Quick Commerce and Consumer Behaviour: An Empirical Analysis of Impulse Buying and Spending Patterns

Introduction

Quick Commerce (Q-Commerce) is transforming the retail ecosystem by enabling ultra-fast delivery of essential goods, typically within 10 to 30 minutes. As an advanced stage in the evolution of e-commerce, this model has gained substantial traction in Indian urban markets due to changing consumer lifestyles, increasing digital penetration, and rising expectations for speed and convenience (Singh, 2024). The rapid expansion of the Indian e-commerce sector is further supported by innovations in supply chain management and last-mile delivery, which significantly enhance consumer experience. (IBEF, 2021) The growth of Q-Commerce in India is primarily driven by the emergence of hyperlocal delivery systems supported by micro-fulfillment centers and dark stores, enabling efficient inventory management and real-time logistics. Leading platforms such as Blinkit, Zepto, and Swiggy Instamart are redefining retail by prioritizing speed, convenience, and responsiveness to consumer needs (IBEF, 2024). These platforms cater largely to urban consumers who increasingly prefer instant access to groceries and daily essentials, thereby shifting consumption patterns from planned bulk purchases to frequent, need-based buying behavior (Lakshmi et al., 2026) [9] . Given the rapid adoption and evolving nature of Q-Commerce platforms, it is essential to examine consumer perceptions and behavioral responses toward these services. Prior research highlights that factors such as perceived usefulness, ease of use, and service experience significantly influence the adoption of Q-Commerce platforms (Deepthi & Bansal, 2023; Kapoor et al., 2023) [3,8] . As Indian cities increasingly embrace digital-first retail ecosystems, such investigations are critical in understanding the transformation of consumer decision-making processes. While the operational advantages of Q-Commerce are well established, its impact on consumer behavior, particularly in terms of spending patterns and impulse buying requires deeper examination. The availability of instant gratification, combined with time-sensitive promotions and personalized recommendations, can significantly influence customer satisfaction and encourage unplanned purchases (Chavadi et al., 2024) [2] .

Objectives of the Study

The main objectives of this study are to analyze the influence of Quick Commerce on consumer spending behavior and impulse purchases and to determine the association between demographic factors and these behaviors. The study also aims to identify how demographic characteristics such as gender, age, income, occupation and family structure correlate with changes in spending patterns and impulsive buying tendencies on Quick Commerce platforms.

Research Methodology

The study is based on primary data collected from 200 consumers residing in Bengaluru city. A structured questionnaire was used comprising both close-ended and multiple-choice questions. Key areas of focus included consumer perceptions of spending pattern, frequency of impulse purchases and demographic information. The data were analyzed using descriptive statistics and Chi-square tests to determine the significance of associations between demographic variables and consumer behavior. The sampling technique used was multi stage sampling and the study focused on users who had made purchases through Quick commerce platforms such as Zepto, Blinkit and Instamart. The results presented in Table 1 indicate that Quick Commerce platforms have a notable influence on consumer spending patterns. A majority of respondents (55.0%) stated that they spend slightly more due to the ease and immediacy offered by these platforms. Furthermore, 19.5% of the users mentioned they spend significantly more, while an equal proportion (19.5%) noted no change in their spending habits. A minority of consumers reported reduced spending, with 5.5% spending slightly less and only 0.5% spending significantly less. It suggests a clear upward shift in expenditure associated with the use of Quick Commerce services, driven primarily by convenience, time-saving features and promotional strategies like flash sales and instant delivery. This corresponds with findings of Goswami and Kumari, 2024 who emphasized that Q-Commerce can alter purchasing decisions and trigger increased spending due to ease of access and time-bound offers. Chi-square tests were used to assess the association between demographic variables and consumers Spending Habits. This non-parametric test determines whether observed differences between categories are statistically significant. A p-value less than 0.05 indicates a meaningful relationship between the variables. Conversely, variables such as education level, family type, family size and vehicle ownership did not show significant influence, suggesting that spending behavior is shaped more by personal and lifestyle dynamics than by structural demographics. This aligns with Singh and Tomar (2024) [12] who highlighted psychological and economic variables such as instant gratification and income level shaping Q-Commerce purchasing patterns, reinforcing the statistical associations observed in this study. As seen in Table 3 impulse buying is prevalent among Quick Commerce users. The largest group (39.0%) admitted to sometimes making impulse purchases, followed by 25.0% who do so often and 7.5% who always buy impulsively. This indicates that over 70% of users engage in unplanned purchases at least occasionally. Only a small proportion 22.5% rarely and 6.0% never reported resistance to impulsive buying. These findings suggest that Quick Commerce platforms through their app design, notifications, limited-time deals and convenience are highly effective at triggering spontaneous consumer behavior, making impulse purchases a defining characteristic of the user experience. Naik and Kapdi (2023) [10] found that delivery speed, convenience and promotional offers are significant factors influencing consumer engagement with Q-Commerce platforms similar to the trends observed in the present study. Chi-square tests were used to assess the association between demographic variables and consumers Impulse Purchases. This non-parametric test determines whether observed differences between categories are statistically significant. A p-value less than 0.05 indicates a meaningful relationship between the variables.  Gender: Female users showed a greater tendency for impulse buying, likely due to higher exposure to promotional content and product browsing.  Age: Consumers aged 18-25 were most prone to impulse purchases, influenced by digital fluency, lifestyle trends and app engagement.  Occupation: Students and private-sector employees were more likely to engage in spontaneous buying, pointing to convenience-oriented consumption habits.  Monthly Income: Respondents with higher income levels displayed greater likelihood of unplanned purchases supported by disposable income and purchasing freedom.  Family Size: Smaller or nuclear families showed increased impulsiveness, potentially due to greater flexibility in budgeting and decision-making.

Results and Discussion

Meanwhile, education level, family type and vehicle ownership did not significantly affect impulse buying behavior. This suggests that psychological and lifestyle factors, rather than structural characteristics, are the primary drivers behind spontaneous purchases in the Quick Commerce context. Impulse buying has been linked to platform design and emotional triggers. Wells et al. (2011) [13] observed that digital interfaces contribute to spontaneous buying, while Bahrainizad and Rajabi (2018) [1] noted that packaging and mood play moderating roles in online purchases.

These insights support the present findings where younger consumers and women reported higher instances of impulse buying. Elangovan et al. (2025) [4] pointed out that demographic factors, especially time pressure among working individuals and family dynamics, significantly influence Q-Commerce behavior. This corresponds with the current research, where gender, age, occupation and income showed a strong association with both spending and impulse buying behaviors.

Managerial Implications

The analysis reveals that Quick Commerce platforms significantly impact consumer spending and impulse buying behavior. A majority of respondents (74.5%) reported increased spending either slightly or significantly due to the convenience, speed and promotional tactics offered by these platforms. Chi-square tests showed that demographic factors such as gender, age, occupation and monthly income had significant associations with spending habits, indicating that young adults, females, students and higher-income groups tend to spend more through Quick Commerce.

Similarly, impulse buying behavior was widespread, with 71.5% of respondents admitting to making unplanned purchases at least occasionally. Impulse buying was significantly associated with gender, age, occupation, income and family size, suggesting that spontaneous purchasing is more common among younger users, women, students and smaller households. Overall, Quick Commerce appears to be reshaping consumer behavior by fostering increased expenditure and impulsive shopping, especially among digitally active and economically capable consumer segments.

Based on the study following implications have emerged for platform developers, marketers and policymakers:  Q-Commerce platforms should focus on younger consumers and high-income groups who show higher impulse buying tendencies.  There is a need to promote financial literacy to help users manage unplanned spending triggered by instant delivery and promotional tactics.  Regulatory bodies should consider setting guidelines for ethical advertising and sustainable packaging in the Q-Commerce sector.

Conclusion

This study highlights the profound influence of Quick Commerce (Q-Commerce) platforms on modern consumer behavior, particularly in urban environments like Bengaluru.

The findings demonstrate that the convenience, speed and user centric design of Q-Commerce services have led to noticeable shifts in both spending patterns and impulse buying tendencies. A significant portion of users, especially younger individuals, women and higher income earners, reported increased spending and frequent unplanned purchases. Chi-square analysis further confirmed strong associations between demographic factors such as age, gender, occupation, income and family size and consumer behaviour on these platforms. These insights underscore that while Q-Commerce meets the demands of fast-paced lifestyles, it also amplifies impulsive and convenience driven consumption. As Q-Commerce continues to grow, understanding these behavioral trends becomes essential for platform developers, marketers and policymakers aiming to balance commercial success with consumer well-being and responsible retail practices.

References

1. Bahrainizad M, Rajabi A. Consumers' perception of usability of product packaging and impulse buying: considering consumers' mood and time pressure as moderating variables. J Islam Mark. 2018;9(2):262-82.
2. Chavadi CA, Kokatnur SS, Sirothiya M. Role of quick commerce instant gratification on customer satisfaction: the moderating effect of green packaging. Indian J Mark. 2024;54(8). doi:10.17010/ijom/2024/v54/i8/174185.
3. Deepthi B, Bansal V. Employing TAM model to investigate the factors influencing quick commerce applications adoption using structural equation modelling technique. Int J Manag Enterp Dev. 2023;22(4):348-65. doi:10.1504/IJMED.2023.134670.
4. Elangovan N, Nagarathinam Aishwarya, Chellasamy Aarthy. The influence of time pressure and physical effort on quick commerce grocery purchases: exploring the effects of family dynamics in purchase decisions [Internet]. 2025 [cited 2026 Jun 20]. Available from: https://ssrn.com/abstract=5129925
5. Goswami A, Kumari R. A study on impact of quick commerce on consumer decision-making process. J Manag Res. 2024;1(2):1-10.
6. India Brand Equity Foundation. The rise of quick commerce in India: revolutionising retail and last-mile delivery [Internet]. New Delhi: IBEF; 2024 Jul [cited 2026 Jun 3]. Available from: https://www.ibef.org/blogs/the-rise-of-quickcommerce-in-india-revolutionising-retail-and-last-miledelivery
7. New Delhi: IBEF; [cited 2026 Jun 20]. Available from: https://www.ibef.org/industry/retail-india
8. Kapoor A, Sindwani R, Goel M. Exploring quick commerce service experience: a moderated mediated investigation using SEM and fsQCA. Total Qual Manag Bus Excell. 2023;34(13-14):1896-919. doi:10.1080/14783363.2023.2213653.
9. Lakshmi CV, Madhuri A, Kumar BR, Rao DB. Impact of quick commerce applications on consumers' buying behaviour and brand perception. Int J Emerg Res Sci Eng Manag. 2026;2(Suppl 1):137-43.
10. Naik GR, Kapdi G. The rise of quick commerce: analyzing consumer preferences and buying behavior in India. Young Res. 2025;14(1):160-4.
11. Singh R. The impact of quick commerce on consumer behavior and economic trends in India: a systematic review. Int J Soc Sci Econ Res. 2024;9(8):2859-74. doi:10.46609/IJSSER.2024.v09i08.020.
12. Singh RR, Tomar VR. A study of the influence of quick commerce on consumer purchase decisions and satisfaction in Thane City. SGOC USI Publ. 2024;1(1):76-91.
13. Wells JD, Parboteeah V, Valacich JS. Online impulse buying: understanding the interplay between consumer impulsiveness and website quality. J Assoc Inf Syst. 2011;12(1):3.