The Rise of Behavior-Based Networking
With the ascent of the smartphone into our every waking hour, a generation is growing up so plugged in that their social lives are suffering. So we watched as an array of dating applications emerged to facilitate interaction.
The issue with platforms like Tinder is a superficiality which ignores a large portion of the population. Besides, matching based on looks or a brief bio seems like a first step considering the technology we have available.
I’d argue the next generation of interaction tools will focus on matching our actions, in large part because of the current accidental implementations of behavior-based networking.
The example that first comes to mind is Uber Pool and Lyft Line, two very similar platforms that connect drivers and riders on similar routes. Three people in a car who likely wouldn’t otherwise meet are connected, usually begrudgingly. And while interaction is usually the exception, I see a future where you can opt for ‘talking’ or ‘no talking’ vehicles, much like Amtrak’s Quiet Car.
In researching, I discovered Waze Carpool, another more explicit behavioral matching service involving transportation.
But this requires another download, it’s a manual experience (I go at this time, at this place…) and most folks simply aren’t downloading new apps, even online dating ones.
However, Google knows everything about us. It knows when and where we go to work, it knows the traffic, it’ll even send alerts when we need to leave. So what about an alert that pairs user behavior?
I can see a future Google Maps push notification saying “Three other people nearby have similar driving schedules — would you like to learn more about Google Ridesharing?” Even with self-driving cars, these systems optimize for efficiency. Now, efficiency can also facilitate social experiences.
In a similar fashion, I can imagine a future where GrubHub notifies you that other folks nearby are ordering lunch. They could ask whether you’d like to join them in their takeout of choice, based on known preferences. Or Airbnb suggesting folks you might want to travel with.
And of course, the idea that started this rabbit hole, “Netflix Dating.” Netflix knows when you watch, what you watch, and where. All that data could result in an amazing matching service, employing user behavior pairing to help facilitate more social experiences.
On the other hand, even as an opt-in feature, many would find this supremely creepy. Folks are already discomforted by Facebook’s eerily accurate advertisements. And despite applications like Happn, which connect you with people who have crossed your path previously, the most popular apps (Tinder, Bumble, Grindr) use a limited scope for matching.
But these scopes are rudimentary, and a shallow level for common ground. In one psychological study, virtual dates were used to increase the viability of matches, prioritizing what the researchers termed “experiential attributes” (rapport, match in sense of humor) instead of “searchable attributes” (height, interests, income). Success in compatibility, it would seem, is difficult to obtain with surface level matches.
Another study finds correlation between individuals’ brand preferences and relationship compatibility. So perhaps an Amazon Dating service is not far off, as disturbing as that may sound to some.
Of course, compatibility doesn’t guarantee friendships nor relationships. But in the end, folks find connection through shared circumstances – from “we’re in the same place” to “we’re on the same app”. The more opportunities technology can provide, the better off society becomes, as we work towards a more connected future.
More:
