iPhone app from Color.com is a new photo-sharing tool that streams images based on two layers: location and social. The revolutionary application of photo-sharing and consumption comes from Bill Nguyen, the brain behind the music service Lala, which Apple (AAPL) acquired in 2009. He’s pulled together a legendary team, which includes the company president Peter Pham, founder of BillShrink, and DJ Patil, the former chief scientist at LinkedIn.
What makes this app stand out from the crowd is its use of public data streams, which center around photo-sharing. When viewing photos in this app, you’re able to see those taken by people within 100 feet or so. Filter out this stream once more, and you can limit it to those photos taken by you and your specified friends in the vicinity. When viewing photos, you can see your groups, as well as those lumped by another group’s social connections.
Monetizing a novelty
This sounds like a pretty fun app, but it’s still a novelty at this point. It is designed to be used in specific situations where you’d like to share and flip through photos based primarily on your location. Color isn’t an app you can use alone, and photo-sharing beyond the app is non-existent. So it may seem surprising that the founding team had $41 million in pre-launch investment capital from high-profile firms, including Sequoia Capital, Bain Capital and Silicon Valley Bank. To put this in perspective, Color is starting out with more capital than Google (GOOG) received from Sequoia. In fact, the amount provided by Sequoia is the most the firm has ever invested in a pre-launch startup.
Monetizing the app will be a top priority, especially as Color dabbles in a mobile industry niche that has become highly competitive. As the mobile realm elevates the commercial relevance of location and social connections, however, Color’s seeking a first-mover advantage in developing a photo-sharing app around these two marketable demographics. Color intends to incorporate local deals and other ads into its photo-streams, evolving a unique data set that looks at one’s social reach and geo-spacial vantage point.
More importantly, Color intends to improve its own data set through constant analysis. It groups nearby individuals based on similar lighting conditions, and even ambient sounds, taken in through the phone’s microphone. This will lend to an ad-supported network that creates its own perspective, based on implicit and inferred activity. What the world ultimately does with this specialized data, we’ll have to wait and see.