Market Insights Digital eServices Dating Services

Matchmaking - Portugal

Portugal

Revenue in the Matchmaking market is projected to reach €3.59m in 2024.
Revenue is expected to show an annual growth rate (CAGR 2024-2028) of 2.29%, resulting in a projected market volume of €3.93m by 2028.
In the Matchmaking market, the number of users is expected to amount to 88.5k users by 2028.
User penetration will be 0.8% in 2024 and is expected to hit 0.9% by 2028.
The average revenue per user (ARPU) is expected to amount to €43.03.
In global comparison, most revenue will be generated in China (€1,111.00m in 2024).
With a projected rate of 3.8%, the user penetration in the Matchmaking market is highest in South Korea.

Key regions: India, South Korea, China, Asia, United States

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Analyst Opinion

The Matchmaking market in Portugal is experiencing significant growth, driven by changing customer preferences and the increasing popularity of online dating platforms.

Customer preferences: In Portugal, like in many other countries, there has been a shift in customer preferences towards online dating platforms. This is due to several factors, including the convenience and accessibility of these platforms, as well as the increasing acceptance of online dating as a legitimate way to meet potential partners. Additionally, the younger generation in Portugal is more open to using technology for dating purposes, further fueling the demand for matchmaking services.

Trends in the market: One of the key trends in the matchmaking market in Portugal is the rise of niche dating platforms. These platforms cater to specific demographics or interests, such as religious or ethnic groups, professionals, or individuals with specific hobbies. This trend is driven by the desire for more personalized and targeted matchmaking experiences, as well as the need to stand out in a crowded market. Another trend in the market is the integration of artificial intelligence (AI) and machine learning (ML) technologies. These technologies are being used to improve the matching algorithms of online dating platforms, resulting in more accurate and successful matches. AI and ML can analyze large amounts of data and learn from user behavior, allowing matchmaking platforms to provide more relevant and compatible matches to their users.

Local special circumstances: Portugal has a relatively small population compared to other European countries, which presents both opportunities and challenges for the matchmaking market. On one hand, the smaller population means that the market size is limited, and matchmaking platforms may struggle to attract a large user base. On the other hand, the smaller population also means that there is a closer-knit community, and word-of-mouth can play a significant role in the success of matchmaking services.

Underlying macroeconomic factors: The improving economic conditions in Portugal have also contributed to the growth of the matchmaking market. As the economy continues to recover from the financial crisis, people have more disposable income to spend on dating and matchmaking services. Additionally, the increasing number of young professionals in the country, who may have less time to socialize and meet potential partners, is also driving the demand for matchmaking services. In conclusion, the matchmaking market in Portugal is experiencing growth due to changing customer preferences, the rise of online dating platforms, and the integration of AI and ML technologies. Despite the challenges of a smaller population, the improving economic conditions and the increasing acceptance of online dating are driving the demand for matchmaking services in Portugal.

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.