On the other hand are real-time programmatic advertisers. Programmatic advertising promises reach against specific audiences, even down to the individual level. This enables advertisers to understand the true value of specific audience-level criteria, and dial up and down bids to serve ad impressions across the open market. Many of these advertisers hail from the world of paid search marketing, one of the first forms of programmatic advertising to emerge. This group believes that transparency, control, and the fundamentals of a free market economy across advertising are the keys to near- and long-term ROI. I think they’re right too.
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But this isn’t really a matter of who’s right or wrong. These two camps already co-exist, each with their own successes, and very little overlap in talent. (Don’t believe me? Go to Content Marketing World, and then attend an event run by AdExchanger. You won’t run into the same people).
This brings me to some core questions I’ve been exploring:Is it time for these two camps to become one? And if so, does the work we’ve done in the world of search (SEO coming together with PPC) provide the blueprint for integration?
I believe there is a larger opportunity here for marketers, and consumers of marketing services, when these talents and technologies are brought together. The promise of marrying smart, laser-focused advertising with personalized and compelling experiences is exciting. This is the same focus on user experience that Craig Danuloff wrote about when he said that Quality Score optimization was far more important than bid optimization for Google AdWords. In each of these scenarios, focusing on relevance across the entire communications continuum trumps optimizing any one step in the process.
And as an industry, there’s a lot of open yardage before us. My friend and mentor Bruce Rooke calls this looming movement “data-driven content marketing,” or “DDCM.”
The vision for DDCM is simple to articulate: hyper-relevance to the consumer, from advertising through to experience. The complexity comes in its execution. Successful DDCM means that the content the organization is authoring and/or curating is both relevant and timely to its recipient. The relationship between brand and consumer then, is iterative and evolutionary. Smart ad tech and data analytics must be in place to track customer interactions, learning incrementally more about every individual with every touch. Advertising too, learns from this growing body of data and uses it to re-invite consumers back into the experience at pivotal moments.
Over time, and with enough observations, the entire DDCM framework can put predictive analytics to use to recommend content and assets across a brand’s owned media channels. This “recommendation engine” too is adaptive, and relies on machine learning technologies to continually refine itself. The end result is one-to-one consumer engagement, at scale.
I realize that this may not be an entirely new construct for everyone, and that some examples of what I’m describing already exist in the wild. So consider this a larger, industry-wide call to action. The future of customer-centric marketing and advertising resides squarely where content, advertising, and data analytics intersect. SEMs have known this for years. The name of this movement is DDCM.
I love this simple but insightful summary of the industry and what is trending. As a recruiter, I find that candidates tend to be firmly in one camp--either content or data. But both are necessary and vital in reaching the right audience. Programmatic and native advertising will co-exist.
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Wow, this is very interesting. I've never thought about a "recommendation engine" for content but it's a great idea and a logical next step in evolution. Our real time decisions software at Entrigna can easily be leveraged for this purpose. Do you think the world is ready for this or is this realistically several years out? Anyways, thanks for a very thought provoking post.
Do the folks at the NY Times know about this?
Nice article and agree with all except "machine learning", as the minute a false positive client experience is recorded, the machine will go very fast at learning the wrong things; therefore, human knowledge must feed the machine, based upon previous client interactions and media/content consumption. The future is indeed bright.