
The rate that things happen
online tends to influence the rest of our world. It began when instant messaging on PCs made a move to SMS text message on mobile phones, giving friends and lovers instant access to each other
whenever and wherever, as long as both were in an area with cellular service. Now, Twitter and Facebook status updates on Google, Microsoft Bing and Yahoo real-time search let us know the moment
someone goes to the bathroom. You get the message.
Real-time search moves into real-time marketing this year, where thousands of bits and bytes of collected data determine which ads to serve
up, along with what Web site configurations to show each individual consumer, based on an IP address and information stored in the browser cookie.
Adchemy Chairman and Chief Executive Officer
Murthy Nukala tells me companies should construct every ad and Web page for a specific individual on the fly. That means ad and Web site platforms require machine learning. These operational systems
determine what to serve up based on the data collected. They change the ad, message, price, and landing page configuration based on what they know about someone through the browser connecting with the
site. "We use real-time marketing across time, and dynamic advertising across segments," he says.
People have begun to find "religion" in data and realize that information in real time
provides better campaign performance, Nukala says. But how do you make the correct decisions across search, mobile, social and widgets?
"This year Facebook becomes as important as Google,"
Nukala says. "It will happen, in part, because Facebook gives you the data to define segments and experiment with marketing strategies. It provides marketers with accessibility to the data to
experiment, much more than display or search."
Facebook claims 50% of active users log into the site each day, and this would mean at least 175 million users every 24 hours, according to
Econsultancy, a digital marketing company that shares additional stats on marketing.
Maybe
so, But advertisers need to keep data collection simple if the industry wants to move more marketing dollars online, notes Jere Doyle, president and chief executive of Prospectiv. Boil it down to a
few pieces of data that matter. While standing outside the conference doors at OMMA Performance last week in San Francisco, Doyle explains how too much online tends to confuses those without
experience collecting and analyzing the stats -- the marketers and media buyers who traditionally purchase print, television or radio ads.
Doyle serves up more advice while we stand there
talking. Start by taking a few pieces of data, such as gender and the ability to identify prior customers, and work from there because these marketers barely use the data they have in the correct way,
he tells me. They don't have the same skills, not yet anyway, as direct marketers, so they become easily overwhelmed with the mounds of available data. "They are getting better at using the data, but
they're not as sophisticated as the industry thinks," Doyle says. "They are sophisticated people, don't get me wrong, but they don't have the time and the resources to sort through and understand the
data, which sometime leads them to confuse many of the stats."
The importance of collecting data has become very obvious to investors, too. BlueKai, which helps online advertisers target
messages based on demographic, geographic and other actionable information, reported closing a $21 million venture capital round of financing Monday. The deal, led by GGV Capital, included
participation from Redpoint Ventures and Battery Ventures. Total funding for the company now stands at $34.7 million.
If offline advertisers aren't moving online fast enough, perhaps they
need to heed lessons learned from the electronics industry. During the mid-2000s, electronics companies tried to introduce new products, such as Blu-ray players or DVRs that record four programs at
once, to jumpstart consumer spending. Adoption of these devices took off slower than expected, because the gadgets were too complicated for the average person to learn how to use, or many consumers
didn't want to take the time.
Perhaps ad executives will learn from the mistakes made by the electronics industry.