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Perinan online dating

perinan online dating-44

Image Credit: The secret behind perfect match making by Ok Cupid (acquired by in 2011 for $50 million), and e Harmony is the big data analysis techniques behind the scenes.In a world of data driven supremacy, it is not possible to connect people unless dating sites connect with online dating data.

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Mc Kinlay was not satisfied with the compatible match making algorithms the dating sites were using as it did not help him find his Mrs.Online dating sites combine "data" and "analytics" to help people find their perfect soul mate.The real hero behind the success stories of online love is the big data analytics technology and infrastructure that help people find their perfect life partner based on their stated preferences and behavioural matching.There is high probability that users might not be honest in answering the questionnaire or users end up providing inaccurate information unintentionally.For example, females usually tend to lie about their weight, age and build while males might provide inaccurate information about their height, income and age intentionally.The Online dating companies provide questionnaires’ of up to as much as 400 questions.

Users have to answer questions on different topics varying from hypothetical situations to political views and taste preferences to increase their online dating success rate.

Image Credit: Online dating statistics state that, of the 54 million singles in US, close to 40 million users have signed up with one of the popular dating sites like Match.com, Ok Cupid, e Harmony, Hinge or Tinder.

Users of online dating websites spend an average of 22 minutes every time they visit an online dating website and close to 12 hours a week in online dating activities.

Some of the dating websites are making efforts to generate online dating data for big data analytics by analyzing the behavior of users on the dating website based on the kind of profiles they visit.

Few other dating sites employ collaborative filtering (preferences and tastes of several users are grouped into sets of similar users) to recommend dates based on their preferences and tastes.

With intense competition in Online Dating industry, companies are making every effort to maintain the credibility by matching the perfect partner to the perfect person at the perfect time.