The disruptor du décade is called Big Data, and it involves the collection, slicing, and dicing of fragments of information that can be rapidly assembled to identify subtle macro trends or create actionable profiles that precisely target unique individuals.
The vastness of opportunity is characterized in this quick paragraph from IBM:
“Every day, we create 2.5 quintillion bytes of data — so much that 90 percent of the data in the world today has been created in the last two years alone. This data comes from everywhere: sensors used to gather climate information, posts to social media sites, digital pictures and videos, purchase-transaction records, and cellphone GPS signals, to name a few.”
Throw in who individuals are, what they read, when they are in a particular place, where they shop, why they buy, and how they feel about public policy, and you have a wealth of valuable data.
The commercial potential for Big Data is the reason Facebook achieved a record high valuation of $104 billion when it began selling its shares on the stock market. Even though Facebook’s shares tumbled in the aftermath of its clumsily managed IPO, the company continues to gather more personal information about people and their friends than any other platform yet devised.
Don’t be misled by the critics who pounced on recent articles questioning Facebook’s potency as an ad medium. While General Motors famously acknowledged immediately before the IPO that it was scrapping its $10 million Facebook ad budget, and a Reuters poll found that only one in five users admits to responding to Facebook ads, the skeptics are missing the point.
Facebook’s success, or lack thereof, will not depend on selling banner advertising, whose pricing and efficacy will necessarily degrade as the supply of page views expands exponentially. Facebook will make its bones, if there are bones to be made, by innovating ways to commercialize the torrents of data it continues to accumulate.
Can’t imagine what the winning Big Data app will be? Don’t feel bad. Facebook might not know, either. But the $4 billion in cash collected at the IPO window equips the company to fund any number of science fair projects and business pilots. Eventually, Facebook — or perhaps someone tinkering in an IBM lab or a dorm room filled with discarded Red Bull cans — will come up with the way to turn the growing stores of data into gold.
There is precedent in Silicon Valley for retroactively lashing a revenue model to a company already in progress. When Google was launched in 1996, the founders had no idea how they were going to make money with the speedy and accurate search engine they had devised. It wasn’t until late 2000 that Google began selling the ads that now accompany its search results.
Google’s AdSense system creates an audience of one when a user types a few keywords into the search box, instantly triggering up to a dozen links to merchants who bid for the right to post ads related to the targeted expression. Although merchants pay only for the limited number of times someone clicks on an ad, the system worked well enough to deliver the preponderance of the $36 billion in revenue that Google reaped in 2011 (a sum equal, by the way, to 1.5 times the combined print and digital ad sales of all the newspapers in the land).
Impressive as Google’s do-it-yourself system is in terms of performance, productivity, and profitability, someday we will look back on it as a quaint, if not to say crude, form of targeted advertising. Because the keyword system responds only to estimated location and the keywords chosen by the user, it cannot leverage all the variables, context, and nuance that a robust Big Data profile could provide.
If Google’s currently dominant digital advertising engine could be surpassed by faster, better, and cheaper ways of connecting buyers and sellers, where does that leave newspapers?
To date, publishers have applied the same business model to everything from print and the Web to the latest mobile and social platforms: Build the biggest possible audience.
This approach, unfortunately, is exactly at odds with the point of Big Data, whose goal is to connect individuals with information specifically tailored to them.
The quicker Big Data applications develop, the faster the large but untargetable audiences traditionally delivered by newspapers will become an anachronism, thus limiting their utility to consumers and their value for advertisers. While most publishers aren’t equipped to be first movers in Big Data, they should be paying attention — and ready to jump into partnerships that prevent them from being left behind.
Alan D. Mutter is a newspaper editor who became a CEO in Silicon Valley and is now a consultant to media companies on technology and to technology companies on media. He blogs at Reflections of a Newsosaur (newsosaur.blogspot.com).