Online Dating - Kenya

Kenya

Highlights

Revenue in the Online Dating market is projected to reach US$387.20k in 2024.
Revenue is expected to show an annual growth rate (CAGR 2024-2029) of -2.76%, resulting in a projected market volume of US$336.60k by 2029.
In the Online Dating market, the number of users is expected to amount to 1.2m users by 2029.
User penetration will be 1.8% in 2024 and is expected to hit 1.9% by 2029.
The average revenue per user (ARPU) is expected to amount to US$0.39.
In global comparison, most revenue will be generated United States (US$1.39bn in 2024).
With a projected rate of 17.7%, the user penetration in the Online Dating market is highest United States.

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The Matchmaking market in Kenya is developing at a steady pace, driven by changing customer preferences and the rise of online platforms. Customer preferences in the Matchmaking market in Kenya are shifting towards convenience and efficiency. With the increasing hectic lifestyles and busy schedules, individuals are finding it difficult to meet potential partners through traditional methods such as social gatherings or introductions by friends and family. This has led to a growing demand for matchmaking services that can provide a quick and efficient way to meet potential partners. The rise of online platforms has also played a significant role in the development of the Matchmaking market in Kenya. Online dating apps and websites have gained popularity among Kenyan singles, providing them with a convenient and accessible platform to connect with potential partners. These platforms offer a wide range of features such as personalized profiles, compatibility matching algorithms, and instant messaging, making it easier for individuals to find and communicate with compatible partners. In addition to customer preferences, there are also local special circumstances that have contributed to the development of the Matchmaking market in Kenya. The cultural norms and traditions in Kenya place a strong emphasis on marriage and family, making matchmaking an important aspect of the society. Matchmaking services are seen as a way to uphold these cultural values and traditions, and are often sought after by individuals who are looking for long-term relationships and marriage. Underlying macroeconomic factors have also played a role in the development of the Matchmaking market in Kenya. The country's growing middle class and increasing urbanization have resulted in higher disposable incomes and greater access to technology, which has in turn fueled the demand for matchmaking services. Additionally, the high rate of internet penetration in Kenya has made online platforms more accessible to a larger population, further driving the growth of the Matchmaking market. In conclusion, the Matchmaking market in Kenya is developing due to changing customer preferences, the rise of online platforms, local special circumstances, and underlying macroeconomic factors. As more individuals seek convenience and efficiency in finding potential partners, matchmaking services are becoming increasingly popular in Kenya. The growth of the middle class, urbanization, and internet penetration have also contributed to the development of the market.

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.