Twitter IPO Hits Pay Dirt From Data Mining

Facebook (FB)… Groupon (GRPN)… Zynga (ZNGA)… Angie’s List (ANGI).

When we saw a rash of social media companies like these go public, I was skeptical.

To me, while their services were popular, their business models – their actual way of monetizing that popularity – didn’t seem very secure, never mind lucrative.

I mean, who wants to own Angie’s List anyway? Great website… weird stock.

The main problem? While the lion’s share of these web companies’ revenue comes from advertising, as mobile technology advances, they’re struggling to keep pace.

For example, when Facebook launched last year, CEO Mark Zuckerberg and his band of overzealous investors faced one glaring issue: no mobile ad revenue… at all. And the stock tanked.

Oddly enough, Twitter faces the same issue. I say “oddly enough” because Twitter isn’t supposed to have a mobile problem.

Its “microblogging” concept is designed specifically for tablets and smartphones, so users can give immediate commentary anywhere… anytime.

But like everyone else in the social media industry, when people use Twitter’s mobile app, the company makes far less money from advertising.

However, unlike everyone else, Twitter has a lesser-known side business that’s proving very lucrative…

And when the company filed its S-1 last week, everyone focused on ad revenue and ignored this…

Almost a year ago, Tech & Innovation Daily noted that Big Data is one of today’s seven most investable technology trends.

Research firm, IDC, agrees. It says the Big Data market is growing seven times faster than the entire information technology sector and is on pace to be worth $16.9 billion in two years.

And Twitter proves why…

The company is selling its data.

You see, thanks to its public, real-time data, nothing compares to Twitter. Its endless stream of news, events, trends, opinions and experiences provides a wealth of insights and opportunities.

In fact, it’s spawned a vast commercial ecosystem called “Social Listening.”

Emerging from the innovation pipeline are social data firms – companies that essentially collect, dissect and analyze information. And they’re buying Twitter’s data to help their clients get a leg up on the competition.

Here’s how…

Ever wonder how Google (GOOG) ranks search queries?

Or how supercomputers crunch numbers light-years faster than humans?

In a word… algorithms.

When it comes to processing and analyzing data and calculations, computer algorithms have become critical. Especially given today’s immense (and increasing) amount of data.

Just ask the clients of social data-mining firms.

Companies like DirecTV (DTV).

Let’s say there’s a service outage in a certain area. Rather than wait for an onslaught of calls and complaints, DTV can use Twitter’s social data analysis to stay ahead of the problem.

It’s certainly not the only one…

• The United Nations uses Twitter algorithms to identify civil disorder hotspots.
• Five Guys worked with Washington, D.C. social data firm, New Brand Analytics, to analyze how its hamburgers measured up against the competition.
• Human resource departments use Twitter data to evaluate potential recruits.
• Even the Library of Congress is cataloging tweets.

And Wall Street is using Twitter’s algorithms to get an edge on the market.

Take Dataminr, for example…

Dataminr serves active traders – something it did very well last week.

Five minutes before news broke about the shooting on Capitol Hill, Dataminr issued a sell alert to its subscribers. Its algorithm had picked up on tweets from eyewitnesses about the shooting.

The algorithm analyzed the timing and location and determined that an urgent situation was developing. One with a high chance of a negative market response.

The program warned Dataminr… Dataminr warned its subscribers… and moments later, the S&P dropped by 20 points.

Fund managers also use algorithms to assess “sentiment scores.”

In other words, they trace investors’ mood on stocks – the forces that can push stocks higher or lower.

Very powerful, profitable information.

The question is: If knowledge is power, what’s the price for it?

Well, Japanese company NTT Data (Tokyo: 9613) paid Twitter $35.6 million per month last year for data.

Along with Gnip, Data Sift and Topsy, these four companies account for the bulk of Twitter’s data revenue.

They’re essentially data brokers. Or what Twitter calls “certified data resellers.”

Twitter sells its data to these firms – who, in turn, sell to companies looking for niche information.

So how is Twitter’s competition responding?

Well, Facebook has largely avoided the data-mining business, as it isn’t set up for conversations and real-time events like Twitter is. Rather, it’s geared towards sharing among friends.

But with an eye towards Twitter’s additional data revenue, Facebook has recently partnered with companies to provide information about certain topics.

Like Twitter’s “trending” application, tools can focus on people in certain areas and monitor emotive phrases. They can then create a heat map or sentiment score.

For decades, businesses have spent countless hours and millions of dollars trying to understand the past. But the innovative minds at Twitter are measuring the present.

They know that whenever we use social media, we provide vital, actionable information for companies to use in the here and now. And the company is finding ways to monetize that information.