“Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.
Today’s column is written by Martin Kihn, research vice president at Gartner.
In May, the IAB released version 1.0 of its Dynamic Content Ad Standard – only seven short years after its first OpenRTB spec. That 84-month lag points to the relative status of dynamic creative and programmatic targeting. Pity the poor creative, which has inspired comments over the years mostly on its unfulfilled potential.
As the IAB admits in the standard: “Media targeting has gotten much, much better, but creative has barely evolved.”
Of course, the message matters. And dynamic creative optimization (DCO) works well in areas where it’s applied: inserting retargeted product feeds and recommendations into banner ads. More inspired examples include text or image changes based on contextual data like temperature or tweets – culminating in that poster child of modern DCO, the weather-triggered Facebook ad.
Swapping out Docksiders and adding a pensive cloud to a Burberry’s banner is effective but feels like an early step in the grand march of creativity itself, which has the entire arsenal of text, image, sound, motion and storytelling in its toolbox.
Now there’s a confluence of forces that promise to level up the state of programmatic creative. This expansion of machine-driven DCO will be more visible than advances made in targeting. It will require internal reconfiguration and a new approach to traditional branding.
We’re ready for the rise of programmatic brands.
Dilemma Of The Dynamic Creative
The first generation of DCO tools – remember Tumri, Teracent and Dotomi? – were essentially authoring platforms. They made it easier for an agency team to build multiple versions of a banner ad in IAB standard sizes using templates. Headlines, images and click-through URLs could be swapped out, and versions were trafficked as regular ads. They were dynamically targeted, not dynamically assembled.
Most of the DCO tools were acquired and built into platforms owned by Google, Conversant, Sizmek, Adobe and others. Standalone providers such as Spongecell and Jivox continue to expand the boundaries of DCO with creative tools and intelligence, and Mirriad, SundaySky and others bring forms of personalization to video.
But DCO as a discipline has yet to rise above its tactical roots and emerge as a strategic weapon higher up the funnel.
There are good reasons for the decade-long DCO doldrums. Programmatic has always been more focused on direct response, which uses content that rarely wins the art awards (“BUY NOW!”). DCO can be complex to set up, test and measure and takes more overhead. Versions often don’t perform differently, causing confusion. Agencies make better margins on the big events like TV ads.
Less talked about, but arguably more important: Really talented creatives don’t like DCO. Who can blame them? What kind of a dreamer would feel fulfilled within a 300×250 canvas, oiling out 56 versions of the same headline and 16 image tweaks to test? You can hear their howls in Hoboken.
Creatives are adapting, but it’s obvious that truly scaled, personalized programmatic ads cannot be created by hand. Much of the work will have to be automated. And there was a sense in Cannes recently that some combination of more ubiquitous data and AI would energize the DCO engine. The IAB standard itself defines metadata for individual creative elements, and so it brings true on-the-fly creation closer.
But there is a bigger problem challenging brands that want to master creative personalization. As FlashTalking CEO John Nardone said: “There’s no methodology … to do the foundational concepting[.]”
Or in the form of a Cannes panel question: What are we talking about when we talk about programmatic branding, Sir Martin?
Rise Of The Automated Brand
A brand is the distance between a product and its magic. It is supposed to create desire and inspire choice, raising margins. Summoning the original meaning of the word, Al and Laura Ries described it as a way to “differentiate your product from all the other cattle on the range.”
Like everything else, branding is changing fast. Formulated in an era of mass media targets, it is struggling to redefine itself in a person-based world overrun by robot intermediaries. There is some evidence that the intrinsic value of a brand – measured by KPIs like stickiness and financial “goodwill” – is falling.
How are brands adapting? The best use a combination of programmatic targeting and dynamic creative to build more detailed audiences.
For example, EA Sports ran a “Madden NFL” campaign that messaged people based on their favorite team. Others, such as Google and Taylor Swift, are adopting a more generic approach, positioning themselves as edgeless “unbrands,” or blank spaces upon which consumers project what we will.
Beyond smarter remarketing and a Zelig-like psychology, brands need a new form of automated storytelling. Stories are the way people make sense of the world, including the world of products and services. In an industry of hypertargeting and -personalization, brand stories need to be as adaptable as targeting algorithms yet retain the brand’s soul.
Anything that can be expressed as a set of rules can be turned into an algorithm. Believe it or not, most stories can be outlined as a set of basic points. Those who have studied them tell us that, while there is no simple formula, there are a clear set of principles that make up good stories.
The Story Algorithm
In my idle youth, I watched 100 of the most successful movies of all time and diagrammed their plots. Similarities abounded. There were clear section breaks and well-ordered turning points. A hero’s journey, a team, a goal; an internal battle, obstacles, a betrayal; a fight to the death (real or spiritual), a resurrection. You could plot it on a graph.
Enterprising brands such as Georgia-Pacific are already talking about building campaigns using a “story framework” – and that’s the right idea. In the future, a brand won’t take a singular position in a broadly released campaign. Rather, it will exist as a codified story framework that is used to inform on-the-fly messaging decisions, based on targeting and contextual data, and powered by dynamic creative.
DCO becomes the place where the customer journey and the brand story intersect.
For example, a car brand might have a story framework coded around rising from scrappy Midwestern roots to overcome flashy foreign machines. A creative execution would know I’d been exposed to the “underdog” theme and would move me further along the narrative, emphasizing specific moves the car brand makes – special features, for example – to beat the enemy. Meanwhile, it would use dynamic elements such as colors and language that appeal to me.
The arc of programmatic advertising continues toward person-based identification and targeting. It’s time for traditional brands to realize the emerging power of dynamic creative to serve person-based sight, sound, motion – and stories.
Follow Martin Kihn (@martykihn), Gartner (@Gartner_inc) and AdExchanger (@adexchanger) on Twitter.
