Matchmaking - Norway

  • Norway
  • Revenue in the Matchmaking market is projected to reach €14.93m in 2024.
  • Revenue is expected to show an annual growth rate (CAGR 2024-2028) of 2.59%, resulting in a projected market volume of €16.54m by 2028.
  • In the Matchmaking market, the number of users is expected to amount to 121.5k users by 2028.
  • User penetration will be 2.0% in 2024 and is expected to hit 2.1% by 2028.
  • The average revenue per user (ARPU) is expected to amount to €132.40.
  • In global comparison, most revenue will be generated in China (€1,123.00m in 2024).
  • With a projected rate of 3.8%, the user penetration in the Matchmaking market is highest in South Korea.

Key regions: India, South Korea, China, Asia, United States

 
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Analyst Opinion

The Matchmaking market in Norway has been experiencing significant growth in recent years, driven by changing customer preferences and the increasing popularity of online dating platforms. Customer preferences in the Matchmaking market in Norway have shifted towards convenience and efficiency, with more individuals opting for online dating platforms to find potential partners. These platforms offer a wide range of features and tools that make it easier for users to connect with others who share similar interests and values. Additionally, the anonymity provided by these platforms allows individuals to explore their options without the fear of judgment or rejection. Trends in the Matchmaking market in Norway indicate a growing acceptance and normalization of online dating. As more people become comfortable with the idea of finding love online, the stigma surrounding online dating has significantly decreased. This has led to an increase in the number of users and a higher demand for matchmaking services. Local special circumstances in Norway, such as a high percentage of the population being digitally literate and having access to high-speed internet, have contributed to the growth of the Matchmaking market. The country's advanced technological infrastructure has made it easier for individuals to connect with others online, leading to the popularity of online dating platforms. Underlying macroeconomic factors, such as a high level of disposable income and a strong emphasis on work-life balance, have also played a role in the development of the Matchmaking market in Norway. With more disposable income, individuals are more willing to invest in matchmaking services to find compatible partners. Additionally, the value placed on work-life balance has led to an increased interest in finding meaningful relationships, further driving the demand for matchmaking services. In conclusion, the Matchmaking market in Norway is experiencing growth due to changing customer preferences, the increasing acceptance of online dating, local special circumstances, and underlying macroeconomic factors. As technology continues to advance and societal attitudes towards online dating evolve, the Matchmaking market in Norway is expected to continue its upward trajectory.

Methodology

Data coverage:

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.

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. The main drivers are internet users, urban population, usage of key players, and attitudes toward online services.

Additional notes:

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.

Visión general

  • Revenue
  • Demographics
  • Analyst Opinion
  • Users
  • Global Comparison
  • Methodology
  • Key Market Indicators
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