Around five years ago, Johnny Lee met Stephen Tse while living in New York City. The two wanted to find bars that played Lakers games, but were disappointed to find that there wasn’t any easy way to search such a thing. Tse continued working at Google Maps, where he was employed at the time, while Lee resumed his globetrotting for work.
Still, the idea stuck with them. A few years later, the two reconnected in San Francisco. And today they’re announcing a $1.3 million funding round and a new version of their “social search” app Spotsetter.
Let’s face it: The only reason we do much of anything these days is so we can comment about it on social networks. If you couldn’t Instagram it, would your burger even taste like anything at all? If you didn’t tweet about it, did you really even read that article? If you don’t Facebook check-in, can you actually be sure you ever went to that nightclub in Tel Aviv?
The only thing that gives us more pleasure than social network commerce-bragging, however, is reaching out to our friends for recommendations of cool places to check out. There’s that friend of yours who knows all the great music venues in Berlin. Or your other friend who’s an expert on all things coffee. Or your other friend who you know just got back from a trip to Nairobi. And increasingly–and crucially–these friends are probably broadcasting their tastes and check-ins on Facebook, Twitter, Instagram, or Foursquare.
Even if you only share location-specific content once or twice a week, says Lee, consider the sum of even such minimal activity across your 1,000 Facebook friends with comparable behavior. All of a sudden, each of us has access to a trove of taste-making data from the set of people we care about most–the people we actually know. That taste is a kind of currency that operates within real-world social networks (like class) has long been a subject of discussion among sociologists. Now, with the rise of apps like Spotsetter and of taste-related data on Instagram and elsewhere, it’s also a topic of great interest to technologists and the investors who back them.
The writing is on the (Facebook) wall. “To ignore what friends like and say is impossible,” says Lee.
How exactly does the app work? You pull it up and authenticate through Facebook. Spotsetter then dives into your social graph, doing its best to reckon which of your friends is the sushi-phile, or which is the ramen aficionado. Spotsetter offers up suggestions on whose advice to take on what matter; you can manually override these, telling the app that it’s really Peter and not Paul whose advice you’ll take on burrito joints, at least while in Texas.
You can then pull up a map of your location (or anywhere else, for that matter) and begin telling Spotsetter just what it is you’re looking for. Lee says that while traditionally mapping apps have a more “transactional” nature–you pull it up, search for directions, print those and leave–Spotsetter finds that its users are rapidly getting addicted to merely browsing the social layer Spotsetter brings to mapping. “Users come in and next thing you know they’re spending half their time in discovery mode,” says Lee. “‘Oh, I didn’t even realize that so-and-so has been here, or that Jack is so into ramen noodles.’”
Spotsetter isn’t too worried about monetizing just yet, says Lee; it’s focused on building a community of users. Search, with its tendency to reveal rather specific intent on the part of the searcher, has been fairly easily monetized in the past (see under: Google). Lee also notes that his app enables a curious feature that he calls the “physical click-through.” Just as Google can track whether a user clicks through an ad, Spotsetter can determine whether a user discovered a business through the app and then checked herself in there later; Spotsetter might collect from a brick-and-mortar business in such cases.
Lee says the app is off to a good start; the company has already processed 5 million profiles, and has considerably swelled its staff since the funding round. The most trying moment for Lee and Tse’s leadership skills, however, may have come back when the startup was a fly-by-night operation run out of the pair’s apartment.
Lee and Tse had devised an algorithm for crawling a major site that Lee will only say is “similar to TripAdvisor”; their bit of code crawled the site in order to index venue listings that the pair could then use in a prototype of their app. Only, a bug in their code led to them crawling far more of the website than they intended–something like 2 million venue listings rather than two thousand. Thinking the Spotsetter boys were launching some sort of attack, the TripAdvisor-like site called up Comcast and had its website blocked for Lee and Tse.
The only problem? Comcast wound up blacklisting not just Lee and Tse, but everyone living in their apartment complex. “Neighbors were saying, ‘What’s going on? We can’t access this website anymore,’” recalls Lee. The site was blocked for months.
“Two people writing code in an apartment can cause interesting things to happen,” he says.