Market Insights Digital eServices Dating Services

Matchmaking - Guatemala

Guatemala

Revenue in the Matchmaking market is projected to reach €5.80m in 2024.
Revenue is expected to show an annual growth rate (CAGR 2024-2028) of 12.59%, resulting in a projected market volume of €9.32m by 2028.
In the Matchmaking market, the number of users is expected to amount to 129.2k users by 2028.
User penetration will be 0.6% in 2024 and is expected to hit 0.6% by 2028.
The average revenue per user (ARPU) is expected to amount to €50.09.
In global comparison, most revenue will be generated in China (€1,123.00m 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

Marché

Région

Comparaison de régions

Monnaie

Analyst Opinion

The Matchmaking market in Guatemala has been experiencing significant growth in recent years. Customer preferences have shifted towards online platforms, leading to an increase in the number of people using matchmaking services. This trend can be attributed to several factors, including the convenience and accessibility of online platforms, changing social norms, and a growing acceptance of technology in everyday life.

Customer preferences: Guatemalan consumers have shown a strong preference for online matchmaking platforms. These platforms offer a convenient and efficient way to connect with potential partners, allowing users to browse through profiles and communicate with others from the comfort of their own homes. The popularity of these platforms can be attributed to the increasing reliance on technology in daily life, as well as the desire for a more efficient and streamlined approach to finding a romantic partner.

Trends in the market: One of the key trends in the Guatemalan matchmaking market is the rise of niche platforms catering to specific demographics or interests. These platforms cater to individuals with specific preferences, such as religious or cultural backgrounds, and provide a more targeted approach to matchmaking. This trend reflects the growing diversity and individuality of consumer preferences, as well as the need for more specialized services in the market. Another trend in the market is the integration of artificial intelligence and machine learning technologies into matchmaking platforms. These technologies are used to analyze user data and preferences, providing more accurate and personalized matches. This trend reflects the increasing reliance on technology in the matchmaking process, as well as the desire for more accurate and compatible matches.

Local special circumstances: The Guatemalan matchmaking market is influenced by several local special circumstances. One of these is the cultural importance of family and community in Guatemala. Matchmaking is often seen as a family affair, with parents and relatives playing a significant role in the process. This cultural aspect has influenced the development of matchmaking services in Guatemala, with many platforms offering features that allow users to involve their families in the matchmaking process. Another special circumstance is the relatively conservative nature of Guatemalan society. While online matchmaking platforms have gained popularity, there is still a preference for more traditional methods of finding a partner, such as introductions through family or friends. This preference has influenced the development of matchmaking services in Guatemala, with many platforms offering a combination of online and offline services to cater to different customer preferences.

Underlying macroeconomic factors: The growth of the matchmaking market in Guatemala can be attributed to several underlying macroeconomic factors. One of these is the increasing urbanization and modernization of the country. As more Guatemalans move to cities and adopt a more modern lifestyle, the demand for matchmaking services has increased. Additionally, the growing middle class in Guatemala has led to an increase in disposable income, allowing more people to afford matchmaking services. Another macroeconomic factor is the increasing internet penetration in Guatemala. As more people gain access to the internet, the market for online matchmaking platforms has expanded. This trend is expected to continue as internet infrastructure improves and becomes more accessible in rural areas. In conclusion, the matchmaking market in Guatemala has experienced significant growth due to changing customer preferences, including a shift towards online platforms. The market is characterized by niche platforms catering to specific demographics and the integration of artificial intelligence and machine learning technologies. Local special circumstances, such as the cultural importance of family and the relatively conservative nature of society, have influenced the development of matchmaking services in Guatemala. Underlying macroeconomic factors, such as urbanization and increasing internet penetration, have also contributed to the growth of the market.

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.