsible approaches. Trust in the brand has emerged as a key condition for engagement. There were also positive reactions to the survey, indicating interest in the topic. The comments confirm the need for more sophisticated, tailored and authentic advertising strategies. Hypothesis testing The study set out five hypotheses. H1: Social media advertising has a statistically significant impact on millennials' purchase behaviour and their intention to buy the advertised products. The first hypothesis was tested with the results of two survey questions: ‒ 7. Do you believe that social media advertising influences your buying behaviour? ‒ 9. Do you agree that advertising on social networks increases your intention to buy the advertised products? SOCIAL MEDIA ADVERTISING: A STUDY ON MILLENNIAL PURCHASE INTENTIONS 348 For question 7, respondents answered on a 5-point scale from "never influences" to "always influences". For the ninth survey question, respondents answered on a 5-point scale ranging from "strongly disagree" to "strongly agree". From the responses, we generate a new variable, namely a 10-point scale representing the sum of the first two scales. A non-parametric one-sample t-test is used to test the hypothesis. The one-sample t-test is appropriate if the data are normally distributed, so we first perform the Shapiro-Wilk test for normality of distribution (Abu-Bader, 2021). The Shapiro-Wilk test for normality of distribution indicates that the data are not normally distributed. In fact, the shape of the histogram deviates from the symmetric bell-shaped curve that is typical of a normal distribution (Figure 1). The Shapiro-Wilk test confirms the non-normality of the data, as the p-value (sig.) is 0.000 and means that the null hypothesis, which assumes that the data are normally distributed, can be rejected (Table 11). Table 11. Shapiro-Wilk test influence on purchase behaviour and purchase intention Statistics df Sig. Influence on purchase behaviour and purchase intention 0,930 100 0,000 Figure 1. Distribution of influence on purchase behaviour and purchase intention Since the data are not normally distributed, we use a non-parametric alternative to the one-sample t-test, the Wilcoxon Signed Rank test, to test the hypothesis. This test is appropriate for ordinal data with the assumption of normality of distribution not satisfied (Abu-Bader, 2021). It provides greater reliability of results and is consistent with methodological recommendations for treating data that do not meet the normality assumption. The Wilcoxon Signed Rank test checks whether the sample median differs from a certain expected or hypothesised value. The hypothetical value was defined as the mean value between the possible maximum (10) and the possible minimum (2) scores. The results of the Wilcoxon test show that there is no statistically significant difference between the median value of the observed variable (6,000) and the hypothetical value (6,000), with a p-value of 0.000 (Table 12). Most of the values of the observed variable (48 cases) are lower than the hypothetical value, while 32 are higher and 20 are the same (Table 13). This means that the median of the observed variable is not statistically significantly higher than the hypothesised value, which does not allow rejecting the null hypothesis and does not confirm that the observed values are significantly different from the expected values. The test statistic𝑍 = -0.027 also indicates a non-significant difference between the observed and hypothesised values, which is not statistically significant (p > 0.05) (Table 14). Based on these results, we reject hypothesis H1. Tina VUKASOVIĆ, Lidija WEIS, Tina KRAMAR 349 Table 12. Descriptive statistics influence purchase behaviour and purchase intention N AS SO Min. Poppy. Quartile 25 % 50% (Median) 75 % Influence on purchase behaviour and purchase intention 100 6,05 1,737 2 9 4 6 7 Hypothetical value 100 6,00 ,000 6 6 6 6 6 Legend: AS - arithmetic mean; SO - standard deviation, Min - minimum; Max - maximum Table 13.Wilcoxon Signed Rank test influence on purchase behaviour and purchase intention N AS early Sum of ranches Impact on purchase behaviour and purchase intention - hypothetical value Negative wounds 48a 33,64 1614,50 Positive mornings 23b 50,80 1625,50 Court 20c Total 100 Legend: a. Hypothetical value < Impact on purchase behaviour and purchase intention; b. Hypothetical value > Impact on purchase behaviour and purchase intention; c. Hypothetical value = Impact on purchase behaviour and purchase intention Table 14. Wilcoxon Signed Rank Test Statistics of the Impact of the Wilcoxon Signed Rank Test on Purchase Behaviour and Purchase Intention Hypothetical value - Impact on purchase behaviour and purchase intention Z - 0,027 Asymp. Sig. (2-tailed) 0,979 H2: Social media advertising has a statistically significant impact on the purchase intention to buy the advertised products. The hypothesis was tested with the results of the ninth survey question: ‒ 9. Do you agree that advertising on social networks increases your intention to buy the advertised products? To test the hypothesis, we first perform a Shapiro-Wilk test for normality of the distribution to choose between a one-sample t-test for a normal distribution or a Wilcoxon Signed Rank test for an abnormal distribution (Abu-Bader, 2021). The Shapiro-Wilk test for normality of distribution indicates that the data are not normally distributed. This is because the shape of the histogram deviates from the symmetric bell-shaped curve that is characteristic of a normal distribution. It can be seen from the graph that the shape of the histogram is not symmetric and does not resemble the bell-shaped curve typical of a normal distribution. An asymmetry is visible, where the values are more concentrated around the value 4 (Figure 2). The Shapiro-Wilk test confirms the non-normality of the data with a p-value (sig.) of 0.000 (Table 15). Based on the results of the normality test, we reject the null hypothesis that the data are normally distributed and due to the non-normal distribution, we also use the Wilcoxon Signed Rank test to test the second hypothesis. Table 15. Shapiro-Wilk test of the results of an increase in purchase intentions Statistics df Sig. Increase in purchase intent ,906 100 ,000 SOCIAL MEDIA ADVERTISING: A STUDY ON MILLENNIAL PURCHASE INTENTIONS 350 Figure 2. Distribution of the results of the increase in purchase intent Due to the non-normal distribution of the data, the second hypothesis is tested using the Wilcoxon Signed Rank test, which tests whether the median of the sample differs from a certain expected or hypothesised value. The results of the Wilcoxon Signed Rank test for hypothesis H2 indicate that social media advertising does not have a statistically significant effect on the purchase intention to buy the advertised products. Descriptive statistics show (Table 16) that the median of the observed variable (responses to question 9) is 3.0, corresponding to the hypothetical value of 3.0. The Wilcoxon test compares the ranked differences between the observed and the hypothetical value and the findings indicate that in 45 cases the observed value is less than the hypothetical value, in 32 cases it is greater and in 23 cases it is equal to the hypothetical value of 3 (Table 17). The test statistic Z = - 1.137 and the p-value = 0.255 also show that the differences between the observed variable and the hypothetical value are not statistically significant (p > 0.05) (Table 18), so we cannot reject the null hypothesis that the median observed value is equal to the hypothetical value and we cannot confirm the second hypothesis. Based on the results of the Wilcoxon test, we reject hypothesis H2 as there is insufficient evidence that social media advertising has a statistically significant impact on respondents' purchase intentions. Table 16. Descriptive statistics on the increase in purchase intent N AS SO Min. Poppy. Quartile 25 % 50% (Median) 75 % Increase in purchase intent 100 3,15 1,218 1 5 2 3 4 Hypothetical value 100 3,00 ,000 3 3 3 3 3 Legend: AS - arithmetic mean; SO - standard deviation, Min - minimum; Max - maximum Table 17. Wilcoxon Signed Rank test of the increase in purchase intent N AS early Sum of ranches Tina VUKASOVIĆ, Lidija WEIS, Tina KRAMAR 351 Increase in purchase intent - hypothetical value Negative wounds 45a 38,12 1715,50 Positive mornings 32b 40,23 1285,50 Court 23c Total 100 Legend: a. Hypothetical value < Increase in purchase intent; b. Hypothetical value > Increase in purchase intent; c. Hypothetical value = Increase in purchase intent Table 18. Wilcoxon Signed Rank test statistics for the increase in purchase intention test Test Statistics Hypothetical value - Increase in purchase intent Z - 1,137 Asymp. Sig. (2-tailed) 0,255 H3: Millennials' interaction with brands on social media has a positive impact on their purchase intentions. The hypothesis is tested with survey questions 9 and 10: ‒ 10. How often do you engage with brands on social media? ‒ 9. Do you agree that advertising on social networks increases your intention to buy the advertised products? To test the hypothesis, we use Spearman's rank correlation coefficient, which measures the strength and direction of the association between two ordinal variables. The test does not assume a normal distribution of the data, so no distribution testing is necessary. The test findings indicate that the correlation coefficient is 0.187, indicating a weak positive correlation between the variables. This means that higher levels of engagement with brands on social networks slightly increase the purchase intention of respondents, but the correlation is very weak. However, the p-value (p = 0.063) is higher than the usual threshold for statistical significance (0.05), indicating that the association between the variables is not statistically significant (Table 19). The findings indicate that there is a weak positive association between engagement with brands and purchase intention, but this association is not strong enough to be considered statistically significant. Based on these data, it cannot be confirmed that engagement with brands on social networks has a significant impact on increasing purchase intent. We reject the third hypothesis H3. Table 19. Correlation between engagement with brands and increase in purchase intent Correlation coefficient 0,187 Sig. (2-tailed) 0,063 N 100 H4: Adapting social media advertising strategies based on the demographic and behavioural characteristics of millennials leads to more effective advertising in targeting this audience. The fourth hypothesis was tested with the results of question 12: ‒ 12. Do you believe that adapting social media advertising strategies increases their effectiveness in reaching millennials? Respondents answered "yes" or "no" to question 12. We use a binomial test to test whether the responses are statistically significantly different from the hypothesised uniform distribution of responses. The binomial test checks whether the proportion of 'yes' or 'no' responses is statistically significantly different from the expected 50/50 even distribution. SOCIAL MEDIA ADVERTISING: A STUDY ON MILLENNIAL PURCHASE INTENTIONS 352 The results of the binomial test show that 79% of respondents confirmed that adapting social media advertising strategies increases their effectiveness in reaching millennials. Comparison with the 50/50 test distribution of expected shares indicates that the observed shares are statistically different from the uniformly distributed responses. A p-value of 0.000 indicates that the difference between the observed distribution of responses (79% and 21%) and the expected distribution (50/50) is statistically significantly different (Table 20). Based on these results, we can conclude that statistically significantly more respondents confirmed than rejected the impact of adapting advertising strategies on increasing effectiveness in reaching millennials. This supports hypothesis H4 that tailoring advertising strategies on social media based on the demographic and behavioural characteristics of millennials leads to greater advertising effectiveness in reaching this target group. Table 20. Binomial test of the view that tailoring social media advertising strategies increases their effectiveness in reaching millennials Category N Observation of proportions Test proportions Exact Sig. (2- tailed) Yes 79 0,79 0,50 0,000 No 21 0,21 Total 100 1,00 The results confirm that tailoring social media advertising strategies based on the demographic and behavioural characteristics of millennials leads to greater advertising effectiveness in targeting this audience. This means that companies should focus their efforts on tailoring advertising strategies to the target group, as such approaches will be more effective in achieving the desired effects. Discussions Over two decades, social media have evolved from communication tools to key platforms for marketing and advertising. Boyd and Ellison (2007) point out that they allow users to create public profiles, make connections and interact with other users. These features have enabled companies to adapt their strategies to the needs of millennials, defined by Helal and Ozuem (2021) as a technologically literate and adaptable generation. Key mechanisms of influence include personalisation, social proof and direct communication with brands. The aim of the study was to examine the impact of social media advertising on the purchase intentions of millennials. The findings indicate that the vast majority of respondents use Facebook and Instagram, confirming the importance of these platforms for the target group. The use of other platforms such as TikTok, LinkedIn and Twitter was lower but still present, showing the diversity of preferences within the generation. The average time spent using social networks ranges between one and four hours per day, confirming their role as part of everyday life. Hypothesis H1 predicted a direct impact of advertising on millennials' purchase intentions. The results did not support this hypothesis (p > 0.05), suggesting that advertising on social networks often falls short of being sufficiently persuasive. A possible reason for this is millennials' greater trust in social proof compared to direct advertising. This confirms the need for content-rich advertising based on trust and authenticity. Hypothesis H2 concerned the impact of advertising frequency. This was also not statistically confirmed (p > 0.05), suggesting that frequency of ad impressions is not a sufficient factor to stimulate purchase intentions. Repeated advertising may even lead to advertising fatigue (Zhang and Mao, 2016), suggesting that content elements are more significant than ad quantity. Tina VUKASOVIĆ, Lidija WEIS, Tina KRAMAR 353 Searching for product information via social networks proved to be a common practice among respondents, indicating the significant role of these platforms as a tool for product research. In this context, hypothesis H3 was tested, which predicted a positive impact of personalisation on the perceived value of advertisements. This hypothesis was also not statistically confirmed (p > 0.05), indicating the complexity of the impact of personalisation. Nevertheless, respondents mostly expressed positive attitudes towards personalised content, if it was appropriately tailored to their interests. Hypothesis H4 predicted that tailoring advertising strategies to the target audience would increase advertising effectiveness. This hypothesis was confirmed, meaning that content that considers the values and interests of millennials has the greatest impact on their purchasing decisions. This includes authenticity, ethics, transparency and the inclusion of social proof such as recommendations from other users. Advertising on social networks therefore has an impact mainly through indirect factors. Most respondents recognise the importance of personalisation and social proof but are often reluctant to advertise if it is not relevant enough. The mere presence of ads is not enough to increase purchase intentions, as strategic and content-rich communication is needed to build trust and long-term relationships. Interaction with brands remains limited, except in cases where trust is already established. It is therefore crucial for companies to invest in creating a positive user experience and encourage engagement through authentic content. User-generated content and recommendations have a significant impact on the perception of credibility and trust in a brand, which supports the thesis on the importance of social proof. This confirms that advertising on social networks requires multi-faceted approaches that focus on building long-term relationships with users. The key findings show the importance of contextual, relevant and targeted strategies based on understanding millennials' values, personalising ads, building trust and incorporating social evidence such as other users' opinions. 6 CONCLUSIONS The survey findings indicated that millennial, as a digitally literate and influential generation, have a selective attitude towards social media advertising. The direct influence of ads on purchase behaviour has not been statistically confirmed, but indirect factors such as personalisation and social proof play an significant role. Recommendations from other users, identified as an element of social validation, have a significant impact on millennials' purchase intentions, suggesting the importance of user-generated content and trust building. To effectively reach this target group, it is recommended to use personalised and ethically based advertising strategies that reduce the feeling of intrusiveness and include relevant and authentic content. Companies should consider the values of millennials such as transparency, sustainability and social responsibility when designing campaigns. At the same time, the study reveals that while presence on platforms such as Facebook and Instagram remains key to reaching the target audience, presence alone is not enough. Strategic content creation based on trust, user experience and active community engagement is essential for effective user engagement. In terms of methodological approach, the study contributes to understanding the complexity of millennials' perceptions of digital advertising and makes recommendations for further research. These should include larger and more diverse samples and comparative analyses between different generations. Such an extension could shed further light on the impact of social networks on consumption habits in a changing digital environment. There are some significant limitations to consider when considering the results of the survey. The first limitation relates to the small sample size (N = 100), which was limited to a relatively small number of millennials in Slovenia. SOCIAL MEDIA ADVERTISING: A STUDY ON MILLENNIAL PURCHASE INTENTIONS 354 The small number of respondents may affect the reliability of the results and reduce the statistical significance of the findings, making it impossible to generalise the results to the whole population of millennials. Another limitation is related to the survey method itself, which may cause both biases related to socially desirable responses and biases due to poor insight into cause-and-effect relationships and factors. In addition, the use of an online questionnaire may have led to bias as it only surveyed active internet users. Future surveys should include a larger sample and combine different data collection methods to improve reliability. Despite these limitations, the study contributes valuable insights into the purchasing behaviour patterns of millennials and offers practical guidelines for companies wishing to improve the effectiveness of their social media marketing strategies. 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