Market Insights eCommerce Dating Services

Matchmaking - Madagascar

Madagascar

Revenue in the Matchmaking market is projected to reach US$1.26m in 2024.
Revenue is expected to show an annual growth rate (CAGR 2024-2029) of 0.63%, resulting in a projected market volume of US$1.30m by 2029.
In the Matchmaking market, the number of users is expected to amount to 82.2k users by 2029.
User penetration will be 0.2% in 2024 and is expected to hit 0.2% by 2029.
The average revenue per user (ARPU) is expected to amount to US$16.34.
In global comparison, most revenue will be generated in China (US$1,211.00m in 2024).
With a projected rate of 3.8%, the user penetration in the Matchmaking market is highest in South Korea.

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Analyst Opinion

Casual dating, a popular trend in many countries, is also gaining traction in Madagascar. The market for casual dating in the country is experiencing growth due to changing customer preferences, emerging trends, and local special circumstances. Additionally, underlying macroeconomic factors contribute to the development of this market. Customer preferences in Madagascar are shifting towards more casual and non-committal relationships. This is driven by a desire for freedom and independence, as well as a growing acceptance of casual dating as a social norm. Younger generations, in particular, are embracing this trend, seeking casual connections without the pressure of commitment. This shift in customer preferences is consistent with global trends in the casual dating market. Trends in the market indicate an increase in the use of online platforms and dating apps to facilitate casual dating in Madagascar. These platforms provide a convenient and accessible way for individuals to connect with others who share similar interests and intentions. The anonymity and ease of use offered by these platforms have contributed to their popularity. Additionally, the use of social media has also played a role in the growth of the casual dating market, as it allows individuals to meet and interact with potential partners. Local special circumstances, such as urbanization and a more liberal social environment, also contribute to the development of the casual dating market in Madagascar. As more people move to urban areas, the pool of potential partners increases, providing individuals with more opportunities for casual dating. Furthermore, a more open and accepting society allows for greater exploration of personal relationships and preferences, leading to an increase in casual dating. Underlying macroeconomic factors, such as economic growth and increasing disposable income, also play a role in the development of the casual dating market in Madagascar. As the economy grows, individuals have more financial resources to spend on leisure activities, including casual dating. This increase in disposable income allows for greater participation in the casual dating market. In conclusion, the casual dating market in Madagascar is developing due to changing customer preferences, emerging trends, local special circumstances, and underlying macroeconomic factors. The shift towards more casual and non-committal relationships, the use of online platforms and dating apps, urbanization, a more liberal social environment, and economic growth all contribute to the growth of this market. As these factors continue to evolve, the casual dating market in Madagascar is likely to experience further development and expansion.

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.