Quantcast Adds Self-Serve Targeting Tools For Publishers And Ad Buyers

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Online analytics provider Quantcast is unveiling a new self-service tool for its brand targeting solution, Quantcast Advertise for Branding. After months of beta, starting today publishers and advertisers can better manage deals directly based on specified audiences. Quantcast CEO Konrad Feldman told AdExchanger the goal is to be viewed as the company that makes real-time bidding and programmatic buying a little bit more attractive to its publisher and marketer clients.

The new tool has three components, which include demographic measurement, where marketers can organize segments around age, gender, parents, education and income, among other things. Then, there’s something Quantcast calls “Spendographics,”  where high-value audience segments modeled from premium purchase data can be chosen for a campaign. Lastly, there’s the Custom Advertiser Segments, which represents custom audience segments built from predictive modeling, based on an advertiser’s unique audience.

AdExchanger: What is the reasoning behind the new dashboard functions? What’s the improvement? And how does the introduction of the self-serve option change  a customer's relationship to Quantcast?

KONRAD FELDMAN: Real-time advertising should not be limited to just RTB. There's a great opportunity for the web's premier destinations to leverage programmatic technology to bring advertisers the most relevant combination of content and audiences. Quantcast Advertise for Branding and its new dashboard feature allows our publishing clients to deliver more valuable audiences to brand advertisers and gives our advertising clients the ability to better find, reach and buy their exact audience at scale across premium content from the publishers they choose.

How has the analytics landscape changed since Quantcast was launched in 2006?

When we started Quantcast, we saw the opportunity to make digital advertising act and perform much like search. The search segment came to dominate online advertising because it took advantage of the fact that content wasn’t broadcast – content was delivered to an individual device and it could be adjusted in real-time based on available data. Search works so well, it’s a case where everyone wins: the advertiser, the seller, the consumer. Many consumers don’t even differentiate search ads from the natural results because it’s all relevant.

We felt that the rest of digital media would soon start to better reflect what was happening in search. The reason we came up with the name Quantcast was because broadcast meant “delivering a message to everyone” and the quantum of delivery for print and television was the whole audience. In contrast, the quantum of delivery for IP-delivered media is the impression. That’s the ultimate fragmentation.

Barely a year after our commercial launch, Google introduced the DoubleClick Ad Exchange, which was centered on price discovery. The idea being, that if a marketer was willing to consistently pay more for an ad, it must be more relevant. And it can be good for everyone.

How do you explain the disconnect between the amount spent on TV commercials versus the CPMs for digital impressions?

It depends what you’re looking at when you talk about the value and cost of advertising. If we look at television, there are roughly 18 minutes of commercials aimed at viewers every hour. So it’s not going to be very relevant and therefore marketers will only pay so much for it. As a result, publishers have to show more commercials to pay for the content. In the end, consumers are faced with even more irrelevant ads. We have the opportunity with online, and eventually television, to change that entirely.

How does the technology change that?

The requirements of “tech” in “ad tech” are much more profound than they’ve ever been. For one thing, there hasn’t necessarily been a lot of “tech” in “ad tech” and the term is something of an oxymoron. The entities that have dealt with fragmentation are largely based on human-brokered relationships – the old way of doing things. That doesn’t mean that the human element won't be a part of the way ads will be bought, sold and priced. But the aspects of initiating and completing the transaction will rely more and more on automation and the human element will be reduced.

Big data is a trendy term and it’s changing a lot of industries, advertising among them. We probably process 750 billion new records every month. There are three technology skill sets in doing this. One involves producing a real-time infrastructure that is robust enough to interpret, act and respond to the data.

Another piece is how do you extract the best information from the data. After all, an impression is data.

What do you make of the recent trend toward viewable impressions?

It’s a great idea. Of course, if an ad is never seen, it can't influence. But while that’s an easy thing to comprehend, in practice, it’s quite difficult. The internet is complex, with lots of different browsers, different content systems, different ad formats and a range of difficult technologies. There’s a lot of work to do though and we’re supportive of this idea. Being able to answer whether something is viewable, however, is just the first step. The most important one is measuring how effective it is once it's been viewed.

In addition to viewable impressions, there’s also a growing demand that digital analytics encompass what’s going on in users’ offline world as well. Is Quantcast able to tie in that aspect of consumers’ lives? For example, can you do anything with information that comes into consumers’ set-top TV boxes?

The work that we’re doing with offline data does involve bridging the outcomes related to offline data through companies’ customer relationship management systems, and other third parties’ information, back to online.

We’re not playing in the addressable TV space. It’s an exciting market, but it’s still in the experimental stage. There’s not enough scale and there’s not enough standardization. There’s a lot of set-top boxes out there. And the ad market isn’t organized around set-top box data yet. In the future, I don’t think it will quite mirror the way the Internet works, but I do think we’ll all be watching our own content when we want it. And at that point, we won’t need those 18 minutes of TV advertising every hour. If you’re an enormous, established company, you can afford to focus on what may be coming 10 years from now. But when you’re a startup, you need to focus on the market that is here and now.

What about mobile advertising? The view is that it’s growing by leaps and bounds, but it’s still a fraction of the overall online marketplace. How do you approach that and how valuable is that space to Quantcast, especially since smartphone usage appears to be so far ahead of the ad spending there?

We talk about mobile being a distinct channel today, and there’s going to be a panoply of distinct devices with geo-targeting as an important vehicle for delivering ads. It wasn’t that long ago that we talked of “going on to the internet.” The internet is ubiquitous, we’re always connected so no one talks like that anymore.

We measure a lot of mobile media consumption, a lot of apps as well. I know it’s popular to say that mobile advertising doesn’t work. But that just isn’t true. However, mobile does have an attribution problem.

What do you mean by that?

We’re so used to online being a performance medium for the advertiser. Companies measure their media spend very carefully when they run a campaign, and they’re waiting for a specific outcome: “sign up for the test drive” or “download the coupon.”

If you look at the use of mobile, someone may view the ads, they may be exposed to the ads – but they may not be completing the form or clicking on the ad. And it doesn’t mean that someone sees a mobile ad and then acts on it later on their PC or their tablet and convert. So the question is, “Does that cross-device experience count as an attribution?” Being able to prove its efficacy is what we’re looking for, and in a sense, that’s the fundamental problem of all advertising, which makes mobile’s challenge more about attribution than a medium problem.

Do you think of Quantcast as being in the “ad effectiveness” arena with comScore and others?

No. Quantcast uses Big Data to help marketers and media sellers. Our business is in measurement and creating relevant advertising. If you think about our product set, our measurement products are free for everyone. When you’re looking at aggregate information that might be used to identify an audience to sell sponsorship or ads on a site, all the measurement is free.

In terms of helping clients create a relevant advertising experience, that data has to be applied and actionable in real-time. We provide that to the publishers so they can identify the right audience to their marketers and increase their yield. And marketers buy that information on a CPM, and increasingly, on a cost-per-action basis.

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