Big Dating: Bringing real data to the dating game.

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The online dating industry has grown from strength to strength and is estimated to be valued in excess of £2Billion, globally. However, the future growth may hinge on how data and new technologies can be leveraged to improve user experience and matching outcomes. Some key questions: Does having more data about potential partners really make any difference in finding the […]

The online dating industry has grown from strength to strength and is estimated to be valued in excess of £2Billion, globally. However, the future growth may hinge on how data and new technologies can be leveraged to improve user experience and matching outcomes. Some key questions: Does having more data about potential partners really make any difference in finding the right match? What are key emerging trends that will affect the evolution of online dating? 

 

There are literally thousands of online dating sites worldwide, including over 1400 sites in the UK alone where online dating accounts for 25% of all new relationships. As might be expected, there are many types of players and business models in the industry, including online behemoths such as eHarmony or Match.com; mobile players like Tinder or Hinge; and increasingly niche specialists that match users based on specific demographic factors e.g. age / income / ethnicity / religion / location / sexuality etc. 
 
Regardless of player size, business model or target user groups, a quick web trawl reveals some salient observations about the current and future state of online dating, as follows:
 
  • Mobile dating on the rise – A key trend is the increasing use of mobile Apps for online dating – major players are refocusing on efforts to improve the multi-channel experience for their users.
  • A question of trust – Online dating services typically require user data for matching potential partners, but this can be greatly impaired by inaccurate data. Users often exaggerate personal attributes, or lie outright, in order to attract potential partners. Providers seek additional data (e.g. from retail, social media, entertainment and online sources) to augment data accuracy. However, there are privacy implications here that need addressing. 
  • User behaviours – Some providers prefer to base matches on actual user behaviour. The idea being that people often say one thing and do the opposite, and this is not unusual with online dating where user reaction to proposed matches can often reveal their true preferences, regardless of what is stated on their profiles.
  • Matching algorithms are far from perfect – In fact, some pundits view matching algorithms as mere “smoke and mirrors”, and that dating sites succeed simply by providing a larger pool of potential partners. Furthermore, human matching is a bi-directional proposition because, unlike Amazon recommends, your supposedly perfect match may not be all that into you! 
 
It is clear from the above that although data and technology will continue to be crucial in the evolution of online dating, the continued success and growth of the industry will depend very much on how well it can handle complex human behaviours, motivations and inconsistencies.
 
Matching algorithms aside, there are significant opportunities and scope for complex human behaviour modelling, and improved dynamic/predictive analytics, to cater for users’ changing preferences, circumstances and motivations. These need to be well in place before any claims and predictions of everlasting happiness via online dating can be tested or verified. Perhaps, if Romeo and Juliet had access to such computer enabled insight theirs may not have been such a tragic love story!

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