Agenda

The buyers are now sellers. Agency trading companies start looking like Wall Street hedge funds. Automation in the online ad industry seems poised to replace humans with algorithms. Suddenly the art of planning is mired in the complex science and pricing of RTB. And figuring out the formulae for attribution among these many channels requires advanced math degrees. From staffing to ad ops to potential conflicts of interest in client relationships, the new display machine is raising important questions about what the digital agency of the future looks like. We bring in some of the people who have been crafting this new machine with the agency world to discuss whether the new display requires a new agency. 

The new 800-pound gorilla of display marketing is loaded with inventory and dense user profiles, but is Facebook really proving to be an important part of the inventory mix for marketers? The company’s ad programs shift as quickly as its privacy policies. The audience is migrating rapidly to mobile media where the ad models remain even less clear. And despite anecdotal evidence of success, the real value of display within Facebook continues to be debatable. And now the company is bringing its data outside the network walls and letting the DSPs and exchanges in. How are agencies meeting the complex challenge that Facebook poses both to the media plan and to the business of display. Can social display inform and enhance a larger marketing plan? Are media buyers moving budget away from other display buys to enter this arena, and how does ROI in the social network compare to returns from the new ad tech machine being built outside of Facebook? 

By some counts real time biding is responsible for up to a third of display spend. That represents an enormous change in just two years since these platforms emerged. But what have buyers learned about executing campaigns via RTB most effectively, and what has this data-rich channel taught the buyers and planners that they didn’t know before? We ask both buyers and providers to explore after two years of experience whether RTB represents just a more efficient method of flying campaigns, or if it changes, enriches or challenges digital buying as we know it? 

Display advertising was counted down and out only a few years ago as media buyers hedged against the economic meltdown with tried and true performance bases search buys. But display is roaring back, showing substantial growth in the last year, as marketers buy in to tech and data-enhanced targeting systems that purport to rival search in their effectiveness. But where are the true drivers of growth here – on the tech-driven demand side platforms or from higher-impact advertising units that are making display more like print and TV? A research analyst weighs in with a market overview followed by a panel discussion acorss multiple models.

“Native” ad formats and models are the latest meme to buzz its way through the ad industry in recent months. Publishers from BuzzFeed to StumbleUpon, Facebook to Tumblr are offering marketers non-standard ad opportunities that are designed to flow more naturally with the ways in which customers actually use their service. Defenders say that going “native” is precisely the kind of beyond-the-banner thinking digital advertising requires. But others argue that it is hard for these models to scale and to fit neatly within a media plan. Site specific deals must be struck and discrete creative must be applied to every deployment. Is this really where budget-constrained campaigns need to head? Or are native formats just the leading edge of post-advertising future where marketers have to think beyond the banner, the spot, the pre-roll and the interstitial? 

Data, data everywhere, but what inputs should marketers drink? In this panel of media planners and buyers we ask the practitioners to speak out of cases and explain how and why they made decisions to include and exclude data from their targeting mix. Everyone talks about having to filter through the waves of data now available to marketers. But let’s get down to cases and uncover people deploying campaigns vet the data and map its against the goals of client and campaign? How and how often are these professionals optimizing campaigns base don’t he real-time data ad exchanges and real-time bidding feed back relentlessly? What best practices are emerging in order to put this complex ad targeting machine to best use? 

And you thought the Luma chart was confusing. Trying to figure out how to assign credit and blame in a campaign’s performance is even more complex than the ad technology economy that powers these efforts. As all marketers claim to move beyond simplistic “last-click” attribution, what are they really doing now to assess what feeds effectiveness? More importantly, how are these models being used to allocate time and money for that next campaign? We bring in the attribution gurus to share their state of the art for assessing this multi-channel world and who gets the credit…or blame.