Matchmaking - CIS | Statista Market Forecast

Matchmaking - CIS

CIS

Highlights

Revenue in the Matchmaking market is projected to reach US$42.06m in 2024.
Revenue is expected to show an annual growth rate (CAGR 2024-2029) of 4.67%, resulting in a projected market volume of US$52.84m by 2029.
In the Matchmaking market, the number of users is expected to amount to 0.00 by 2029.
User penetration will be 0.00 in 2024 and is expected to hit 0.00 by 2029.
The average revenue per user (ARPU) is expected to amount to 0.00.
In global comparison, most revenue will be generated China (US$1.21bn in 2024).
With a projected rate of 0.0, the user penetration in the Matchmaking market is highest 0.0.

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The Casual Dating market in CIS is experiencing significant growth and development due to changing customer preferences, emerging trends, local special circumstances, and underlying macroeconomic factors. Customer preferences in the Casual Dating market in CIS are shifting towards more casual and non-committal relationships. This is driven by a desire for freedom and flexibility in personal relationships, as well as a growing acceptance of casual dating as a social norm. Additionally, the younger generation in CIS countries is increasingly embracing the concept of casual dating, seeking fun and excitement without the pressure of commitment. Trends in the market include the rise of online dating platforms and apps, which provide a convenient and accessible way for individuals to connect with potential partners. These platforms offer a wide range of features and options, allowing users to tailor their search for casual relationships based on their preferences and interests. Furthermore, the use of social media and messaging apps has also become a popular way for people to meet and engage in casual dating. Local special circumstances in CIS countries, such as a conservative cultural and social environment, have contributed to the growth of the Casual Dating market. In many CIS countries, traditional dating practices and social norms still prevail, making it difficult for individuals to openly pursue casual relationships. As a result, the anonymity and discretion offered by online dating platforms have become appealing to those seeking casual encounters. Underlying macroeconomic factors, such as increasing urbanization and changing gender roles, have also played a role in the development of the Casual Dating market in CIS. As more people move to cities and experience a shift in lifestyle, there is a greater demand for casual dating options that cater to their busy and fast-paced lives. Additionally, the changing dynamics of gender roles, with more women entering the workforce and pursuing independent lifestyles, have contributed to the rise in casual dating as a way for individuals to explore their personal desires and preferences. In conclusion, the Casual Dating market in CIS is experiencing growth and development driven by changing customer preferences, emerging trends, local special circumstances, and underlying macroeconomic factors. As the market continues to evolve, it is expected that online dating platforms and apps will play an increasingly important role in connecting individuals and facilitating casual relationships.

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.