That being said, you can develop a dating algorithm that can set your product apart from other similar choices. Tinder matches people on locations, Dine utilizes users favorite restaurants and Hinge matches individuals based on common friends. But instead of using all these factors, come up with something unique for your matchmaking algorithm. After all, your dating application shouldnt be just another Tinder alternative.
Lots of dating apps use GPS as the basis for matching. They generate a list of users in the vicinity and set distance limits on search, then they provide users with general facts about candidates before making a decision on breaking ice and starting communication.
In such a scenario, algorithms are based on calculating the compatibility percentage by coinciding or matching answers asked by app bot. Even skipping the question might become the reason for matching in case a user and a potential candidate skipped ‘together.
Algorithms identifying patterns in preference and behavior are fed on data gathered from connected social networks profiles and analysis of likes comments and groups that users prefer. Incorporating this algorithm is associated with the employment of significant resources but the percentage of match accuracy justifies expenses.
To enhance user experience and provide highly accurate matching, dating apps also employ various advanced technologies like machine learning, VR, AI, etc. to take a step further in the personalization of the recommendations and suggestions. (more…)