Retail Delivery - Mongolia

  • Mongolia
  • The Reail Delivery market in Mongolia is projected to reach a revenue of US$94.22m by 2024.
  • It is expected to grow at an annual rate of 18.56% (CAGR 2024-2029), resulting in a projected market volume of US$220.70m by 2029.
  • By 2029, the number of users in the Reail Delivery market is expected to reach 0.8m users.
  • The user penetration is projected to be 14.9% in 2024 and is expected to increase to 21.1% by 2029.
  • The average revenue per user (ARPU) is expected to be US$181.30.
  • In comparison to other countries, United States is projected to generate the highest revenue in the Reail Delivery market, amounting to US$195,400.00m in 2024.
  • The United States, with a projected user penetration rate of 30.4%, will have the highest user penetration in the Reail Delivery market.
  • In Mongolia, the retail delivery market is experiencing a significant shift towards online platforms due to increasing internet penetration and changing consumer preferences.
 
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Analyst Opinion

Mongolia, a country known for its rugged terrain and nomadic culture, has seen a steady growth in its Retail Delivery market in recent years.

Customer preferences:
Mongolians, like many consumers around the world, are increasingly turning to online shopping for convenience and variety. The country's vast geography and low population density make it difficult for traditional brick-and-mortar retailers to reach all potential customers. As a result, online marketplaces and delivery services have become popular among urban and rural residents alike.

Trends in the market:
One trend in the Mongolian Retail Delivery market is the rise of e-commerce platforms. Local and international companies have launched online marketplaces that offer a wide range of products, from groceries to electronics. These platforms often partner with local delivery companies to ensure timely and reliable delivery to customers across the country.Another trend is the growth of last-mile delivery services. As more consumers shop online, there is an increasing demand for fast and efficient delivery to their doorstep. Local delivery companies are expanding their fleets and investing in technology to improve their delivery times and customer experience.

Local special circumstances:
Mongolia's unique geography and climate pose challenges for Retail Delivery companies. The country's harsh winters and rugged terrain can make delivery difficult, especially in rural areas. However, some companies have found ways to overcome these obstacles by partnering with local logistics providers who have experience navigating the country's challenging landscape.

Underlying macroeconomic factors:
Mongolia's Retail Delivery market is benefiting from the country's overall economic growth and increasing internet penetration. As the country's middle class expands, more consumers are able to afford online shopping and delivery services. Additionally, the government has made efforts to improve internet infrastructure and reduce barriers to e-commerce, which has helped to spur growth in the Retail Delivery market.

Methodology

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.

Overview

  • Revenue
  • Analyst Opinion
  • Users
  • Global Comparison
  • Methodology
  • Key Market Indicators
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