One in four Aussies under the age of 44 met their partner online. Oddly enough, as a 19-year-old woman, I do not know any of them. My experiences with Hinge and Tinder have been more about playing “smash or pass” when the dinner conversation lulls. But the stats seem to place the dating apps as a pretty good investment.
So, how do dating apps work? It helps, like many things, to think about it, like economics. Imagine that all of your potential partners exist in one market. It is your prerogative to invest time and energy (this is called a search cost) into finding the match that best suits you.
Enter dating apps! More people are within your reach and are brought to your attention more quickly. Gone are the days of singles nights at your local pub – all you need are some good photography skills, strong swiping abilities, and probably a nice glass of red wine.
This process is “thickening” the market, which describes increasing the options available to any given consumer. Is this a good thing? Depends on who you ask. Studies have shown for two decades that minorities are exponentially more likely to use dating apps.
The market has even pivoted so that some markets specialise in hyper-specific consumer bases. BLK, a dating app for people of colour, has had more than seven million downloads. While Grindr, designed for gay, bi, trans, and queer people, has more than 12 million active users.
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Some less renowned dating apps include Bristlr (those attracted to facial hair), Align (which connects you to those with compatible star charts), and Kitty Nip (for cat people). Whatever your idea of purr-fection is, I guess.
No matter which app you swipe right on, users are given access to “thickened” markets tailored to their preferences. A feature of these markets is differentiated goods, meaning that no two options are the same. So, consumers must invest the “search costs” to find the outcome that best satisfies them.
That brings us to a downside of these thickened markets: determining the opportunity cost of choosing one partner over another takes more time and effort, which may be particularly difficult when an algorithm tailors every option to suit you.
