Matchmaking - Panama

Panama

Highlights

Revenue in the Matchmaking market is projected to reach US$1.40m in 2024.
Revenue is expected to show an annual growth rate (CAGR 2024-2028) of NaN%, resulting in a projected market volume of US$-268.10k by 2028.
In the Matchmaking market, the number of users is expected to amount to 42.2k 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 US$37.28.
In global comparison, most revenue will be generated China (US$1.21bn in 2024).
With a projected rate of 3.8%, the user penetration in the Matchmaking market is highest South Korea.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The Matchmaking market in Panama has been experiencing significant growth in recent years. Customer preferences, trends in the market, local special circumstances, and underlying macroeconomic factors have all contributed to this development. Customer preferences in Panama have shifted towards online matchmaking platforms. With the increasing use of smartphones and the internet, more people are turning to online platforms to find their perfect match. These platforms offer convenience, a wide range of options, and the ability to connect with potential partners from the comfort of one's own home. This shift in customer preferences has led to the proliferation of online matchmaking services in the country. Trends in the market indicate a growing acceptance and openness towards matchmaking services in Panama. In the past, matchmaking was often seen as a last resort for individuals who were unable to find a partner through traditional means. However, this perception has changed as more people recognize the benefits of using matchmaking services. Matchmaking is now viewed as a legitimate and efficient way to find a compatible partner, leading to an increase in demand for these services. Local special circumstances in Panama have also contributed to the growth of the matchmaking market. The country has a relatively small population compared to other countries in the region, which can make it more challenging to find a suitable partner. This has created a demand for matchmaking services that can help individuals expand their pool of potential partners beyond their immediate social circles. Underlying macroeconomic factors have also played a role in the development of the matchmaking market in Panama. The country has experienced steady economic growth in recent years, leading to an increase in disposable income. As a result, more people are willing to invest in matchmaking services as they see it as a worthwhile investment in their personal lives. In conclusion, the Matchmaking market in Panama has been growing due to shifting customer preferences towards online platforms, a growing acceptance of matchmaking services, local special circumstances, and underlying macroeconomic factors. As these trends continue, it is likely that the matchmaking market in Panama will continue to thrive in the coming years.

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.