Quick Commerce - India

  • India
  • The Quick Commerce market in India is forecasted to generate a revenue of €3,106.00m in 2024.
  • This market is expected to exhibit a compound annual growth rate (CAGR 2024-2029) of 24.59%, leading to a projected market volume of €9,325.00m by 2029.
  • By 2029, it is anticipated that the number of users in the Quick Commerce market in India will reach 60.6m users.
  • The user penetration rate, which currently stands at 1.8% in 2024, is projected to rise to 4.0% by 2029.
  • The average revenue per user (ARPU) is estimated to be €118.40.
  • In a global perspective, China is expected to generate the highest revenue in the Quick Commerce market, amounting to ¥€74,960.00m in 2024.
  • Furthermore, China boasts the highest user penetration rate in the Quick Commerce market, projected to reach 21.4%.
  • India's quick commerce market is experiencing rapid growth due to increasing smartphone penetration and a young tech-savvy population.
 
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Analyst Opinion

The Quick Commerce market has been rapidly growing in India, with a significant increase in demand for on-demand delivery services.

Customer preferences:
Customers in India have shown a preference for convenience and speed, leading to the rise of Quick Commerce companies. With the increasing penetration of smartphones and internet connectivity, customers are now more comfortable using mobile applications to order and receive goods within a short period.

Trends in the market:
The Quick Commerce market in India has seen a significant increase in competition, with both local and international players entering the market. Companies are now expanding their services beyond food delivery to include groceries, medicines, and other essential items. The COVID-19 pandemic has also accelerated the growth of the Quick Commerce market, with customers preferring contactless delivery options.

Local special circumstances:
India's vast geography and dense population have presented unique challenges to the Quick Commerce market. Companies have had to develop innovative solutions to navigate the country's complex logistics network. Additionally, the diversity of languages and cultures across India has led to the need for localized marketing strategies to appeal to customers in different regions.

Underlying macroeconomic factors:
India's growing middle class and increasing disposable income have contributed to the growth of the Quick Commerce market. Additionally, the government's push towards digitalization and the ease of doing business in India have attracted foreign investment and led to the development of the digital economy. However, the lack of adequate infrastructure and regulatory challenges continue to pose a threat to the growth of the Quick Commerce market in India.

Methodology

Data coverage:

The data encompasses B2C enterprises. Figures are based on Gross Merchandise Value (GMV) and represent what consumers pay for these products and services. The user metrics show the number of customers who have made at least one online purchase within the past 12 months.

Modeling approach / Market size:

Market sizes are determined through a bottom-up approach, building on predefined factors for each market. As a basis for evaluating markets, we use annual financial reports of the market-leading companies, third-party studies and reports, as well as survey results from our primary research (e.g., the Statista Global Consumer Survey). In addition, we use relevant key market indicators and data from country-specific associations, such as GDP, GDP per capita, and internet connection speed. This data helps us estimate the market size for each country individually.

Forecasts:

In our forecasts, we apply diverse forecasting techniques. The selection of forecasting techniques is based on the behavior of the relevant market. For example, the S-curve function and exponential trend smoothing. The main drivers are internet users, urban population, usage of key players, and attitudes toward online services.

Additional notes:

The market is updated twice a year in case market dynamics change. The impact of the COVID-19 pandemic and the Russia-Ukraine war are considered at a country-specific level. GCS data is reweighted for representativeness.

Vue d’ensemble

  • Revenue
  • Analyst Opinion
  • Users
  • Global Comparison
  • Methodology
  • Key Market Indicators
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