Advertising-technology vendors and agencies are part of the same ecosystem and often share brand clients. But each has developed an animosity toward the other. They straddle opposite sides of a creativity-automation divide, with brands caught in the middle.
Big data allows previously unimaginable levels of precision ad targeting, but it has opened divides among ad-tech vendors, agencies and brands. Ironically, though, it's in the technology that we can also find bridges across.
Ad-tech vendors are at home with big data; it fits their numbers-driven world. But it has darkened the canvas for ad agencies, which take pride in their creative side. It began around 2007 with the rise of "dynamic creative" providers like Tumri, Teracent and Dapper. The ads employed machine-driven templates to boost performance, but the machine also determined the creative.
CMOs were glad to see a lift in clicks and conversions, but left hanging about why it was working. Ad targeting's automation typically doesn't deliver the kind of insights that could help fuel performance across channels.
Next came real-time bidding providers, who enabled programmatic media buying. Ad performance potential was boosted, but agencies were pushed farther away from the data-centric process, and CMOs had even less insight into what was driving results.
Some brands, feeling the squeeze, have cut the agency out of the picture or reduced its role by creating in-house digital units. Kellogg, for example, has stirred things up by working directly with vendors to handle programmatic buying, while using its agency in more of a consultative role.
While most brands aren't yet taking such a drastic step, it's going to get worse down the road if all sides don't find ways to work together, as big data becomes even a larger part of the picture.
The solution? Use technology to create greater data transparency. Companies like Flite, InMobi and Adacado are wedding programmatic buying and dynamic ad serving with more of a creative element and an open data environment that all parties can access. Agencies become more of a player in the process as the ad-tech companies provide data that tell them what types of creative are working and in what situations, and brands can apply these insights across channels. This flips the question from "Are humans or machines driving ad performance?" to "How can we apply machine learning to the creative process and achieve better results?"
In this new model, the ad-tech company, agency and CMO share the same dashboard view of real-time ad performance. The agency gleans from the data the most effective use of creative, the vendor wields the data to build better, more effective technology and the CMO gains insights to apply across multiple channels.
The result is greater cooperation among the parties. So what's preventing this more harmonious scenario from playing out? Nothing, as long as more ad-tech providers are willing to lift the veil and create a more open data environment to the benefit of all stakeholders.
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