The Smart Home market Comfort & Lighting includes devices for the improvement of the living atmosphere. These are devices such as sensors and actuators (e.g. door and window sensors, shutters) as well as connected and remote controllable light sources (smart bulbs) or garage door controls. Programmable or controllable power sockets are not included (see Control & Connectivity).
Digitally connected and controlled devices for living atmosphere improvement
Window/door sensors, shading devices, garage door controls
Control buttons, gateways/hubs
B2B/C2C sales of any kind (e.g. to hotels or office buildings)
The Comfort & Lighting segment includes devices such as door and window sensors or shutters as well as smart bulbs. Because almost all devices in this segment are relatively cheap and especially smart bulbs are easy to install, the products from this segment are used as a market entry by customers. Depending on the specific product, several companies dominate the market. In the field of smart bulbs, key players are Philips Hue, TP-Link, Lifi Labs or IKEA with Tradfi. Besides the general functions of on/off switches, dimming and color-changing modes, we don't see any major innovations at the time but products of this segment are a bridging technology and will be likely absorbed by the corresponding traditional consumer markets.
The data encompasses B2C enterprises. Figures are based on the sales of smart home products, excluding taxes.
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.
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.
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.