Data-Driven Thinking

After attending the Federal Trade Commission’s virtual roundtable about the impact of generative AI on creative fields last Wednesday, all I can wonder when I see an AI-generated creation is whose work it’s based on.

Marketing analytics and ad ops teams are overwhelmed with data, which is compounded by the accelerated pace of generative AI-produced content.

The industry is too focused on quantity over quality. Unfortunately, it seems there are many people still chasing scale due to a lack of understanding. 

After 12 years of working in – or adjacent to – the ad tech industry, I am coming to terms with the simple answer to many depressing questions.

Digital media and television have been playing by different sets of rules due to the nature of ad delivery and tracking. But these worlds are slowly colliding.

While clean rooms do offer significant value in today’s privacy-first world of data, they are not the be-all and end-all for brands seeking controlled and reliable means of data collaboration.

Arielle Garcia, UM’s former chief privacy and responsibility officer, explains why she decided to leave the large agency holding company model – a model that is rife with competing interests and conflicting loyalties, shackled to the industry status quo by “dysfunctional interdependencies.”

To enable startups to seamlessly integrate with DSPs, ad servers, ad exchanges, measurement platforms and SSPs, a centralized ecosystem and industrywide support are urgently needed.

The proposal to transition ads.txt into ads.json comes with some major problems, and its benefits can be largely achieved in a far simpler way – by reformatting existing ads.txt files.

Of course, the misappropriation of a publisher’s audience data would be unethical. But this is not what contextual providers do.