Restaurant Delivery - Bulgaria

Bulgaria

Highlights

The projected revenue in the Restaurant Delivery market in Bulgaria is expected to reach US$58.10m in 2024.
This is estimated to show an annual growth rate of 8.04% from 2024 to 2029, resulting in a projected market volume of US$85.55m by 2029.
Additionally, the number of users in the Restaurant Delivery market is projected to reach 1.8m users by 2029.
The user penetration rate, which is the percentage of the population using Restaurant Delivery market services, is expected to be 20.1% in 2024 and is anticipated to increase to 28.6% by 2029.
The average revenue per user (ARPU) is projected to be US$43.75 (Bulgarian Lev).
In comparison to other countries, United States is expected to generate the most revenue in the Restaurant Delivery market, reaching US$36.95bn (Bulgarian Lev) in 2024.
On the other hand, South Korea is projected to have the highest user penetration rate in the Restaurant Delivery market, with a rate of 44.8%.
Due to the increasing demand for convenient food options in Bulgaria, restaurant delivery services have experienced significant growth in the country.

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The popularity of restaurant delivery services in Bulgaria has been on the rise in recent years, with an increasing number of consumers opting for the convenience of having their meals delivered to their doorstep.

Customer preferences: One of the main reasons for the growth of the restaurant delivery market in Bulgaria is the changing preferences of consumers. With busy lifestyles and hectic schedules, many people are finding it difficult to make time for cooking meals at home or dining out at restaurants. As a result, they are turning to restaurant delivery services as a convenient and time-saving alternative.

Trends in the market: The restaurant delivery market in Bulgaria is becoming increasingly competitive, with new players entering the market and existing players expanding their services. This has led to a wide range of options for consumers, with many different types of cuisine and delivery options available.

Local special circumstances: One of the unique characteristics of the restaurant delivery market in Bulgaria is the popularity of traditional Bulgarian cuisine. Many consumers are looking for traditional dishes that are not always available at restaurants, and are turning to delivery services to satisfy their cravings. Additionally, the rise of food delivery apps has made it easier for consumers to order food from their favorite restaurants, further driving the growth of the market.

Underlying macroeconomic factors: The growth of the restaurant delivery market in Bulgaria can also be attributed to underlying macroeconomic factors, such as rising disposable incomes and increasing urbanization. As more people move to cities and earn higher incomes, they are more likely to eat out and use restaurant delivery services. Additionally, the COVID-19 pandemic has accelerated the growth of the market, as consumers are increasingly turning to delivery services as a safer alternative to dining out at restaurants.

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.