Quick Commerce - Lithuania

Lithuania

Highlights

The Quick Commerce market in Lithuania is projected to reach a revenue of US$14.38m in 2024.
It is expected to show an annual growth rate (CAGR 2024-2028) of 7.25%, resulting in a projected market volume of US$19.02m by 2028.
By 2028, the number of users in the Quick Commerce market is expected to amount to 246.6k users.
The user penetration rate, which is currently at 7.3% in 2024, is expected to increase to 9.8% by 2028.
The average revenue per user (ARPU) is projected to be US$75.87.
In global comparison, China is anticipated to generate the highest revenue in the Quick Commerce market, with US$80.84bn in 2024.
Additionally, China is expected to have the highest user penetration rate in the Quick Commerce market, projected at 21.0%.
The Quick Commerce market in Lithuania is thriving, with local delivery platforms offering a wide range of products and services for fast and convenient delivery to customers.

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

As consumer trends turn towards ultra-convenience and consumer demands grow, Quick Commerce grocery start-up’s growth exploded. At the end of 2021, Getir, Flink, and Gorillas dominated the European markets, having a total of more than 350 locations. But as demand slows down, we see these player scale back operations. With this, we are also seeing more acquisitions between Meal Delivery players and instant grocery players such as Delivery Hero’s purchase of a majority stake in Glovo.

China leads the quick commerce market of Online Grocery Delivery owing its growth to the rapid increase of internet users, established players, and a mature digital market. Players like MissFresh, and Meituan dominate 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.