On a Saturday morning in August of 2006, Sergey Brin and a team of Googlers flew to Los Angeles to meet Tom Anderson and his MySpace team. By the next afternoon, the two founders shook hands on a three year $900M contract. About twelve months later, I found myself as the product manager for the team in Marrakesh, Google’s executive board room, reporting the state of affairs to Eric, Larry and Sergey.

After signing the letter of intent, Google assembled a superb five-person team of machine learning experts and tasked them with improving ad targeting on MySpace and other social networks. At the time social networks like LinkedIn, Bebo, MySpace, Hi5, BlackPlanet and others generated about 40% of ad impressions for AdSense, but only 2 to 3% of revenue. The disparity was extreme.

When Sergey signed the contract with MySpace, Google hadn’t built the technology to properly target ads on social networks. But he believed it could be developed. And he was right.

Over the course of the next 18 months, the engineering team experimented and tinkered. They discovered that the language on social networks varies greatly from the language on the rest of the web. We threw away the dictionaries used for AdSense targeting and built new dictionaries using social-native dialects. The team modeled the dispersion of conversations through out the network in different ways - testing, testing, testing. Every week, we reviewed the experimental results.

Marrakesh is a long, thin room with grey walls, red couches. Two monitors hung on the wall at one end and Eric sat at the head of the table on the other side. When we stood up to present, we reported that in just a few quarters, the engineering team had increased revenue by greater than 10x. More importantly, they proved intent could be extracted from social media conversations at scale.

As social media usage continues to grow exponentially, users will pour out their opinions into conversations across the web in ever greater numbers. Within the morass of LOLs and emoticons, there is real value to be found.

Redpoint has invested in two companies which also pursue this idea: BlueFin, which Twitter just acquired, and Quantifind. Both BlueFin and Quantifind harvest data from the social web to glean meaningful insights and grow revenue for their customers.

We are only at the beginning of understanding the value of data contained within social media. I believe there is another 10x hidden in that tweet.