Market Insights Digital Online Food Delivery Meal Delivery

Restaurant Delivery - Sri Lanka

Sri Lanka

The Restaurant Delivery market in Sri Lanka is expected to generate a revenue of US$28.69m in 2024.
This revenue is projected to grow at an annual rate of 4.14%, resulting in a market volume of US$33.74m by 2028.
In terms of user base, the number of users is expected to reach 1.1m users by 2028.
The user penetration rate, which currently stands at 4.3% in 2024, is anticipated to increase to 4.6% by 2028.
The average revenue per user (ARPU) is expected to be US$29.03.
In comparison to other countries, in the United States is projected to generate the highest revenue in the Restaurant Delivery market, with a staggering amount of US$36,950.00m in 2024.
On the other hand, in South Korea is expected to have the highest user penetration rate with a projected rate of 53.5%.
"The restaurant delivery market in Sri Lanka is experiencing a surge in demand due to the growing urban population and hectic lifestyles."

Key regions: Asia, Europe, South Korea, Germany, China

Market

Region

Region comparison

Currency

Analyst Opinion

The Restaurant Delivery model gained track fast, as it provided an easy solution for restaurants to switch from phone to online orders. Players like Just Eat, Delivery Hero or Takeaway.com strongly pushed the global markets in the recent decade, and global fast food chains like Domino's have adopted their digital strategies, too. The fierce competition resulted in thinner margins as companies poach customers from each other, so currently the market is in its consolidation phase with major M&A deals happening in all regions. Since adoption rates for this market are already high, it is likely towill likely grow slower in the next years and probably convergedelivery models.

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.