The Matchmaking market in Serbia is experiencing significant growth due to changing customer preferences and the emergence of new trends in the market. Customer preferences in the Matchmaking market in Serbia have shifted towards online platforms and mobile applications. This is driven by the increasing popularity of smartphones and the convenience of using these devices for matchmaking purposes. Customers are now able to access a wide range of potential matches at their fingertips, making the process of finding a suitable partner much easier and more efficient. Additionally, online platforms and mobile applications offer various features such as compatibility tests and personalized recommendations, which further enhance the matchmaking experience for customers. One of the key trends in the Matchmaking market in Serbia is the rise of niche matchmaking services. These services cater to specific demographics or interests, such as religious matchmaking, LGBTQ+ matchmaking, or matchmaking for professionals. By targeting specific segments of the market, these niche services are able to provide more tailored and personalized matchmaking experiences for their customers. This trend reflects the increasing demand for specialized services and the recognition that one-size-fits-all approaches may not be suitable for everyone. Another trend in the Matchmaking market in Serbia is the integration of artificial intelligence (AI) and machine learning technologies. These technologies are being used to analyze large amounts of data and provide more accurate and personalized matchmaking recommendations. By analyzing factors such as interests, values, and personality traits, AI algorithms are able to match individuals based on compatibility and increase the chances of successful matches. This trend is driven by the growing availability of data and advancements in AI technology, which enable matchmaking platforms to provide more sophisticated and effective matchmaking services. Local special circumstances in Serbia also contribute to the development of the Matchmaking market. Serbia has a relatively high divorce rate, which has created a demand for matchmaking services among individuals who are looking to start a new relationship. Additionally, cultural and societal norms in Serbia place importance on finding a suitable partner for marriage, which further drives the demand for matchmaking services. These local factors create a favorable environment for the growth of the Matchmaking market in Serbia. Underlying macroeconomic factors, such as increasing disposable income and changing social dynamics, also play a role in the development of the Matchmaking market in Serbia. As individuals have more financial resources, they are more willing to invest in matchmaking services to find a compatible partner. Furthermore, changing social dynamics, such as the increasing number of individuals who prioritize their careers or choose to remain single for longer periods, contribute to the demand for matchmaking services. These macroeconomic factors create opportunities for the Matchmaking market to thrive in Serbia.
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.
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