What Facebook’s IPO reveals about big-data analytics
Those obsessed with Mammon will read Facebook’s IPO prospectus for what it says about making money. Others of us with a more geeky bent will pour over what it reveals about how the company handles data. It starts with arresting stats: 845 million active monthly users; 100 billion friendships, and every day 250 million photos uploaded and 2.7 billion likes or comments.
But that is just the eye-candy. The substance is buried deep in the prose, under the heading “Data Management and Personalization Technologies.” Get a load of this:
“loading a user’s home page typically requires accessing hundreds of servers, processing tens of thousands of individual pieces of data, and delivering the information selected in less than one second. In addition, the data relationships have grown exponentially and are constantly changing.”
And then there is this:
“We use a proprietary distributed system that is able to query thousands of pieces of content that may be of interest to an individual user to determine the most relevant and timely stories and deliver them to the user in milliseconds.”
“We store more than 100 petabytes (100 quadrillion bytes) of photos and videos.”
“We use an advanced click prediction system that weighs many real-time updated features using automated learning techniques. Our technology incorporates the estimated click-through rate with both the advertiser’s bid and a user relevancy signal to select the optimal ads to show.”
But my favorite is this:
“Our research and development expenses were $87 million, $144 million, and $388 million for 2009, 2010, and 2011, respectively.”
So R&D expenses grew almost five-fold in three years. Considering Facebook had $1 billion in profit on $3.7 billion of revenue last year, the company’s research budget came to 10% of sales. This is very healthy (albeit natural, perhaps, with a company boasting such hefty profit margins). According to the OECD, the top 100 R&D-inteisve companies in the IT and telecoms sectors spend an average of nearly 7% of revenue on R&D.
Most of the fruits of the R&D is probably kept internal and covered under trade secrets. But for that generous sum, the prospectus informs us:
“As of December 31, 2011, we had 56 issued patents and 503 filed patent applications in the United States and 33 corresponding patents and 149 filed patent applications in foreign countries relating to social networking, web technologies and infrastructure, and related technologies. Our issued patents expire between May 2016 and June 2031.”
But the most interesting thing is how much was not exposed in the prospectus. In a section were Facebook purported to explain its analytics, with an example of how it uses elements on a webpage to determine what ads to show (page 87), the example was so juvenile as to be meaningless.
It is actually funny the way Facebook keeps quiet on analytics, considering that the first time the word appears is on page 12, when Facebook cites it as one of the “risk factors” that could ruin the business:
“our inability to improve our analytics and measurement solutions that demonstrate the value of our ads and other commercial content”
Though it is loath to make too much of it, since it is its main source of value, Facebook is an analytics company before anything else. Google might have been the world’s first big-data IPO. Facebook may be the first analytics one. But you wouldn’t know it from its IPO prospectus.