What I Want From Location Services
Posted by Sebastian in Technology, tags: Caterina Fake, Check.in, Facebook, Foursquare, Gowalla, Hunch.com, Twitter
With all the recent success of LBS (Location Based Services) companies, like Foursquare, 2010 is quickly turning into the year of ‘the check-in’. That’s the term used for the voluntary location broadcast by users on these services. So if I’m sitting in a coffee shop and want to let my network know (or part of it), I check in at that coffee shop and voila, now my location is broadcast in the feeds of those that are subscribed to me.
Very cool!
Except there isn’t one LBS that does this. Like mushrooms after a rainstorm, they’re popping up everywhere: Foursquare, Gowalla, Loopt, and now even Twitter and Facebook are getting in on the game. With the exception of the last one, none of them have the network reach to be an all-encompassing solution. By which, I mean, if I use Foursquare but some of my friends use Gowalla, the system doesn’t work. And even in the case of Facebook where it’s likely that 98% of my contacts are registered (except for those two friends of mine that still believe modern society died with the advent of the push-button telephone), there’s the issue of me broadcasting my location to the wrong people. Ooops, didn’t want my coworkers knowing that I’m on a sunny patio drinking a beer on my ’sick’ day.
Coming out of SXSW this year, numerous people commented on ‘check-in’ fatigue: trying to keep all your networks abreast of your location was too damn tiring! And there’s at least one company, Check.in, working on a universal…ummm, check-inner.
But the thought of trying to organize my network of friends, business contacts, Twitter contacts and random hangers-on into groups that I feel comfortable broadcasting my location to, well it gives me a headache.
Instead, why not take a page from Caterina Fake’s newest venture, Hunch.com, and develop an algorithm that learns, based on your location, time of day, day of week, and relationship to contact, whether or not to automatically broadcast my location using whichever service I’m plugged into. That’s a scary word, isn’t it? Automatically! The idea of automatically sharing our location has been a barrier to LBS growth for more than a decade. The security implications are enormous.
But what I’m envisioning is an engine that learns, based on your behaviour and the aggregate behaviour of others (a la Hunch: if most single 34 year old males tend not to broadcast their location on Friday nights to their mom and coworkers, we can probably assume that’s a given – unless it’s manually overridden by that single male 34 year old at that specific location). What my system would have is a simple learning mechanism that would learn from you whether or not it should broadcast your location to certain people.
So you enter a restaurant and the system politely asks you if you’d like to share you location at all. If you say no or don’t respond, no location will be shared. If you say yes, it’ll ask you through a set of simple steps whether those contacts that previously had access to your location can get it again, and then prompt you with a few other suggestions, based on who the algorithm thinks you might want to broadcast to. At any time you can of course manually share your location via the traditional check-in.
Through this learning process, the system will gradually learn your preferences to the point where it can automatically broadcast your location (with your permission, or by prompting you for approval) to previously approved contacts.
The benefits of this system versus the current manual check-in process are: less time spent on checking in, more people will try using location based services (particularly on Facebook) given this big hurdle is removed and potentially more people in your network receiving access to your location (most of us have connections that we forget to include in invitations or location broadcasts because we haven’t seen them in awhile and so they’re not top of mind, but you would love to see them if you had the chance).
So although I’m a huge fan of LBS and am really excited to see it grow throughout 2010, I can’t wait for someone to solve this tedious check-in problem using simple, smart technology.





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