The core of any quality product is analytics and analysis of large data. You are required to follow your intuition and to examine a lot, tons of statistics in order to be successful. Successful products constantly develop and test hypotheses. They run several solutions in parallel and compare their results with each other: different models of monetization, multiple forms of onboarding, and various matching algorithms.

The artificial intelligence along with machine learning has been used in the dating industry lately. These algorithms try to determine the user’s behavior, his or her intentions, the ability to pay and build a special and unique path for a particular purpose.

There is also, of course, some luck and a sense of the market. Sometimes it can play a decisive role, as it happened, for example, with the founder of Bumble Whitney Wolf Herd. The launch of her dating platform, where only women were allowed to chat with men first, is also successfully coincided with the height of the #MeeToo actions in the USA. In this case, the company was able to find its special place in the dating market.

How will the dating industry develop in the nearest future?

An increasing number of people consider online dating to be basic nowadays. Statistics have shown, that about one in three couples is formed online, and for partners of the same sex this indicator is twice as high. Such adjustment of perception is one of the main sources of expansion of the industry.

On account of such development, dating platforms developers are facing new challenges. Distinct communication creates a demand for new standards of interaction between two users online. The most popular type of content is streaming and video. And the global quarantine has only increased the need for a more complete type of communication. So, we can expect the embedding of video calls and messages into all of the modern dating products in the nearest future.

Moreover, technologies, powered by AI and machine learning can make applications truly personalized and save users time.