Quick Commerce - Tunisia

  • Tunisia
  • The Quick Commerce market in Tunisia is projected to achieve a revenue of US$5.77m by 2024.
  • This revenue is expected to experience an annual growth rate of 9.01% (CAGR 2024-2029), resulting in a projected market volume of US$8.88m by 2029.
  • Additionally, the number of users in the Quick Commerce market is anticipated to reach 521.0k users by 2029.
  • In terms of user penetration, it is expected to be 3.0% in 2024 and increase to 4.0% by 2029.
  • Furthermore, the average revenue per user (ARPU) is projected to be US$15.47.
  • When comparing the Quick Commerce market globally, China is predicted to generate the highest revenue, reaching US$80,840.00m in 2024.
  • Additionally, China is expected to have the highest user penetration rate in the Quick Commerce market, with a projected rate of 21.4%.
  • Tunisia's quick commerce market is experiencing a surge in demand as consumers increasingly prioritize convenience and time-saving solutions.
 
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Analyst Opinion

Quick Commerce, also known as Q-commerce, is a rapidly growing sector in the Tunisian market. This market allows customers to order products online and receive them within a short period of time, usually within an hour.

Customer preferences:
Tunisian customers are increasingly looking for convenience and speed when it comes to shopping for goods. With the rise of e-commerce and the COVID-19 pandemic, customers have become more comfortable with online shopping and are looking for faster delivery options. In addition, the younger generation in Tunisia is more tech-savvy and prefers to shop online.

Trends in the market:
The Quick Commerce market in Tunisia is still in its early stages but is growing rapidly. Many local and international companies are entering the market and attempting to establish themselves as the dominant player. One trend in the market is the use of mobile applications for ordering and delivery. Many companies have developed user-friendly mobile applications that allow customers to easily order products and track their delivery. Another trend is the use of artificial intelligence and machine learning to optimize delivery routes and ensure faster delivery times.

Local special circumstances:
Tunisia is a small country with a population of around 12 million people. The country has a relatively high unemployment rate, which has led to a growing interest in entrepreneurship and small businesses. Many Tunisians are turning to Q-commerce as a way to start their own businesses and generate income. In addition, the country has a growing middle class that is looking for more convenient shopping options.

Underlying macroeconomic factors:
Tunisia has a relatively stable economy, but the country has struggled with high levels of inflation and a growing debt burden. The government has implemented economic reforms in recent years to address these issues, but the country still faces challenges in attracting foreign investment and creating jobs. The Q-commerce sector has the potential to create new jobs and stimulate economic growth. In addition, the government has recently launched initiatives to promote entrepreneurship and innovation, which could further support the growth of the Q-commerce market.

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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