Throughout the history of mass consumer advertising, creative teams drove the bus while the media team played a support role. The advent of programmatic digital flipped that model on its head. Today it is the media team that leads every digital marketing effort, while the creative team has been relegated to a supporting role.
Over this same period, the industry has created an ad tech ecosystem that exhibits a strong media bias. As media planners focus on who to buy and where to find them, investments in data management platforms, demand-side platforms, and buy-side technology have soared. The focus was — and continues to be — on optimizing buying strategies (by the media strategists) and maximizing operational efficiencies (for media operations).
In this media-centric programmatic world, creative is largely an afterthought, with account leads seemingly telling their teams: "Just make sure we have something to show them when the campaign launches." Creative teams are brought to the table late, often with incomplete information about the campaigns. Likewise, the creative management platforms — the ad servers — play a subservient role to the buying platforms.
Fortunately, this is all beginning to change thanks to a rapid evolution in consumer behavior. With the proliferation of smartphones and tablets, consumers have become chronically distracted multitaskers, creating a new and powerful demand for highly personalized, contextually relevant creative. And so it is that, 10 years into the programmatic advertising revolution, the pendulum is beginning to swing back to the middle where creative and media teams are equal collaborators from the outset of a campaign.
Building a Middle Ground
Personalization is having a tangible impact on roles and responsibilities within the entire advertising value chain. While the media team continues to identify the best "target audiences" to pursue on the buying platforms, the creative team is splitting them into smaller "message audiences," each defined by its own unique value proposition. An "SUV intender" target audience, for example, can be split into multiple message audiences: adventure seekers, young families, parents with teens, boomers nearing retirement. Each can be messaged in a distinct contextually relevant manner.
Brands today need to be able to own, grow, and redistribute the intelligence that they build around these creative message audiences with the same level of rigor and innovation that they do with their media target audiences.
Likewise, advertising technology must evolve and adapt to service an advertising ecosystem in which creative has regained its seat at the table.
For starters, advertisers must view creative management as separate and distinct from the media buying platforms. For personalization to be effective, an advertiser must be able to deliver a relevant and engaging creative piece at each touchpoint in the buying funnel, across channels, and, by extension, across buying platforms.
This is where the limits of a buyer-centric ad tech ecosystem come into stark relief. Imagine the work required to configure thousands of personalized creative messages — the versioning, decisioning logic, trafficking, tracking — within each individual buying platform on the media plan. Then try to coordinate the decisioning logic, sequencing, and frequency exposure limits across platforms.
The ad tech platforms must also enable advertisers and their agency partners to unleash efficiencies across the creative team. In today's media-centric world, there is a belief — a myth, as it turns out — that efficiencies are operational in nature (i.e., how does one implement the campaigns with the minimal number of people?). In most advertising initiatives, however, there are significantly more creative resources at work than media resources. When viewed through this broader lens, one realizes that there are much greater organizational efficiencies to be had, and the better question to ask oneself is how can technology enhance the productivity of the creative team, which must activate more and more personalized creative across the entire customer journey?
Finally, the personalization paradigm imposes new requirements around data collection and analytics. Advertisers require meaningful creative performance metrics so they can understand which messages are resonating and which are falling flat. Reports from buy-side platforms cannot provide this level of insight; they can only tell marketers how certain placements and audiences perform within their platforms.
Generating these new creative performance metrics requires integration of disparate data sets from across all buying platforms, identity resolution using cookie-less tracking and cross-device identity graphs, and advanced creative analytics capabilities including fractional attribution.
As personalization strategies take hold, these gaps in the media-centric ad tech ecosystem will become more apparent. This will be an opportunity for the industry to reevaluate the role of the ad server. When uncoupled from the buying platforms, the ad server can serve as the platform for creative management, activation, and analytics.
In the age of personalization, the ad server is reemerging as a mission-critical middleware platform for advertisers to execute their data-driven creative strategies.
What a Data-Driven Strategy Means for Advertisers
Implementing a personalization initiative using data-driven creative is fundamentally a change management exercise: It will require marketers to adopt new paradigms, build new capabilities, and reevaluate their technology stack.
A brand's plan of action is dependent on where it is within the personalization journey:
- Crawl stage. A brand is just getting started on its personalization initiative by conducting a proof of concept (POC). During this phase, the brand team is learning how to execute data-driven creative and understand its technology partners' capabilities. Analytics is an often-overlooked part of the POC, so brands need to make sure partners provide sample raw-data logs, identity resolution results, and creative analytics insights.
- Walk stage. The brand has run a successful POC and is now looking to scale its personalization capabilities. This is the opportunity for marketers to battle-test the full complement of their data-driven creative strategies, workflow processes, and analytics capabilities. The marketing team may also decide to evaluate additional technology partners. During this stage, marketers should actively search for limitations imposed by technology, data, and analytics partners; these will ultimately place hard limits on any upside opportunity.
- Run stage. The brand is now ready to develop and execute its personalization roadmap. Marketers should start by assessing the gaps (people, process, data and analytics, and technology) between their current state and future vision, then build out plans to close the gaps, leveraging what they have learned across the first two phases. All facets are important, but technology, data, and analytics are the limiting factors. Brands can have the best people and processes, but relying on buy-side platforms for creative management, activation, and measurement will severely limit their ability to execute against a personalization strategy.
By John Mruz is the SVP of strategy at Flashtalking.