Smart Appliances - Burundi

Burundi

In 2024, the Smart Appliances market in Burundi is projected to reach a revenue of €1.6m.
This is expected to show an annual growth rate (CAGR 2024-2028) of 15.79%, resulting in a projected market volume of €2.8m by 2028.
By that time, the number of active households in Burundi's Smart Appliances market is expected to amount to 39.0k users.
The household penetration rate is projected to be 0.7% in 2024 and is expected to increase to 1.2% by 2028.
Currently, the average revenue per installed Smart_Home in Burundi is expected to be €83.47.
When comparing global markets, it is worth noting that in China generates the highest revenue, with €15,630.0m in 2024.
The demand for smart appliances in Burundi is steadily growing, driven by an increasing urban population and a rising middle class.

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

Marché

Région

Comparaison de régions

Monnaie

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.