Argentina, known for its love for food, has seen a significant rise in the Online Food Delivery market.
Customer preferences: Argentinians have always been fond of food, and with the increasing use of technology and the internet, the Online Food Delivery market has gained popularity. The convenience and ease of ordering food online have made it a preferred choice for customers. The availability of a wide range of cuisines and the ability to compare prices and menus of different restaurants have also contributed to the growth of the market.
Trends in the market: The Online Food Delivery market in Argentina has seen a lot of new players entering the market, leading to increased competition. The market has also seen a rise in the number of food delivery apps and websites that offer discounts and cashback to attract customers. The trend of healthy eating has also influenced the market, with many restaurants offering healthy meal options. The use of technology such as artificial intelligence and machine learning to improve the customer experience has also been observed in the market.
Local special circumstances: Argentina's economy has been struggling in recent years, leading to a rise in unemployment rates. This has led to an increase in the number of people looking for part-time or flexible work, leading to a rise in the number of food delivery drivers. The country's love for food has also led to a rise in the number of food festivals and events, providing a platform for restaurants and food delivery companies to showcase their offerings.
Underlying macroeconomic factors: Argentina's economy has been facing inflation and currency devaluation, leading to a rise in the cost of living. This has led to a change in customer behavior, with people opting to eat at home rather than going out to restaurants. The rise in the Online Food Delivery market can be attributed to this change in customer behavior. Additionally, the COVID-19 pandemic has further accelerated the growth of the market, with people preferring to order food online rather than going out to eat.In conclusion, the Online Food Delivery market in Argentina has seen a significant rise in recent years, driven by customer preferences for convenience and ease of ordering food online, healthy eating, and the use of technology to improve the customer experience. The rise in the number of food delivery apps and websites, the increase in competition, and the rise in the number of food festivals and events have also contributed to the growth of the market. The underlying macroeconomic factors such as inflation, currency devaluation, and the COVID-19 pandemic have further accelerated the growth of the market.
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.
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