Casual Dating comprises online services for the establishment of sexually oriented contacts outside of romantic relationships. These are not exclusively addressed to singles, but also provide people with ways to enter into extra-relational affairs like Ashley Madison. These types of online dating such as AdultFriendFinder or VictoriaMilan clearly focus on non-committal erotic adventures.
Data icludes revenue figuresin Gross Merchandise Value (GMV), Users, average revenue per user (ARPU), and user penetration rate. User and revenue figures represent B2C services.
Apps and portals focused on non-committal erotic adventures
Infidelity-based online dating service to enter into extra-relational affairs (e.g. Ashley Madison)
Niche dating, such as portals or apps for vegetarians
The Casual Dating segment comprises online services for the establishment of sexually oriented contacts outside of romantic relationships. It is the smallest segment in terms of revenues and has a high gap between paying and non-paying user numbers, while most users are not willing to pay for services. As casual dating contacts become ever more socially accepted, concerns centered around security and online safety become increasingly important for both the industry and the users. We therefore expect a significant improvement in the field of data protection within the next years. However, should these issues be neglected, further data breaches like the Ashley Madison hack might negatively affect user growth.
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.
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.
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.