




































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 

 

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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 % 



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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 % 



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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. 



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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? 

 



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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. 



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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 



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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  



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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. 



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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. 



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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.  



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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. 

We recommend that companies invest in tailoring ads to the interests of the target audience, 

provide authentic content and avoid intrusive advertising approaches, as these can negatively 

affect brand perception. 

 

 

REFERENCES 

1. Abraham, R., & Harrington, C. (2015). Consumption patterns of the millennial 

generational cohort. Modern Economy, 6(1), 51–64. 

2. Aguirre, E., Mahr, D., & Grewal, D. (2015). Personalisation and privacy: A cross-

cultural comparison of consumer attitudes and behavioural intentions. Journal of 

Interactive Marketing, 32, 36-53. 

3. Alalwan, A. A., Dwivedi, Y. K., & Rana, N. P. (2017). Social media as a marketing 

tool: A literature review. International Journal of Information Management, 37(2), 150-

157. 

4. Arora, T., Kumar, A., & Agarwal, B. (2020). Impact of social media advertising on 

millennials' buying behaviour. International Journal of Intelligent Enterprise, 7(4), 

481–500. 

5. Ashley, C., & Tuten, T. L. (2015). Creative strategies in social media marketing: An 

exploratory study of the practices of social media marketers. Journal of Interactive 

Advertising, 15(2), 139-154. 

6. Atkinson, M. (2025). Statistics on social media use by generation. Unpublished report 

or internal data summary. 

7. Bart, Y., Stephen, A. T., & Sarvary, M. (2014). The role of social media in the purchase 

decision process: A meta-analysis of the literature. Journal of Marketing Research, 

51(5), 605-618. 

8. Bayer, B., Campbell, S. W., & Ling, R. (2017). Connection and disconnection: 

Exploring the relationship between millennial attachment to mobile devices, social 

media, and loneliness. Mobile Media & Communication, 5(1), 77-93. 

9. Boerman, S. C., Kruikemeier, S., & Zuiderveen Borgesius, F. J. (2017). Exploring the 

effects of personalized advertising on consumer responses: A meta-analysis of the 

literature. Journal of Advertising, 46(3), 309-322. 

10. Boerman, S. C., Kruikemeier, S., & Zuiderveen Borgesius, F. J. (2017). Online 

behavioural advertising: A literature review and research agenda. Journal of 

Advertising, 46(3), 363-376. 

11. Cole, M., Smith, R., & Houghton, L. (2017). The impact of social media on consumer 

purchasing decisions: A review of the literature and future research directions. Journal 

of Marketing Management, 33(3-4), 305-328. 

12. Content Science. (2024). Millennial Content Consumption Fact Sheet. Retrieved from: 



Tina VUKASOVIĆ, Lidija WEIS, Tina KRAMAR 

 

355 

 

13. Dabija, D.-C., Bejan, B. M., & Tipi, N. (2018). Generation X versus Millennials 

communication behaviour on social media when purchasing food versus tourist 

services. E+M Ekonomie a Management, 21(1), 191–205. 

14. DataReportal. (2025). Digital Around the World. Retrieved from: 

15. Diah, A. P., & Hidayat, R. (2020). The role of digital marketing in shaping millennial 

consumer behavior. Journal of Digital Marketing, 5(2), 45–58. 

16. Dimock, M. (2019). Defining generations: Where millennials end and Generation Z 

begins. Pew Research Center. 

17. Djafarova, E., & Trofimenko, O. (2019). "Instafamous" – credibility and self-

presentation of micro-celebrities on social media. Information, Communication & 

Society, 22(10), 1432–1446. 

18. Gallicano, T. D., Curtin, P. A., & Matthews, K. D. (2012). Public relations and social 

media: An analysis of public relations practice. Public Relations Review, 38(5), 1–7. 

19. Hall, K., Towers, N., & Shaw, D. . (2017). The role of social media in the marketing 

mix: A review and future research agenda. International Journal of Research in 

Marketing, 34(4), 469-483. 

20. Helal, S., & Ozuem, W. (2021). The impact of social media on consumer behaviour: A 

study on millennials. Journal of Business Research, 124, 335-344. 

21. Howe, N., & Strauss, W. (2000). Millennials rising: The next great generation. Vintage 

Books. 

22. Hwang, J., & Zhang, Q. (2018). The influence of parasocial relationships with social 

media influencers on followers’ purchase intentions and electronic word-of-mouth 

intentions. Journal of Interactive Advertising, 18(2), 97–108. 

23. Iprom. (2024). In Slovenia, digital advertising already accounts for 52% of the total 

advertising revenue. Retrieved from: https://iprom.si/v-sloveniji-digitalnemu-

oglasevanju-ze-52-odstotkov-celotnega-oglasevalskega-kolaca/  

24. Jereb, E. (2020). The impact of social media on consumer purchasing behaviour in 

Slovenia. Bachelor thesis. University of Ljubljana, Faculty of Social Sciences. 

25. Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and 

opportunities of Social Media. Business Horizons, 53(1), 59-68. 

26. Knoll, J. (2016). Advertising in social media: A review of empirical evidence. 

International Journal of Advertising, 35(2), 266–300. 

27. Kovač, M. (2018). The impact of social media on marketing communication. 

Ekonomska Istraživanja, 31(1), 118-135. 

28. Kovačević, L. (2021). Influencers' influence on millennials' purchase decisions on 

social networks. 

29. Ledbetter, A. M., & Mazer, J. P. (2014). Enjoyment fosters media use frequency and 

determines its relational outcomes: Toward a synthesis of uses and gratifications 

theory and media multiplexity theory. Communication Research Reports, 31(2), 138–

149. 

30. Mittendorf, C. (2018). The Impact of Social Media Influencers as an Advertising Source 

in the Beauty Industry from an Irish Female Millennials’ Perspective (magistrsko delo, 

National College of Ireland). 

31. MMS media. (2024). How do Generation Z and Millennials differ in their use of social 

media? Retrieved from https://www.mms.si/novice/kako-se-razlikujeta-uporaba-

drustvenih-omrezij-med-generacijama-z-in-milenijci/  

32. Montag, C., Yang, H., & Elhai, J. D. (2021). On the psychology of TikTok use: A first 

glimpse from empirical findings. Frontiers in Public Health, 9, 641673. 



SOCIAL MEDIA ADVERTISING: A STUDY ON MILLENNIAL PURCHASE INTENTIONS 

 

356 

 

33. Neal, E. (2024). 70+ Social Media Marketing Statistics You Need To Know. Retrieved 

from: https://explodingtopics.com/blog/social-media-marketing-statistics  

34. Novak, M. (2020). The role of social networks in digital marketing. 

35. Nye, J. (2017). Millennials and leadership: A systematic literature review. Total 

Quality Management & Business Excellence, 31(1–2), 1–20. 

36. Pilcher, J. (1994). Mannheim's sociology of generations: An undervalued legacy. 

British Journal of Sociology, 45(3), 481–495. 

37. Rapp, A., Beitelspacher, L. S., Grewal, D., & Hughes, D. E. (2013). Understanding the 

role of social media in the marketing mix: A review and future research agenda. Journal 

of Marketing Theory and Practice, 21(4), 329-345. 

38. Scully, J. (2001). Generational theory and the sociology of generations. Sociology 

Compass, 5(1), 1–14. 

39. Smith, K. T. (2016). Digital marketing strategies that millennials find appealing, 

motivating, or just annoying. Journal of Strategic Marketing, 19(6), 489–499. 

40. Smind, M. (2020). Understanding millennial purchasing power in the digital age. 

Journal of Consumer Research, 12(1), 23–34. 

41. Statista. (2025). Leading social media platforms used by marketers worldwide as of 

January 2024. Retrieved from: https://www.statista.com/statistics/259379/social-

media-platforms-used-by-marketers-worldwide/  

42. Tucker, C. E. (2014). Social networks and privacy concerns: An empirical investigation 

of the effects of social media on advertising effectiveness. Journal of Marketing 

Research, 51(5), 546-562. 

43. Tuten, T. L., & Solomon, M. R. (2017). Social Media Marketing (2. izd.). SAGE 

Publications. 

44. Young, J. (2015). The impact of user-generated content on consumer behavior. Journal 

of Business Research, 68(8), 1–8. 

45. Zupančič, M. (2018). Direct communication between millennials and brands on social.  


