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The phrase “online advertising business model” has become the punch line to a bitter joke for some startups, as ad revenue plummets and companies scramble for alternative revenue streams.
Nonetheless, world advertisers will spend $59.9 billion online in 2010, according to WPP plc’s GroupM unit, which is the largest buyer of media in the world. In a report earlier this month, the London-based media-buying giant predicted online ads will grow to 17 percent of the U.S. marketplace, even as ad spends decline overall.
Several ad optimization software startups believe they can increase that rate of growth by making online ads so relevant that users will look at them as a service, rather than as a nuisance. It’s a nut that tech companies haven’t yet cracked, say ad buyers.
But three Boston-area companies are trying as hard as they can, each with a different approach to figuring out what information each user wants to see — and what products each user might be likely to buy — from moment to moment online.
OwnerIQ Inc. thinks it can tell what you might be likely to buy, based on what you own. To determine that, the Boston company tracks owner’s manual downloads across a network of manufacturer and retailer sites.
“Ownership targeting is one of these things that’s a fundamental insight,” said CEO Jay Habegger. “I think it’s going to be a big component of the targeting universe.”
Meanwhile, ScanScout Inc. works exclusively with video, distributing video ads to go alongside video content. The company puts together an “interest profile” for each user of a client site by monitoring viewing habits.
One of the challenges has been to write an algorithm that can bring together viewing data, categorize the person and select the appropriate ad in milliseconds, said co-founder and CTO Steven Lee.
“It needs to be quick,” he said. “You can’t slow down the video loading of the publisher or the page loading. You can’t alter the user experience.”
Cambridge-based ChoiceStream Inc. takes a different approach. The company works with large retail clients who have high transaction volume. By amassing transaction data and crunching numbers in real time, the company’s software is designed to identify patterns that will predict what each user is likely to buy or click on next, and that determines product recommendations in-site and ads delivered to outside content publishers.
“I think we have accomplished what we set out to do,” said CTO Mike Strickman of the 9-year-old company, one of the longest-lived in the optimization space. “But we’ve only scratched the surface. The opportunity remaining is larger than the opportunity that has been realized to date.”
Ad optimizers still have knotty problems to solve, said Ryan Alderman, senior vice president in the Boston office of digital ad agency Razorfish Inc. — but it’s a solution advertisers and technologists feel intuitively they can reach.
“Conceptually, it all makes sense and everybody gets it and knows it’s going to work out,” he said. “But truly pulling it off … on one level it’s a technology problem, and on another level it’s a psychological problem.”
Thinking about human behavior conceptually, it seems intuitive, he explained, but getting a computer to think in the same way can be challenging.
OwnerIQ’s Habegger said he doesn’t doubt it’s something startups like his will be able to achieve. He just wonders whether the technology for providing custom creative content on the fly will keep up with the targeting capability.
“We’re going to quickly, within the next 24 to 36 months, have extremely effective targeting ability,” he said. “Then the battle becomes how you get their attention, because the creative hasn’t really kept up.”
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