Smart Appliances - Georgia

Georgia

The Smart Appliances market in Georgia is expected to generate a projected revenue of US$2.5m by 2024.
It is further anticipated to exhibit an annual growth rate of 8.48% (CAGR 2024-2028), resulting in a projected market volume of US$3.4m by 2028.
The number of active households in this segment is projected to reach 36.1k users by 2028.
In terms of household penetration, it is expected to be 1.8% in 2024 and is projected to increase to 3.4% by 2028.
The average revenue per installed Smart_Home is currently estimated to be US$126.10.
When compared globally, it is noteworthy that in China generates the highest revenue in this segment, reaching US$17,040.0m in 2024.
The demand for smart appliances in Georgia is steadily increasing as consumers seek to embrace modern technology in their homes.

Key regions: Sweden, Denmark, Japan, China, Europe

Market

Region

Region comparison

Currency

Analyst Opinion

The segment Smart Appliances includes connected versions of all kinds of household appliances. In most cases, smart appliances are incremental innovations which add new features to existing products rather than creating totally new devices. The high amount of revenues are generated mainly by relatively high product prices. Many customers as a first step purchase lower-priced small appliances such as smart coffee machines or vacuum robots, whereas people who already own products from other segments are more likely to purchase large, higher-priced appliances like fridges. We expect devices to be adopted rather moderately in Europe and North America, but more quickly in Asia.

Methodology

Data coverage:

The data encompasses B2C enterprises. Figures are based on the sales of smart home products, excluding taxes.

Modeling approach:

Market sizes are determined through a bottom-up approach, building on a specific rationale for each market segment. As a basis for evaluating markets, we use the Statista Global Consumer Survey, market data from independent databases and third-party sources, and Statista interviews with market experts. In addition, we use relevant key market indicators and data from country-specific associations, such as household internet penetration and consumer spending for households. 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 are well suited for forecasting digital products and services due to the non-linear growth of technology adoption. The main drivers are GDP/capita, level of digitization, and consumer attitudes toward smart home integration.

Additional notes:

The data is modeled using current exchange rates. The impact of the COVID-19 pandemic and the Russia-Ukraine war are considered at a country-specific level. The market is updated twice a year in case market dynamics change.