Market Insights eCommerce Dating Services

Casual Dating - Serbia

Serbia

Revenue in the Casual Dating market is projected to reach US$452.70k in 2024.
Revenue is expected to show an annual growth rate (CAGR 2024-2029) of -0.52%, resulting in a projected market volume of US$441.00k by 2029.
In the Casual Dating market, the number of users is expected to amount to 270.9k users by 2029.
User penetration will be 3.5% in 2024 and is expected to hit 3.9% by 2029.
The average revenue per user (ARPU) is expected to amount to US$1.84.
In global comparison, most revenue will be generated in the United States (US$293.80m in 2024).
With a projected rate of 4.6%, the user penetration in the Casual Dating market is highest in Armenia.

Market

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Currency

Analyst Opinion

The Online Dating market in Serbia has been experiencing significant growth in recent years.

Customer preferences: Serbian consumers are increasingly turning to online dating platforms to meet potential partners. This shift in behavior can be attributed to several factors. Firstly, the convenience and accessibility of online dating platforms make it easier for individuals to connect with others, especially in a fast-paced digital world. Additionally, the anonymity provided by these platforms allows users to feel more comfortable and confident in expressing themselves, leading to more meaningful connections.

Trends in the market: One of the key trends in the Serbian online dating market is the rise of niche dating platforms. These platforms cater to specific interests or demographics, such as religious or cultural groups, and provide a more targeted approach to finding a compatible partner. This trend is driven by the desire for individuals to connect with others who share similar values and interests, increasing the likelihood of a successful match. Another trend in the market is the integration of advanced technologies, such as artificial intelligence and machine learning, into online dating platforms. These technologies enhance the user experience by providing personalized recommendations and improving the accuracy of matching algorithms. By analyzing user data and preferences, these platforms can suggest potential matches that are more likely to be compatible, increasing the chances of a successful match.

Local special circumstances: The cultural and social dynamics in Serbia also play a role in shaping the online dating market. Traditional gender roles and societal expectations may influence the preferences and behaviors of individuals when it comes to dating. Online dating platforms provide an alternative avenue for individuals to meet potential partners, allowing them to bypass some of these traditional norms and restrictions. This has contributed to the growing popularity of online dating in Serbia.

Underlying macroeconomic factors: The growing online dating market in Serbia can also be attributed to the country's improving economic conditions. As the economy continues to develop and incomes rise, individuals have more disposable income to spend on leisure activities, including online dating. Additionally, increased internet penetration and smartphone adoption have made online dating more accessible to a larger segment of the population. These factors have created a favorable environment for the growth of the online dating market in Serbia.

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.