Quick Commerce - Malaysia

  • Malaysia
  • The Quick Commerce market in Malaysia is projected to reach a revenue of MYR US$78.04m in 2024.
  • It is expected to experience an annual growth rate (CAGR 2024-2029) of 9.1%, resulting in a projected market volume of MYR US$114.10m by 2029.
  • By 2029, the number of users in the Quick Commerce market is expected to reach 4.4m users.
  • The user penetration rate is projected to increase from 9.1% in 2024 to 12.0% by 2029.
  • The average revenue per user (ARPU) is expected to be MYR US$24.78.
  • In comparison to other countries, China is expected to generate the highest revenue in the Quick Commerce market, with an estimated amount of MYR US$80,840.00m in 2024.
  • China also has the highest projected user penetration rate of 21.4% in the Quick Commerce market.
  • With the rise of e-commerce platforms like GrabMart and FoodPanda, quick commerce in Malaysia is experiencing a surge in demand for convenient and fast delivery services.
 
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Analyst Opinion

The Quick Commerce market in Malaysia has been growing at a rapid pace in recent years, driven by changing consumer behavior and increasing demand for convenience.

Customer preferences:
Customers in Malaysia are increasingly turning to Quick Commerce services due to their fast delivery times and convenience. With busy lifestyles and a growing preference for online shopping, Quick Commerce services provide a solution that allows customers to receive their orders quickly and efficiently. Additionally, the COVID-19 pandemic has accelerated the adoption of Quick Commerce services as more customers are opting for contactless delivery options.

Trends in the market:
One of the key trends in the Quick Commerce market in Malaysia is the emergence of new players. Traditional retailers and e-commerce platforms are expanding into the Quick Commerce space, while new startups are also entering the market. This has led to increased competition and innovation, with companies looking for ways to differentiate themselves and offer unique services to customers. Another trend is the use of technology to improve delivery times and efficiency, with companies investing in logistics and fulfillment capabilities to meet customer demand.

Local special circumstances:
Malaysia's diverse population and geography present unique challenges for Quick Commerce companies. The country's large urban centers offer significant market potential, but the rural areas are more difficult to serve due to limited infrastructure and logistics capabilities. Additionally, Malaysia's hot and humid climate can be a challenge for companies delivering perishable goods.

Underlying macroeconomic factors:
Malaysia's growing middle class and increasing internet penetration rates are driving the growth of the Quick Commerce market. The country's GDP has been steadily increasing, and consumers have more disposable income to spend on convenience services like Quick Commerce. Additionally, the government has been supportive of e-commerce and digital innovation, providing a favorable regulatory environment for Quick Commerce companies to operate in.

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.

Overview

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