Quick Commerce and the Digital Consumer: Insights from a Survey-Based Analysis
Keywords:
Quick Commerce, Consumer Behavior, Digital Marketing, Customer SatisfactionAbstract
The emergence of quick commerce—characterized by the promise of ultra-fast delivery of everyday essentials—has rapidly transformed consumer shopping behavior in urban and semi-urban markets. This study explores the dynamics of user engagement with quick commerce platforms by conducting a comprehensive survey-based analysis that spans demographic profiling, behavioral patterns, satisfaction levels, and the impact of digital marketing and artificial intelligence (AI) on consumer preferences. With a dataset comprising 180 responses, this analysis offers empirical insights into the determinants of platform preference, consumer expectations, and opportunities for platform improvement.
The survey revealed that young adults aged 18–24, particularly students, form the core user base of quick commerce platforms, accounting for over 70% of respondents. This group, predominantly urban and digitally savvy, values speed, convenience, and seamless app experiences. Among the platforms analyzed, Zepto emerged as the most used (38%), followed by Swiggy Instamart (35%) and Blinkit (25%). Product categories most frequently ordered included snacks and beverages, groceries, and household essentials—highlighting the platforms’ utility for impulse and routine purchases alike.
Delivery speed (89%), competitive pricing and discounts (62%), and product availability (58%) were identified as the top factors influencing platform choice. While satisfaction levels were generally high—48% of users reported being "satisfied" and 32% "very satisfied"—key pain points emerged, including high delivery fees, limited product variety, and inflexible return policies. These were also the most commonly cited issues in open-ended feedback. Suggestions for improvement centered on lowering delivery costs, expanding product selection, and enhancing customer support—indicating a demand for greater value and service reliability.
Sentiment analysis of user feedback revealed a largely neutral to positive tone. Users appreciated the speed and convenience of quick commerce but were vocal about the need for more transparent pricing and consistent service quality. The sentiment distribution also reflected practical expectations, with users acknowledging both benefits and limitations of current service offerings.
Chi-square and t-test statistical analyses provided additional insights into user behavior. No significant gender-based differences were found in platform preference or satisfaction scores, indicating a gender-neutral appeal of these services. However, occupation significantly influenced satisfaction, with students reporting higher satisfaction levels than employed professionals or self-employed respondents. This suggests that lifestyle and availability play a role in how quick commerce services are perceived and utilized.
The influence of digital marketing and AI-driven personalization emerged as a key theme. Instagram (65%) and YouTube (25%) were the most effective channels for reaching consumers, especially via video ads. Social media content focused on promotional offers and user-generated content proved particularly influential. Furthermore, AI-based promotions were deemed effective by 42% of users, though trust in AI recommendations remained mixed. Students showed higher responsiveness to influencer campaigns, especially those featuring discount codes and product reviews.
Looking ahead, the study identified future consumer expectations leaning heavily toward speed (78%) and personalization (65%), along with a growing demand for sustainable practices (52%). These insights underscore the need for quick commerce platforms to not only meet current operational standards but also evolve in alignment with emerging trends in user expectations.
In conclusion, this study provides a data-driven perspective on quick commerce adoption and satisfaction. It emphasizes the importance of delivering value through operational efficiency, digital engagement, and tailored user experiences. To sustain growth and enhance market positioning, platforms must adopt a user-centric strategy that incorporates AI-driven personalization, responsive customer service, and strategic influencer marketing. As competition intensifies in the sector, businesses that can align with the digital lifestyles of younger consumers while addressing key friction points will be better positioned to lead in the evolving quick commerce landscape.
Downloads
Metrics
References
Accenture. (2022). AI in E-commerce: Future Trends in Personalization and Efficiency. Retrieved from https://www.accenture.com
Business Standard. (2023). Zepto’s hypergrowth and the rise of 10-minute grocery delivery. Retrieved from https://www.business-standard.com
Deloitte. (2023). Digital Consumer Trends in India. Retrieved from https://www2.deloitte.com
EY. (2022). The Rise of Quick Commerce in India: Speed as a Service. Retrieved from https://www.ey.com
KPMG. (2022). Connected Retail: Creating the Consumer-First Commerce Experience. Retrieved from https://home.kpmg
McKinsey & Company. (2022). The Changing Face of Indian Retail: Speed and Convenience Redefined. Retrieved from https://www.mckinsey.com
RedSeer. (2023). India Q-Commerce Market Update. Retrieved from https://redseer.com
Grewal, D., Roggeveen, A. L., & Nordfält, J. (2011). The Future of Retailing. Journal of Retailing, 87(S1), S1–S6.
Seiders, K., Voss, G. B., Godfrey, A. L., & Grewal, D. (2005). Do satisfied customers buy more? Journal of Marketing, 69(4), 26–43.
Parasuraman, A., & Colby, C. L. (2015). An Updated and Streamlined Technology Readiness Index. Journal of Service Research, 18(1), 59–74.
Chevalier, J. A., & Mayzlin, D. (2006). The effect of word of mouth on sales. Journal of Marketing Research, 43(3), 345–354.
Batra, R., & Keller, K. L. (2016). Integrating Marketing Communications. Journal of Marketing, 80(6), 122–145.
Downloads
Published
How to Cite
Issue
Section
License

This work is licensed under a Creative Commons Attribution 4.0 International License.
You are free to:
- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
Terms:
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.