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Ad Tech Startup Yieldbot Says It's Obliterating Paid Search


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Things are heating up for local ad tech. Last week, Apple announced that it was tapping Adelphic Mobile for help with the launch of its much-anticipated iAd. Meanwhile, word is that Boston ad tech firms such as DataXu and OwnerIQ continue to grow steadily.

And then there's Yieldbot, an New York-based ad tech startup with its development headquarters in Maynard, Mass., which raised an $18 million Series B round this summer (but remains little known in Boston). The company's mission is to get increasingly improved results from display ads, and it claims to be even more effective than paid search.

They point to results for proof. One health care services organization reaped 20 percent higher conversion rate from Yieldbot than paid search. Meanwhile, a major food brand moved its entire non-branded keyword buying to Yieldbot after it beat search ROI by 26 percent. And a major home improvement company scored higher leads with Yieldbot than paid search for 13 consecutive months.

How it works

It began five years ago, when SEO expert and startup advisor Jonathan Mendez found that some of the primary landing page optimization and search indexing operation principles could be applied to premium display and web-based mobile advertising. The technology that his team devised is capable of essentially capturing and organizing real-time consumer intent by tracking and analyzing clickstream and search data. The result? Ads are more actionable, and everyone wins: Publishers see more valuable content and higher revenues, and consumers are exposed to ads for things they actually might want to buy.

Three years ago we predicted that Yieldbot could provide the "biggest breakthrough the online advertising world has seen in a decade" - and it's made big strides to deliver on that promise for its client roster, which includes publishers like Meredith Corporation, BlogHer and Rodale.

Yieldbot doesn't want the "ad tech"  label to limit its scope, though (and ad tech, of course, faces steep challenges as a sector). The startup insists that it defies categorization.

The two words that Yieldbot is perfectly comfortable associating itself with, however, are performance and relevance: proving its positive impact for buyers with back-end metrics, effective CPM and revenue, and ensuring that ads reflect what consumers actually want.

"This funding will help ensure we continue to be able to define ourselves," the team wrote in a recent blog. "When you create something entirely new and never seen before you get that privilege."

Co-founder and CTO Richard Shea, who leads the development team in Maynard, maintains that Yieldbot goes beyond the realm of ad tech because these tools can drive publishers to realize the full potential of their content. As an example, he cited how the company can derive insights into keywords or what topics are trending both at the publisher level and across their marketplace.

"That type of data can drive products that go beyond the narrow scope of maximizing yield on their existing ad units," Shea said. "I think that the Yieldbot is both set up well to benefit from and also an enabler and driver for allowing publishers to be more intelligent."

Next chapter

"I think that the Yieldbot is both set up well to benefit from and also an enabler and driver for allowing publishers to be more intelligent."

So what's next? Now that Yieldbot has additional funding, Shea revealed that there are several initiatives the company is focusing on. The top priority is continuing to scale the business in an efficient way. Currently, Yieldbot employs about 50, and the startup plans to double in size by the end of 2015.

"While we've continued to innovate this past year in areas like creatives and automated optimization, we also have created a growing list of things that we want to do to build on the valuable data that we have across our publisher marketplace," he said.

The bottom line: Yieldbot is leveraging cutting edge technologies at the forefront of managing big data and machine learning to solve highly challenging problems.

Image via Shutterstock.


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