The revenue in the Matchmaking market worldwide is projected to reach €3,618,000,000.00 by 2023.
This is expected to show an annual growth rate (CAGR 2023-2028) of 1.86%, resulting in a projected market volume of €3,968,000,000.00 by 2028.
Furthermore, the number of users in the Matchmaking market is estimated to amount to 134.5m users by 2028.
The user penetration is predicted to be 1.5% in 2023 and is expected to increase to 1.7% by 2028.
Additionally, the average revenue per user (ARPU) is projected to be €31.43.
In global comparison, it is worth noting that the highest revenue in the Matchmaking market will be generated in China, with a projected revenue of €1,086.00m in 2023.
On the other hand, when considering user penetration, in South Korea is expected to have the highest rate of 3.7% in the Matchmaking market.
In the worldwide eServices market, online matchmaking platforms are gaining popularity in countries like the United States, China, and India due to their large populations and high internet penetration rates.
The Matchmaking market contains online services for the systematic search for partners by means of psychological tests or questionnaires. The main characteristic of these services is the fact that registered members search for life partners who are willing to enter into a long-term committed relationship. Furthermore, matchmaking services automatically recommend potential partners to their users. These suggestions are based primarily on personality tests, which can determine a suitable partner by means of matching algorithms.
Data includes revenue figures in Gross Merchandise Value (GMV), Users, average revenue per user (ARPU), and user penetration rate. User and revenue figures represent B2C services.
Matchmaking for the search for life partners
Matchmaking portals and apps that use mathematical algorithms to generate matches
Offline matchmaking services
Apps and portals that create matches based on users location (e.g. Spotted)
Apps and portals that create matches based on simple demographic criteria (e.g. Badoo)
Niche dating, such as portals or apps for vegetarians
Matchmaking has become a big business since the early days of online dating. As these services build on some high complexity algorithms and personality tests, they remain quite expensive and therefore still generate the most revenues in the market. The market is already highly saturated, thus growth rates cannot be expected to be high in the next years. Due to the increasing amount of free services, the industry needs to explore new revenue streams and add extra value to their services. Widespread application of Artificial Intelligence could extend to AI coaching from profile recommendations to relationship and life coaching.
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 segment. 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.
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.
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.