Color is a new photo sharing app that builds social networks based on proximity. You take a picture with the app, and it turns around and starts grouping you with and sharing photos from other people nearby who have done the same. Sounds kind of dumb, right? Why would I want to see photos from nearby strangers?
Well, Sequoia thinks there’s something there, and has put $41 million into the company before it’s really even launched (thanks to a killer pitch deck). “Not since Google” have they seen this. Given that “this” currently refers to an app that I can’t even get to work on my phone, I’m left hoping that there’s a lot more going on here.
So what could that be? I’m going to put on my magic hat of credulity now, and describe what I (yes, I, random internet wantrepreneur) would be willing to bet $41 million on in this space.
Color is being run by Bill Nguyen, who sold Onebox for $850M in 2000, Lala to Apple for over $80M in 2009, and (at least until 11:41am today) spent time at AdGent. I’m not going to say that his presence means Color will be successful, but I do take it as a pretty good sign that there’s no possible way their actual business story is “Color shows you photos taken by people in the same room and then money pours out”.
From the TechCrunch writeup:
Color is also making use of every phone sensor it can access. The application was demoed to me in the basement of Color’s office — where there was no cell signal or GPS reception. But the app still managed to work normally, automatically placing the people who were sitting around me in the same group. It does this using a variety of tricks: it uses the camera to check for lighting conditions, and even uses the phone’s microphone to ‘listen’ to the ambient surroundings. If two phones are capturing similar audio, then they’re probably close to each other.
Remember The Dark Knight, when Batman hacked into everyone’s cellphone and streamed back sonar data to build a cohesive picture of what was happening everywhere in the city? That sounds awfully similar to what’s going on here – photo, GPS, and audio streams feeding back to Color in such a way that they can build a real-time model of where all their users are, who they’re with, and what’s happening around them.
With that kind of technology, who cares what their frontend does? Based on the quality of the first release of the phone apps, they’re clearly not sweating it too much. Whatever hook they try to snag users with is just a way to get that datastream, so they should ride whatever wave is currently popular. This week it’s Instagram and Path, so, sure, do that. Next week it’s going to be something else, so next week they’ll shift their apps towards that, or if they really can’t figure out how to get traction, they’ll release an api and let others do it for them. It doesn’t matter how that data comes in, as long as it comes in.
The web is training advertisers how to most effectively work with real time data (tracking cookies, ad auctions, sentiment analysis, twitter monitoring, all of that). How many companies work on this? How much money is being spent on these efforts, and how much is being made? There’s already one $190B company in this space on the web; the startup that can bring the same sort of tools into the real world might actually have a shot at becoming another.
Facebook, Foursquare, Yelp, Gowalla, Brightkite, Loopt, and everyone else with check-in functionality are already going for this. The biggest differences with Color seem to be that they want check-ins to be implicit byproducts of actions users have other motivations for (you’re not trying to get a free soda, you’re taking a picture to, uh, show to strangers in the same room), and that they’re handling far more inputs than just location.
These differences are both potentially huge. Other services risk crossing a mental line where explicitly checking in feels like work done for compensation (which is bad, which is why Foursquare is set up as a game), whereas this is an attempt to keep motivation purely social. And using multimedia opens up the door for all kinds of data points – facial recognition to keep track of people who aren’t actively using their product, brand recognition to note logos on clothes or labels on bottles, song recognition to track what music people are actually listening to – that advertisers would pay through the nose for.
Taking the credulity hat back off, even though I really do think the potential business models could make a ton of money, I’m equally convinced that this initial attempt at getting users isn’t going to make it very far. With $41M in the bank, though, they’ve got plenty of room to fail.
Update: Bill Nguyen confirms all of this almost point-by-point in an interview with Business Insider:
Photo sharing is not our mission. We think it’s cool and we think it’s fun, but we’re a data mining company.