Restaurant Delivery - Central America

Central America

Highlights

The Restaurant Delivery market in Central America is projected to reach a revenue of US$67.35m in 2024.
It is expected to exhibit an annual growth rate (CAGR 2024-2029) of 8.76%, resulting in a projected market volume of US$102.50m by 2029.
By 2029, the number of users in the Central American Restaurant Delivery market is expected to reach 2.9m users.
The user penetration rate is projected to be 3.9% in 2024 and is expected to increase to 5.1% by 2029.
The average revenue per user (ARPU) is anticipated to be US$32.30.
In terms of global comparison, United States is expected to generate the highest revenue in the Restaurant Delivery market, amounting to US$36.95bn in 2024.
South Korea, on the other hand, is projected to have the highest user penetration rate in the Restaurant Delivery market, with a rate of 44.8%.
In Central America, the restaurant delivery market is thriving, with a strong preference for local cuisine and a growing demand for contactless delivery options.

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The popularity of restaurant delivery services in Central America has been on the rise in recent years.

Customer preferences: Customers in Central America have shown a growing preference for the convenience of having food delivered to their doorstep. This trend is driven by factors such as the increasing number of dual-income households, busy work schedules, and the desire for a hassle-free dining experience. Additionally, the COVID-19 pandemic has accelerated the adoption of food delivery services as people are encouraged to stay at home and avoid crowded places.

Trends in the market: In countries like Costa Rica and Panama, the restaurant delivery market is dominated by third-party delivery platforms. These platforms have made it easier for customers to order from a wide range of restaurants and have their food delivered in a timely manner. In contrast, countries like Guatemala and Honduras have a more fragmented market with many small, independent delivery services. However, both types of markets are seeing an increase in demand for food delivery services.

Local special circumstances: One factor that affects the restaurant delivery market in Central America is the prevalence of cash payments. Many customers in the region still prefer to pay in cash, which can be a challenge for delivery services that rely on digital payments. To address this, some delivery platforms have partnered with local convenience stores to allow customers to pay in cash when they pick up their food.

Underlying macroeconomic factors: The restaurant delivery market in Central America is also influenced by broader economic factors such as GDP growth, urbanization, and internet penetration. As the region's economies continue to grow and more people move to urban areas, the demand for food delivery services is likely to increase. Additionally, the increasing availability of smartphones and internet access is making it easier for customers to order food online.

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.