The Meal Delivery market in the Philippines is projected to reach a revenue of €1.89bn in 2024.
It is expected to experience an annual growth rate (CAGR 2024-2028) of 5.03%, resulting in a projected market volume of €2.30bn by 2028.
In the Philippines, the Platform Delivery market is projected to have a market volume of €1.08bn in 2024.
When compared globally, in China is expected to generate the highest revenue with €167,200.00m in 2024.
The average revenue per user (ARPU) in the Meal Delivery market in the Philippines is projected to be €89.11 in 2024.
By 2028, the number of users in the Meal Delivery market is expected to reach 25.1m users.
The user penetration rate in the Meal Delivery market in the Philippines will be at 18.4% in 2024.
The meal delivery market in the Philippines is experiencing a surge in demand due to the growing urban population and changing consumer habits.
Meal Delivery is the online ordering and delivery of prepared meals by a restaurant or a platform for direct consumption. Orders are typically placed in an app or on a website. The delivery is handled by the platform enterprise (e.g. Deliveroo) or directly by the restaurant (e.g. Domino’s).
Meal Delivery contains the user and revenue development of two different delivery service solutions for prepared meals: (1) Restaurant Delivery and (2) Platform Delivery. The Restaurant Delivery market includes the delivery of meals carried out directly by the restaurants. The order may be made via platforms (e.g. Delivery Hero, Just Eat) or directly through a restaurant website (e.g. Domino's). The Platform Delivery market focuses on online delivery services that provide customers with meals from partner restaurants that do not necessarily have to offer food delivery themselves. In this case, the platform (e.g. Deliveroo) handles the delivery process.).
Revenue includes the gross merchandise value (GMV), defined as the total sales dollar value for merchandise/food sold through the Online Food Delivery marketplace. User and revenue figures represent B2C services.
Meals ordered online which are directly delivered by the restaurant, no matter if ordered via a platform (e.g. Delivery Hero) or a restaurant website (e.g. Domino's)
Online meal order and delivery both carried out by a platform (e.g. Deliveroo)
Online orders that are picked up in the restaurant
Deliveries of non-processed or non-prepared food (e.g. HelloFresh)
Since Pizza Hut launched the first-ever pizza online order back in 1994, online food delivery has become a billion-dollar business. Aggregator platforms like Takeaway.com or Delivery Hero have expanded all over the world through the sale of reliable infrastructure solutions and attractive commission rates for restaurants. Platform-to-Consumer Delivery companies like Deliveroo or Uber Eats operate a more cost intensive business model, but are taking care of the whole delivery logistics. Those companies have also gained track over the last years, especially in densely populated regions. Both models will likely converge with stronger competition between in-house and third-party solutions.
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.
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.
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.