The Hinge dating application launches a new function today aimed at improving its recommendations, according to whether the coincidences had successful dates in the real world or not. The function can also help solve one of the main problems with today's dating applications: that nobody knows how well they work. After all, it's one thing to get matches and have conversations, but it's quite another to turn them into appointments, let alone into a long-term relationship.
With a new feature called "We Met", Hinge will ask users a few days after sharing their phone numbers if they had an appointment and, if so, if they would like to see that person again. This data will be used as a signal to inform the Hinge algorithms and improve the matches, if the user returns later to the application.
During beta testing, Hinge says that 90% of members said their first dates were excellent and 72% said they wanted to go for a second.
"Ultimately, if you went to a date with someone and thought it was great, that's the clearest sign that we've come very close to your type of person. people like that person, we can show them to you, "says Hinge CEO Justin McLeod.
By "how that person" is not a matter of physical appearance or some sort of profile classification, to be clear.
"You can not really add people to their components and try to decipher what someone's ideal person is," explains McLeod.
Instead, Hinge uses the collaboration filter, people who like X also like Y, to help inform their coincidences on that front.
With the release of We Met, Hinge will now know when the dates are successful or not, and eventually, why. He also plans to combine the We Met data with other signals, for example, if users become inactive in the application or delete their accounts, as well as survey data by email, to find out which dates may have become relationships.
This is something for the first time for the dating applications industry, which today is incentivized to keep users "playing" in their pairing games and spend money on subscriptions within the application, not leaving them. It is not in the financial interest of dating applications, at least, to create relationships (that is, large numbers of users).
This influences the design of dating applications; They do not usually include features designed to connect people in real life.
For example, they do not make suggestions of events, concerts and other things to do; they do not offer maps of restaurants, bars, coffee shops or other public spaces nearby for first dates; they do not offer integrated calls (or gamify unlocks a call feature by continuing to chat in the app); they do not use instructions in the application to suggest to users that they exchange numbers and leave the application. Instead, apps tend to push users to chat plus – with things like buttons to add photos and GIFs, or even tabs to navigate Facebook-style news sources.
The problem of wasting time chatting in dating apps has now become so frequent that many user profiles today explicitly state that they are "not looking for pen pals".
Of course, dating apps, like any other way of meeting new people – will have their share of success stories. Everyone knows someone who met online.
But he states that, for example, Tinder is responsible for a whole generation of "Tinder babies" who are greatly suspects, because the company has no way of tracking if the matches are really quotes, and certainly not if they end up getting married and having children. He even said it in a recent documentary.
Everything Tinder has, or any of these companies, are actually anecdotes and emails from happy couples. (And this, of course, must be expected, with user bases in tens of millions, like Tinder.)
We find ourselves, meanwhile, actually focused on quantifying the success of dating real in Hinge, not in the commitment application. In the longer term, it could help establish Hinge as a place for people who want relationships, not just for serial dates or connections.
The feature is also another example of how Hinge takes advantage of A.I. Combined with user knowledge to improve matches. Recently, he implemented a function based on automatic learning, the most compatible, to help users with daily recommendations based on their activity in the application.
Hinge says that We Met will be released today, October 16, on iOS first. Soon Android will come.