Restaurant Delivery - Cuba

Cuba

Highlights

The Restaurant Delivery market in Cuba is projected to reach a revenue of US$1.41m by 2024.
This is expected to show an annual growth rate (CAGR 2024-2029) of 2.16%, resulting in a projected market volume of US$1.56m by 2029.
Furthermore, in the Restaurant Delivery market in Cuba, the number of users is expected to amount to 72.4k users by 2029.
The user penetration is projected to be 0.6% in 2024 and is expected to increase to 0.7% by 2029.
The average revenue per user (ARPU) is expected to be US$20.38.
When comparing globally, it is worth noting that United States is expected to generate the highest revenue in the Restaurant Delivery market, with a projected amount of US$36.95bn in 2024.
On the other hand, South Korea is anticipated to have the highest user penetration rate in the market, with a projected rate of 44.8%.
With the recent growth in online food delivery platforms, Cuba is witnessing a surge in demand for restaurant delivery services, catering to a population seeking convenience and variety in their dining experiences.

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

Cuba, the largest island in the Caribbean, is known for its rich culture, music, and iconic vintage cars. The country has a unique cuisine that blends Spanish, African, and Caribbean flavors. The Restaurant Delivery market in Cuba is developing slowly due to various factors.

Customer preferences: Cubans prefer home-cooked meals, which are cheaper and healthier than restaurant food. The majority of Cubans do not have access to the internet, which limits their ability to order food online. Moreover, the country's infrastructure is not well developed, which makes it difficult for delivery companies to operate efficiently.

Trends in the market: The Restaurant Delivery market in Cuba is slowly developing due to the increasing number of tourists and the rise of private restaurants, known as Paladares. These restaurants are run by entrepreneurs who offer innovative cuisine and better quality service than state-run restaurants. Paladares are more likely to offer delivery services to attract customers.

Local special circumstances: The Cuban government has strict regulations on private businesses, which makes it difficult for entrepreneurs to start and operate a business. The government controls the prices of food, which limits the profit margins of restaurants. Moreover, the country's infrastructure is not well developed, which makes it difficult for delivery companies to operate efficiently.

Underlying macroeconomic factors: Cuba's economy is heavily dependent on tourism, which has been severely impacted by the COVID-19 pandemic. The country's GDP is expected to contract by 8% in 2020. The government has implemented strict measures to control the spread of the virus, which has led to a decline in economic activity. The Restaurant Delivery market in Cuba is expected to recover slowly as the country reopens its borders to tourists. However, the market is likely to remain small due to the country's infrastructure limitations and government regulations.

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.