Catching The VIBE: Targeting The User-Generated Video Space
Behavioral Insider: We've heard a lot about video networks recently, but yours seems geared especially to user-generated content. Why did you choose that space?
Sladek: Publishers have realized it's one thing to bring together hundreds of thousands or millions of people to share videos. But it's another order when you start figuring out how to monetize it. Advertisers are anxious to reach the 13 to 34 demographic. They know social networks are where they are. But beyond that fact, they need-- and so far, have lacked--ways of making sure their message is received in a context that is conducive to the brand.
BI: So in targeting the UGV space, the mandate is, "first, do no harm"?
Young: Agencies are adamant about that. The first thing they're interested in is finding ways of insuring that nothing you do on a network will endanger their brand. So the first step in targeting is to make sure advertisers have maximum visibility into the kinds and categories of content that exist on a site, and a mechanism for controlling where they will not be.
BI: So at this point the basis of targeting is type of content?
Young: Content targeting is only a starting point. We're interested in getting advertisers to think through how to target a world not of passive consumers, but [one] where there are thousands of content creators.
Now, the first reflex of most agencies after worrying about putting their brand in an awkward place is to ask, 'Well what's the point of my having my brand's pre-roll or post-roll seen in connection with the video of Betty's last birthday party?" Well, what we're finding out is that running your Fortune 1000 brand video with Betty's is a great idea if you know that not only is Betty a prime prospect for your product, but that dozens of Betty's friends, who also closely fit the demographic and personal interest profile of your brand, will share Betty's film--and beyond, that several dozen more friends of friends often refer to Betty's recommendations about products and other favorite things. So the question with social networks we think is going to become, in a new way, how demographics and lifestyle interest interact with behavior.
BI: You've referred to the acronym VIBE--or, Viewer-Initiated Brand Experience. Could you explain how that fits in?
Young: We think in a social network advertising is content or it's nothing. So based on their interests and behavior, we recommend paid ads to users who are engaged with video content--but we don't impose them.
We offer a variety of units. One is an "ad ticker" overlay, which displays a suggested trailer or other paid video ad in a thin strip of text at the bottom of a requested video while it plays. Another issues a still-frame call to action at the end of a video, inviting users to click through to watch a paid ad. These are delivered strictly on an opt-on basis. Advertisers can also deploy a prominent brand presence below the requested video as it plays, and then showi a brief still frame ad followed by a :15 or :30 post-roll spot. Ultimately, users on the network need to decide what advertising content is most relevant to them.
BI: What kinds of behavior are most relevant in this space?
Young: We're still scratching the surface of how to use data streams. We can track the particular types of videos viewers click on, and whether they watch pre-rolls or post-rolls more readily. How long they watch videos, optimally. Those are basics.
But one really big thing that differentiates social networks is the very high percentage of users who log in. So the profiles go deeper than gender, age, location and occupation--into particular interests, hobbies, favorite products etc.
There are also many more different cues to behavior on a user-generated site than on a traditional content site. One new category to look at and integrate into targeting is the whole area of influence and peer-to-peer reference and recommendation networks. It may be just as crucial to learn how a consumer interacts with others on the network than the specific subject of videos he or she is watching right now. Network behavior includes how many people forward the recommendations, how active their inflow and outflow of network communications are, how often their recommendations are solicited or how often they give recommendations.
BI: That brings up the field of social network analysis, Six Degrees of Separation.
Young: Yes, this is all stuff that's been relevant to other disciplines but remains relatively new to advertising. It's going to become very integral to studying the way advertising is actually used in a user-generated network.