Inside Foursquare: Checking In Before the Party Started (Part II)
In Part I of our insider look at the earliest days of Foursquare, we saw everything go downhill in a flurry of technical catastrophes. But we also caught a glimpse of light at the end of the tunnel.
Context & Ripple Effects
Foursquare arrived at this profile riding a breakout spring: it faced off with Gowalla at SXSW in March 2010 for the title of top location-tagging service, added roughly 100,000 users in ten days on the back of that push, and sat near 500,000–600,000 users by mid-March according to contemporaneous counts. It had also aired its first television commercial on Bravo in February and absorbed the [[a:none|Please Rob Me]] privacy backlash over tweeted locations — though that last thread belongs to the corpus record rather than a linkable piece.
Epicenter's two-part series is an origin story, not breaking news: Part I catalogued the flurry of technical catastrophes of the earliest days, and Part II reports light at the end of the tunnel as conditions improve. What makes the retelling matter is the field it lands in — by April 2010, Twitter, Google, Foursquare and Gowalla were all confirmed to be racing into the location space as the land rush hit full swing.
First-order effects
- Foursquare's engineers must convert fragile launch-era infrastructure into systems that survive SXSW-scale spikes, because every outage now hits a six-figure user base rather than a small beta circle.
- Gowalla, its head-to-head SXSW rival, gets a ready-made talking point whenever Foursquare's reliability wobbles — uptime quietly becomes a competitive metric between the two.
Second-order effects
- With Twitter, Google, Foursquare and Gowalla crowding into location, venues and media partners such as Bravo gain multiple suitors for check-in-driven promotions, strengthening their hand on deal terms.
- Privacy episodes like the Please Rob Me reaction force every player in the race to build location-sharing controls into the product itself rather than treating them as policy fine print.
Third-order effects
- If the land-rush pattern holds, accumulated check-in volume becomes the durable asset: whoever builds the richest place database can extend into recommendations, advertising, and data licensing while the bare check-in mechanic commoditizes across competitors.
The trend: Location services in 2010 are racing from novelty check-ins toward scale-dependent data businesses, where infrastructure reliability and place databases — not the mechanic itself — decide the survivors.