Restaurant Delivery - Switzerland

Switzerland

Highlights

The Restaurant Delivery market in Switzerland is projected to reach a revenue of US$189.00m in 2024.
This indicates an expected annual growth rate (CAGR 2024-2029) of 3.69%, resulting in a projected market volume of US$226.50m by 2029.
Moreover, the number of users in the Restaurant Delivery market is expected to reach 2.0m users by 2029.
In terms of user penetration, it is anticipated to be 19.9% in 2024 and is projected to increase to 21.8% by 2029.
The average revenue per user (ARPU) is expected to be US$107.30.
When compared globally, United States is projected to generate the highest revenue in the Restaurant Delivery market, amounting to US$36.95bn in 2024.
Additionally, South Korea is expected to have the highest user penetration rate of 44.8% in the Restaurant Delivery market.
Switzerland's restaurant delivery market is thriving, with a focus on high-quality, gourmet options to cater to the discerning tastes of its affluent population.

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

Switzerland, a country famous for its chocolate, cheese, and watches, is also a hub for the restaurant delivery market.

Customer preferences: Swiss consumers are known for their high standards and expectations when it comes to food quality and service. Therefore, they prefer to order food from restaurants that offer high-quality cuisine and timely delivery services. The Swiss market is also highly diverse, with a wide range of cuisines available to choose from, including traditional Swiss dishes, Italian, Asian, and Middle Eastern cuisines.

Trends in the market: The restaurant delivery market in Switzerland has witnessed significant growth in recent years, with the COVID-19 pandemic further accelerating the trend. The convenience of ordering food online, coupled with the closure of restaurants during the pandemic, has led to a surge in demand for restaurant delivery services. This has led to an increase in the number of food delivery platforms, such as Uber Eats, Just Eat, and Deliveroo, operating in the country.

Local special circumstances: Switzerland's unique geography and topography, with its mountains and lakes, have led to challenges in the restaurant delivery market. The delivery of food to remote areas can be difficult and time-consuming, leading to higher delivery costs. Additionally, Switzerland's strict regulations regarding the use of electric bikes for food delivery have also affected the market, with some platforms having to switch to traditional bikes or scooters.

Underlying macroeconomic factors: Switzerland's high standard of living and disposable income levels have contributed to the growth of the restaurant delivery market. Additionally, the country's tourism industry has also played a significant role in the market's development, with tourists contributing to the demand for food delivery services. The country's stable economy and political environment have also attracted investment from international food delivery platforms, further driving the market's growth.

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.