Authors : Sachin Gupta; Dr. Khushboo Agnihotri

Volume/Issue : Volume 11 - 2026, Issue 3 - March

Google Scholar : https://tinyurl.com/2v35xxsc

Scribd : https://tinyurl.com/bdhdust5

DOI : https://doi.org/10.38124/ijisrt/26mar150

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : The force turning this country in the grip of major corporate narrative based marketing to user driven feedback loops is the digital transformation of retail, especially fashion ecommerce. With the Indian e-commerce market expected to reach Rs 297 billion by 2030, for platforms such as Myntra, this "product-performance risk" becomes a continuous issue when there are no physical touchpoints. The purpose of this study is to analyze the overall impact of Online Customer Reviews (OCR) and electronic Word-of-Mouth (e-WOM) on purchase intentions among 100 current retail investors and shoppers. Through a descriptive research design and analysis of the Likert scale data, this study assesses the extent to which review valence, volume and visual content function as online stand-ins for physical inspection. The results show 80% of shoppers who have completed the "add to cart" phase believe reviews are an essential part of the process. One key finding is the power of visual User-Generated Content (UGC); 85% were more likely to make a purchase after viewing reviews with photos or videos, which provide “diagnostic cues” for fit and material. Notably, the amount of reviews (Mean = 4.37) carries more psychological weight than the mean star rating value (Mean = 3.13), implying that Indian consumers give more weight to “crowd validation” as a peripheral heuristic. ” Moreover, while 84% of users use positive reviews to gain a little momentum, the negative feedback carries a disproportionate weight with 94% using it to locate their “deal-breakers. The study finds out that in the case of a high involvement category such as fashion, reviews act as “trust anchors” which help overcome trust element lacking with virtual browsing. In order to maintain this competitive edge, the paper suggests that platforms such as Myntra, with fintech integrated into them, would naturally have greater focus on Explainable AI and authenticated visual feedback designed to close what the researchers called "the trust gap" -- leading to a more transparent and inclusive digital investment/shopping eco-system.

Keywords : E-commerce, Social Proof Theory, User-Generated Content (UGC), Consumer Behavior, Myntra.

References :

1. Akar, E., & Nasir, V. A. (2015). A review of literature on eWOM and its antecedents and effects on consumer decision-making. Marketing Review, 15(4), 23-40.
2. Albayrak, T., & Ceylan, C. (2021). The effect of eWOM on consumer purchase intention and mediating role of brand equity: a study of apparel brands. Journal of Branded Apparel, 12(2), 145-160.
3. Cialdini, R. B. (2001). Influence: Science and practice. Allyn and Bacon.
4. Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Addison-Wesley.
5. Godara, S., et al. (2024). The role of customer reviews in shaping brand preference and long-term purchase behavior. Journal of Online Shopping Environments, 5(1), 12-29.
6. Kotler, P., & Keller, K. L. (2016). Marketing Management (15th ed.). Pearson.
7. Kumar, V., & Sharma, A. (2020). The role of influencer marketing in shaping purchasing decisions among younger consumers. International Journal of Digital Commerce, 8(3), 201-215.
8. Kurrey, R., & Sheikh, S. (2025). Consumer buying behavior trends in Indian e-commerce. International Journal of Advances in Engineering and Management, 7(8), 326-332.
9. Mukesh, Narwal, M., & Seema. (2023). Influence of e-WOM on women's apparel purchase intention: a study on Myntra app. International Journal of Business Competition and Growth, 8(3), 147-163.
10. Park, D. H., Lee, J., & Han, I. (2007). The effect of online consumer reviews on consumer purchasing intention: The moderating role of involvement. International Journal of Electronic Commerce, 11(4), 125-148.
11. Petty, R. E., & Cacioppo, J. T. (1986). Communication and persuasion: Central and peripheral routes to attitude change. Springer-Verlag.
12. Solomon, M. R. (2017). Consumer Behavior: Buying, Having, and Being. Pearson Education.
13. Tiwari, P. (2025). Impact of customer reviews and ratings on buying decisions. International Journal of Novel Trends and Innovations, 25(11), 98-105.