Dapper Dives Into the Display DR Dream


dapperADOTAS – CEO James Beriker sets me straight: The name Dapper “is not about how we dress.”

“Some people think Dapper is a gentleman’s clothing site from London,” he quips.

No, the company is called Dapper because they are makers of “daps” — “data maps,” the nickname for the content feeds Dapper helps build.

In 2006 cofounder Eran Shir, a black hole physicist (“and a really interesting guy,” Beriker adds) had a startup in Israel focused on Internet infrastructure usage and the analytics surrounding it. He met Jon Aizen, computer scientist from Cornell, who was also passionate about enabling browsers to view content on their own terms, as HTML construction is constraining.

Together they built a platform that enabled developers to create APIs for assembling feeds, ultimately allowing consumers to digest content in whatever form they wanted. The machine-learning technology examines the structure of a website and the hierarchy within the HTML and discerns similar elements. The integrity of the dap can withstand site modification.

In 2008 Dapper boasted 100,000 daps and a million XML calls a day, but Shir and Aizen were feeling limited — daps could be put to further use. But they saw opportunity in online advertising’s most notorious slacker.

Although it was an established infrastructure in every website, display advertising was never relevant or engaging — no surprise that CTR had fallen through the basement because the ads weren’t resonating with consumers

“It’s astonishing to me that it’s still a $9 billion industry,” Beriker comments.

Dapper saw the potential for a new display ad unit that would essentially turn a product catalog into a live feed. However, through using user actions on advertisers’ sites and other intent data to gather data representing user intent, these ads could be targeted to put highly relevant — and dynamic — content in front a user, changing the way advertisers and agencies buy and optimize display ads.

“And along the way, make the web a better place,” Beriker adds, which was the original intent. Hey, if you can change the world and make a buck, who am I to judge?

Hence Dapper’s display platform was designed to enable marketers to not only index but dynamically present content in various ways. Powered by Dapper’s IntentMatch technology, the platform extracts products, offers and relevant content from advertisers’ sites. In particular, retailers with highly liquid inventory — online travel agencies such as Expedia and Kayak — are fond of Dapper’s services as it updates in real-time.

Yesterday the company released the Dapper Display DR Platform as both a full- and self-service display solution for direct-response-focused large advertisers that combines a media buying platform with the ability to create, traffic and target dynamic ads based on advertiser inventory.

Part of the solution is pure convenience — it’s a confusing ecosystem out there, Beriker says, and although more brands are realizing the potential of display and audience targeting, it’s difficult to figure out where to start.

“We’ve essentially unified or consolidated different elements of the stack,” he says. “Rather than going to four or five places to do all this, we can do all the efficient media buying and run real-time media buying across the Google DoubleClick Ad Exchange and the other exchanges.”

While a typical DSP enables high-volume segment-buying based on data across exchanges, Dapper uses algorithms to inform the media-buying decision — bids are based on how well an offer might convert based on the ad served. The technology employs 15 to 20 factors such as time of day and strength of intent when determining the probability of conversion — the process takes a whole 50 milliseconds.

“In search marketing, you use a single platform to place your bid for the keyword and serve the static text ad — it’s holistically optimized,” says Beriker, who was previously CEO and president of Efficient Frontier, which blends search and display for performance marketing. “In Dapper Display DR, our ability to buy media based on intent signals and serve an ad based on the probability of conversion allow for real efficiency.”

Say the ad served was based on a flight query previously made by a user, the final optimized ad would display flights from the user’s preferred airlines and departure times, as well as price  and seat availability changes since the last query. There could be a discount included for converting right then and there. Afterward, an advertiser can employ retargeting techniques — so the user bought a flight, won’t he or she need a hotel?

The self-service platform makes it simple to serve offers and automatically build dynamic creative via the users website or feed. Setting up where the crawler hunts for inventory on a site is surprisingly intuitive. Don’t take my word for it — check out the video below.


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