The rapid expansion of social media platforms has reshaped the landscape of modern marketing, fundamentally altering how consumers interact with brands and make purchasing decisions. As platforms such as Facebook, Instagram, Twitter, LinkedIn, and TikTok attract billions of active users worldwide, social media marketing (SMM) has emerged as a critical tool for influencing buying patterns and strengthening brand–consumer relationships. These platforms enable businesses to promote products, enhance visibility, and create personalized experiences that directly impact consumer behavior. The dynamics of social media marketing operate across multiple dimensions, including information search, brand perception, and purchase intention. Through reviews, influencer recommendations, advertisements, and user-generated content, consumers are continuously exposed to persuasive cues that shape attitudes and guide buying decisions. Social media also facilitates two-way communication, enabling brands to engage with audiences in real time. This interactive digital environment fosters trust, community building, and long-term loyalty, significantly influencing how consumers form preferences and ultimately make purchases (Dwivedi et al., 2023; Alalwan, 2022). Influencer marketing has further transformed consumer buying patterns. Endorsements by content creators, lifestyle bloggers, and digital celebrities are often perceived as authentic and relatable, making them highly persuasive in shaping consumer choices (Lou & Yuan, 2022; Hudders & De Jans, 2022). As a result, influencers now play a central role in bridging the gap between brands and consumers, increasing the visibility and credibility of marketing messages. Despite these advantages, the dynamics of social media marketing also present challenges. Oversaturation of promotional content, misinformation, privacy concerns, and the spread of fake news can negatively affect consumer trust and brand credibility (Muntinga et al., 2023; Huang & Benyoucef, 2023). These complexities highlight the need for a deeper understanding of how social media marketing shapes buying patterns in both positive and negative ways.

This study examines the evolving dynamics of social media marketing and its effect on consumer buying patterns by exploring key factors that shape digital engagement and influence purchasing behavior. By analyzing demographic interactions and marketing variables, the research seeks to provide insights into the mechanisms through which social media drives consumer decisions in an increasingly digital marketplace (Voorveld, 2023; Kaplan & Haenlein, 2023).

Regional Growth Trends of the Global Social Media Market

The chart illustrates the projected growth of the social media analytics market size, segmented by region, from 2018 through 2030, measured in billions of US dollars. Over this period, the global market exhibits strong and consistent growth, with the total market size expanding from a modest level in 2018 to an anticipated $43.2 billion by 2030. North America leads the market throughout the period, represented by the darkest segment, showing steady and substantial growth, indicating its dominant role in the adoption and advancement of social media analytics technologies. The Asia Pacific region follows as the second-largest contributor, with its market size expanding rapidly, particularly after 2024, reflecting increasing digital transformation and social media adoption in countries within this region. Europe also shows significant growth, steadily increasing its share across the years. Latin America and the Middle East & Africa (MEA) markets are smaller in comparison but demonstrate gradual upward trends, signaling emerging opportunities in these regions. Notably, the market size experiences accelerated growth from 2023 onwards, reaching $10.2 billion in 2023 and rapidly increasing to $43.2 billion by 2030. This surge underscores the growing importance of social media analytics as organizations worldwide invest heavily in data-driven marketing, customer insights, and competitive intelligence.

Figure: 1 Regional Growth Trends of the Global Social Media Analytics Market (2018–2030)

1. Objective of the Study

• To examine the dynamics of social media marketing and its effect on consumer buying patterns.
• To analyze the association between demographic variables—age, gender, and employment status—and variations in consumer buying patterns influenced by social media marketing.

2. Conceptual Frameworks

A conceptual framework illustrates the expected relationships between the key variables examined in a study. For research on the dynamics of social media marketing and its effect on consumer buying patterns, the framework helps clarify how marketing elements influence consumer responses. It is developed based on insights from existing literature and outlines how independent variables—such as advertising strategies, engagement metrics, psychographic factors, and influencer impact—are expected to shape the dependent variable, namely consumer buying patterns. The framework serves as a guide for understanding how various components of social media marketing interact to affect consumer decision-making behaviour.

Independent Variables Dependent Variable

Figure 2 Conceptual Framework

The study adopts a descriptive, correlational, and quantitative research design to examine the dynamics of social media marketing and its effect on consumer buying patterns in Kathmandu. To capture diverse viewpoints, the research engaged participants from different demographic backgrounds, acknowledging that individuals vary in their willingness and ability to share their experiences regarding social media–driven purchases. A total of 202 respondents were selected using a convenient sampling technique, based on criteria such as active use of social media platforms, prior purchases influenced by social media, representation across age groups (below 20, 20–30, and above 30), and inclusion of all gender identities to ensure an inclusive analysis. Only individuals who voluntarily consented were included in the study. Data were collected through a structured questionnaire administered via online forms, designed to gather relevant information on social media usage patterns and their influence on consumer buying decisions. The survey required approximately 5–10 minutes to complete, enabling efficient and systematic data collection from a broad segment of the population.

1. Data Analysis and Results Outcomes

6.1 Demographic Profile

In this section, the collected data were systematically analyzed to understand how social media marketing influences consumer buying patternsacross different demographic groups. Using quantitative techniques such as descriptive statistics and Chi-Square tests, the study examined relationships between variables like age, gender, employment status, and consumer responses to social media marketing efforts. The results reveal significant insights into the dynamics of social media marketing—highlighting which platforms consumers frequent, how much time they spend engaging with digital content, and the extent to which social media affects their product discovery and purchasing decisions. The analysis also tested the association between demographic factors and buying patterns, uncovering that while demographic variables have limited impact individually, overall social media engagement strongly shapes consumer behavior.

Table 1: Demographic information

Figure 3 Demographic characteristics

Table 1 presents the demographic characteristics of the 202 respondents included in the study. The gender distribution shows that 56.4% are female and 43.6% are male, indicating a slightly higher participation from women. In terms of educational background, the majority of participants, 65.3%, hold a Bachelor’s degree, followed by 19.3% with high school education or below, and 15.3% with a Master’s degree, suggesting that the sample is relatively well-educated and likely familiar with digital platforms. Employment status data shows that 55.4% of the respondents are students, making them the largest group in the sample. This is followed by 21.3% employed part-time, 11.4% employed full-time, and 11.9% unemployed. The dominance of students indicates that younger and more digitally active individuals are strongly represented, which is relevant given the study’s focus on social media marketing and consumer behavior. This demographic structure reflects a population that is highly exposed to online content and therefore likely influenced by digital marketing strategies.

Table 2: Social Media Platform

This study explored the influence of social media marketing on consumer buying behavior, with particular attention to demographic variables such as age, gender, and employment status. The findings underscore the pivotal role social media plays in shaping consumers’ purchasing decisions, as most respondents reported discovering products and services through these platforms. A significant proportion of participants actively follow brands or companies on social media, motivated by updates, exclusive offers, and engaging content. The demographic profile reveals a predominance of students and individuals holding bachelor’s degrees, reflecting a young and educated sample highly engaged with digital media. Social media usage is extensive, with many respondents spending several hours daily on platforms like Instagram and Facebook. Although demographic factors showed limited direct influence, age demonstrated a notable association with responsiveness to social media marketing, highlighting the importance of digital engagement among younger consumers. Moreover, the majority of respondents anticipate that social media marketing will continue to evolve, signaling the necessity for businesses to adapt to shifting consumer behaviors. In conclusion, brands aiming to effectively influence consumer buying patterns in today’s digital landscape should prioritize targeted marketing strategies, personalized content, and sustained strategic engagement to foster loyalty and drive purchase decisions.

1. Acharya, S., Shrestha, S. K., Neupane, D., & Mahat, D. (2024). Exploring Green Finance Practices for Advancing Sustainable Development in Nepalese Banking Sector. NPRC Journal of Multidisciplinary Research, 1(8), 23–34.
2. Alalwan, A. A. (2022). Investigating the impact of social media marketing on consumer behavior: Insights and trends. Journal of Consumer Marketing, 39(2), 317–333.
3. Dwivedi, Y. K., Rana, N. P., Slade, E. L., & Shareef, M. A. (2023). Social media marketing and consumer engagement: A systematic review. International Journal of Information Management, 64, 102632.
4. Hudders, L., & De Jans, S. (2022). Social media influencers and their impact on consumer behavior. Journal of Marketing Communications, 28(4), 529–547.
5. Huang, Z., & Benyoucef, M. (2023). The role of social media in shaping consumer trust and brand perception. Computers in Human Behavior, 138, 107532.
6. Kaplan, A. M., & Haenlein, M. (2023). Rethinking social media marketing: The evolution of digital engagement. Business Horizons, 66(1), 23–39.
7. Khadka, P., Bista, S., Panta, S., & Rimal, S. K. (2024). Unravelling the Influential Factors in the Decision-Making Process of Bank Selection Preferences among Atharvians and Their Relatives. International Journal of Atharva, 2(1), 78–87.
8. Lamichhane, B., & Neupane, D. (2023). Perceived Organizational Support in Nepalese Banks. International Journal of Atharva, 1(1), 1–13.
9. Lou, C., & Yuan, S. (2022). Influencer marketing: A systematic review and future research agenda. Journal of Business Research, 147, 217–229.
10. Mahat, D., Karki, T. B., Neupane, D., Shrestha, D. K., & Shrestha, S. (2024). Decolonization in Focus: A Bibliometric Analysis of Scientific Articles from 2010 to 2023. Nepal Journal of Multidisciplinary Research, 7(1), 1–21.
11. Muntinga, D. G., Moorman, M., & Smit, E. (2023). The dark side of social media marketing: Overexposure and consumer skepticism. Journal of Advertising Research, 63(1), 102–118.
12. Neupane, D., Mahat, D., Shrestha, S. K., & Karki, T. B. (2025). Reckoning the student perspectives on the educational environment: An in-depth analysis using the Dundee Ready Education Environment Measure in the management discipline. Humanities and Social Sciences Letters, 13(1), 301–312.
13. Rayamajhi, A., & Sejuwal, N. (2024). Analyzing the Impact of Service Delivery, Pricing, and Facilities on Customer Satisfaction at Big Mart: A Descriptive and Causal-Comparative Study. International Journal of Atharva, 2(2), 125–135.
14. Shrestha, S. K., Dipak Mahat, Dasarath Neupane, & Tej Bahadur Karki. (2025). E-wallet usage and customer purchase intention: Understanding the mediating role of shopping satisfaction and E-wallet structure. Multidisciplinary Reviews, 8(3), 2025091.
15. Shrestha, S. K., Neupane, D., Karki, T. B., & Mahat, D. (2024). Insights into Paper Souvenir Purchase Intention of Tourists in Nepal. Nepal Journal of Multidisciplinary Research, 7(4), 104–113.
16. Shrestha, S. K., Paudel, A. K., Mahat, D., Karki, T. B., & Neupane, D. (2025). Corporate Social Responsibility in Cultivating Customer Loyalty: Intuitions from the Banking Industry. NPRC Journal of Multidisciplinary Research, 2(2), 160–168.
17. Voorveld, H. A. (2023). The effectiveness of social media advertising: A meta-analysis. Journal of Interactive Advertising, 23(1), 1–20.
18. Wagle, N., Neupane, D., Nyaupane, N. P., & Timalsena, C. (2024). Compassionate Care: Exploration of the Nurse-Patient Relationship and Behavioral Dynamics in Healthcare Settings. International Journal of Atharva, 2(1), 65–77.