Use of social media marketing by women entrepreneurs and its effect on business growth and success

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Type of the article: Research Article

Abstract
The exponential rise of social media users has reshaped marketing and enabled entrepreneurs to access wider markets at minimal cost. This study examines how Social Media Marketing (SMM) practices influence the perceived business growth and success of women entrepreneurs in Assam, India, an emerging and under-researched context. The study aims to analyze the effects of SMM frequency, platform diversity, and customer-engagement activities on entrepreneurial growth outcomes. A descriptive quantitative design was applied. Primary data were collected through a structured, face-to-face survey conducted between January and June 2025 among registered women entrepreneurs in seven major urban-agglomeration cities of Assam: Guwahati, Silchar, Dibrugarh, Jorhat, Nagaon, Tezpur, and Tinsukia. Respondents were selected based on two criteria: operating their businesses for at least one year and actively using social media for business purposes. A total of 206 valid responses were obtained. Regression analysis was used to test the hypotheses.
The results show that frequent SMM use significantly enhances perceived business growth (β = 0.716), while using multiple platforms strongly predicts higher growth and success (β = 0.810). Engagement activities including prompt responses, interactive content, and customer-review sharing also significantly contribute to growth perceptions (β = 0.803). These findings quantitatively confirm that SMM functions not only as a promotional mechanism but also as a strategic enabler that strengthens women’s entrepreneurial capabilities, visibility, and market reach. The study concludes that structured, multi-platform, engagement-oriented SMM strategies can meaningfully support the entrepreneurial development of women in emerging markets such as Assam.

Acknowledgments
Conflict of interest: The authors declare that they have no conflict of interest.

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    • Table 1. Demographic profile
    • Table 2. Scale development
    • Table 3. Items and their Cronbach’s Alpha
    • Table 4. Model summary for Hypothesis 1
    • Table 5. ANOVA and coefficient table for Hypothesis 1
    • Table 6. Model summary for Hypothesis 2
    • Table 7. ANOVA and coefficient table for Hypothesis 2
    • Table 8. Model summary for Hypothesis 3
    • Table 9. ANOVA and coefficient table for Hypothesis 3
    • Conceptualization
      Sonia Laskar, Habibur Rahman Laskar
    • Data curation
      Sonia Laskar
    • Investigation
      Sonia Laskar
    • Methodology
      Sonia Laskar, Habibur Rahman Laskar, Md. Nazrul Islam Barbhuyan
    • Validation
      Sonia Laskar, Habibur Rahman Laskar, Md. Nazrul Islam Barbhuyan
    • Visualization
      Sonia Laskar, Habibur Rahman Laskar
    • Writing – original draft
      Sonia Laskar
    • Formal Analysis
      Habibur Rahman Laskar
    • Software
      Habibur Rahman Laskar
    • Supervision
      Habibur Rahman Laskar, Md. Nazrul Islam Barbhuyan
    • Writing – review & editing
      Habibur Rahman Laskar, Md. Nazrul Islam Barbhuyan