Matchmaking - South Africa

South Africa

Highlights

Revenue in the Matchmaking market is projected to reach US$8.52m in 2024.
Revenue is expected to show an annual growth rate (CAGR 2024-2029) of 0.41%, resulting in a projected market volume of US$8.69m by 2029.
In the Matchmaking market, the number of users is expected to amount to 594.9k users by 2029.
User penetration will be 0.8% in 2024 and is expected to hit 0.9% by 2029.
The average revenue per user (ARPU) is expected to amount to US$17.49.
In global comparison, most revenue will be generated China (US$1.21bn in 2024).
With a projected rate of 3.8%, the user penetration in the Matchmaking market is highest South Korea.

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The Casual Dating market in South Africa is experiencing significant growth and development due to changing customer preferences, emerging trends in the market, local special circumstances, and underlying macroeconomic factors. Customer preferences in South Africa are shifting towards more casual and non-committal relationships, leading to an increased demand for casual dating services. This is driven by a desire for freedom and flexibility, as well as a growing acceptance of casual relationships in society. Additionally, the younger generation is more open-minded and less traditional in their approach to dating, further fueling the demand for casual dating services. Trends in the market indicate a rise in the use of online platforms and dating apps for casual dating purposes. These platforms provide a convenient and accessible way for individuals to connect with potential partners, offering a wide range of options and the ability to filter based on specific preferences. The use of technology has also made it easier to maintain anonymity and discretion, which is particularly important in the context of casual dating. Local special circumstances in South Africa contribute to the development of the Casual Dating market. The country has a diverse population with different cultural backgrounds, which influences dating preferences and practices. For example, the urban population is more likely to engage in casual dating compared to rural areas, where traditional values and norms are more prevalent. Additionally, the high prevalence of mobile phone usage and internet penetration in South Africa has created a conducive environment for the growth of online dating platforms. Underlying macroeconomic factors also play a role in the development of the Casual Dating market in South Africa. The country has experienced economic growth in recent years, resulting in an expanding middle class with higher disposable incomes. This has increased the affordability of dating services and contributed to the growth of the market. Furthermore, the increasing urbanization and changing lifestyles in South Africa have led to a greater emphasis on personal fulfillment and self-expression, driving the demand for casual dating services. In conclusion, the Casual Dating market in South Africa is experiencing growth and development due to changing customer preferences, emerging trends in the market, local special circumstances, and underlying macroeconomic factors. The shift towards more casual and non-committal relationships, the rise of online platforms and dating apps, the diverse cultural landscape, and the economic growth in the country are all contributing to the expansion of the market.

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.