Smart Home - Southern Africa

Southern Africa

The Smart Home market in Southern Africa is anticipated to witness significant growth in the coming years.
By 2024, the projected revenue for this market is expected to reach US$800.5m.
Furthermore, it is projected to exhibit a compound annual growth rate (CAGR) of 11.06% from 2024 to 2028, resulting in a market volume of US$1,218.0m by 2028.
In terms of active households, the Smart Home market is anticipated to have approximately [users_currentlayer_yearend] households by 2028.
The household penetration rate, which measures the proportion of households using Smart Home market technology, is projected to increase from 10.2% in 2024 to 19.0% by 2028.
The average revenue per installed Smart Home market currently stands at US$363.10.
This metric reflects the average amount of revenue generated by each Smart Home market installation.
When comparing the Smart Home market globally, United States leads in terms of revenue generation.
In 2024, United States is expected to generate US$38,800.0m in revenue.
These projections highlight the promising growth potential of the Smart Home market in Southern Africa, with revenue, market volume, and household penetration expected to increase steadily over the forecast period.
In Southern Africa, the smart home market is rapidly growing, with an increasing demand for energy-efficient devices and home automation systems.

Key regions: United States, United Kingdom, Germany, Europe, Norway

Market

Region

Region comparison

Currency

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.