{"id":7784,"date":"2018-04-08T21:38:10","date_gmt":"2018-04-09T01:38:10","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-digit\/submission\/tinder-romance-algorithm-just-keep-swiping\/"},"modified":"2018-04-08T21:38:10","modified_gmt":"2018-04-09T01:38:10","slug":"tinder-romance-algorithm-just-keep-swiping","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-digit\/submission\/tinder-romance-algorithm-just-keep-swiping\/","title":{"rendered":"Tinder romance algorithm: just keep swiping"},"content":{"rendered":"

Launched in 2012, Tinder has become one of the top dating apps thanks to it user friendly design, mobile-first approach, and matching algorithm. By 2018 Tinder has been downloaded over 100 million times, available in 30 languages, created 20 billion matches, has had 1.8 billion swipes every day resulting in 1.5 million dates every week. By the end of 2017 it had over 50 million members. Match Inc., its parent company reported revenues of $1.3 bn in 2017, with the analysts suggesting most of the growth coming from Tinder users, 79% of which are millennials. \u00a0The company gets revenue from both its members and advertisers. For members, it offers TinderPlus (and recently launched TinderGold), that offer exclusive and premium features, as well as paid-for options like Tinder Boost.<\/p>\n

\"\"<\/a><\/p>\n

Tinder is a data-driven company with data in the heart of the decision making, especially in such teams like engineering and marketing. Tinder accumulates a vast amount of information about user\u2019s preferences and applies machine learning to suggest ever better match. To do that, the company uses two key tools. First is its matching algorithm, which is based mainly on finding similar personalities among the users in close proximity, combined with your internal score, called \u201cElo score\u201d, that ranks a user in terms of likability by others. Elo score is a ranking, that goes beyond the profile photo and pure attractiveness. In short, it is a \u201cvast voting system\u201d, which users create when swiping left or right on other people.<\/p>\n

Second is its bespoke behavioral analytics platform called Interana, which provides<\/p>\n

behavioral analytics for conversion, retention and engagement, enables delivery of the behavioral insights in seconds despite dealing with large amounts of records, and provides self-service and a complete solution for the teams to use fast and easy. Interana segments users into cohorts to offer more advanced analytics (groups can range in demographics, age, gender location etc.).<\/p>\n

One of the main challenges Tinder had to overcome was the fact that humans lie, which makes relying on the data that Tinder members put in their profiles tricky. Tinder has successfully acknowledged it and while it does use user initial information and preferences, it constantly analyses user\u2019s behavior on the platform to identify any difference, but also compares it with the behavior of similar users (just like Amazon does) to come up with new suggestions. For example, if a person claims that he\/she looks for someone not older than 26 years old but keeps approving profiles of people in the range of mid 30s, the system will adjust to showing more of such profiles.<\/p>\n

Thanks to its proprietary data software and rapidly expanded user base, Tinder has an advantage to learn and adapt its platform to the best users\u2019 liking fast, adjusting both its matching algorithm and the features. Tinder has been formidable in launching new features like super like, social feed, smart photos, and partnership with Spotify.<\/p>\n

Beyond the speed of innovation, data analysis based on the personality (which is used by most of the dating apps) provides advantage for the niche Tinder decided to play in: impromptu drinks date or a \u201chookup\u201d rather than long-term relationships. This is a head wind for the company against such long-term players like eHarmony.com or match.com, since, as the CEO of Match Inc. said himself, \u201cwe\u2019re decades away from predicting chemistry between people\u201d. To reinforce this perspective, a recent study of married couples shows that only 50% of the similarities of partners personalities contribute to the couple\u2019s happiness.<\/p>\n

Future challenges.\u00a0Multiple recent studies suggest that matching algorithms are just slightly better than random matching. Dating apps like Tinder will need to invest and innovate substantially more to move to the next level of data analytics. New breakthrough matching algorithm that can identify chemistry and predict future expectations of a user can create substantial competitive advantage for Tinder, potentially allowing it to expand its currently niche dating market and appeal to long-term relationships seekers.<\/p>\n

    \n
  1. https:\/\/www.cnbc.com\/2018\/02\/21\/tinder-new-user-growth-could-be-cut-in-half-jp-morgan-says.html<\/a><\/li>\n
  2. https:\/\/www.esquire.com\/lifestyle\/sex\/a12149373\/tinder-statistics-study\/<\/a><\/li>\n
  3. http:\/\/blog.gotinder.com\/page\/9\/<\/a><\/li>\n
  4. https:\/\/www.datingsitesreviews.com\/staticpages\/index.php?page=Tinder-Statistics-Facts-History<\/a><\/li>\n
  5. https:\/\/expandedramblings.com\/index.php\/tinder-statistics\/<\/a><\/li>\n
  6. http:\/\/ir.mtch.com\/static-files\/4b8c3e80-5bfe-4185-a113-9fe17e3c59f3<\/a><\/li>\n
  7. https:\/\/practicalanalytics.co\/2015\/05\/29\/love-sex-and-predictive-analytics-tinder-match-com-and-okcupid\/<\/a><\/li>\n
  8. https:\/\/www.fastcompany.com\/3054871\/whats-your-tinder-score-inside-the-apps-internal-ranking-system<\/a><\/li>\n
  9. https:\/\/insidebigdata.com\/2015\/10\/05\/tinder-and-interana-find-a-match\/<\/a><\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"

    Launched in 2012, Tinder has become one of the top dating apps thanks to it user friendly design, mobile-first approach, and matching algorithm<\/p>\n","protected":false},"author":2020,"featured_media":7788,"comment_status":"open","ping_status":"closed","template":"","categories":[1003,2015,272],"class_list":["post-7784","hck-submission","type-hck-submission","status-publish","has-post-thumbnail","hentry","category-dating-apps","category-mobile-dating","category-tinder","hck-taxonomy-organization-tinder"],"connected_submission_link":"https:\/\/d3.harvard.edu\/platform-digit\/assignment\/competing-with-data-challenge\/","yoast_head":"\nTinder romance algorithm: just keep swiping - Digital Innovation and Transformation<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/d3.harvard.edu\/platform-digit\/submission\/tinder-romance-algorithm-just-keep-swiping\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Tinder romance algorithm: just keep swiping - 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