There is no shortchanging the complexity of today’s media industry or the impact that the ever-expanding range of choice has on effective cross-media measurement. That complexity, however, doesn’t grant marketers any leeway when it comes to delivering on business objectives. In reality, increased complexity amplifies accountability.
The last few years saw the app giants take over the mobile app ecosystem, wielding brute strength to overwhelm the smaller publishers whose innovation and risk-taking historically drove things forward. But generative AI is leveling the playing field, giving small and midsize app developers the ability to create new apps and innovate on existing platforms dramatically faster with substantially fewer resources.
Having time to prepare for major changes is generally regarded as a good thing, both in life and the digital advertising industry. But when it comes to preparations for a privacy-first, post-cookie world, there’s been far too much talk about preparation and far too little action. This is hurting advertisers’ results today, not just in some theoretical future.
When you lose something important, you want to get it back. That’s the human instinct driving the conversation around signal loss. Marketers rightly feel an urgency to get back to a higher level of confidence targeting, attribution and measurement – particularly with broader economic pressures squeezing budgets.
If you scan the ad tech headlines, you’d assume artificial intelligence (AI) offers the solution to every challenge facing today’s brands and agencies. Even if marketers understand how the hype machine works, many are still willing to buy into the smoke and mirrors, especially when it comes to the power of AI to cure what ails them (e.g., the deprecation of third-party cookies and the loss of other previously relied-upon industry identifiers).
AI went from quirky novelty to dominant disruptor in a matter of months, taking over the headlines, as consumer-friendly and business-centric AI applications continue emerging in every sector. AI’s role in digital advertising is much more established, but rapid advances increasingly deliver unexpected and transformative capabilities for digital marketers.
Here’s how you succeed in ad tech: Analyze more data in more complex ways and turn that into differentiated products.
Ad tech players know it’s not that simple. Until recently, this path required obscure detours through data summarization and sprawling tech specialization.
Following the broader digital ad world, the TV market is rapidly moving to the impression-based model. Managed services for impression-based (including addressable) remain alive and well, but this year’s Upfronts demonstrated the most dynamic growth centers on the programmatic marketplace.
In truth, it doesn’t matter when – or if – third-party cookies go away for good.
Despite the industry’s collective hand-wringing, we’re in a moment rife with possibility. The advertising industry has never been better positioned to think differently about how to delight consumers with useful and relevant advertising while continuing to prioritize their trust. Of course, this requires making use of different, sometimes new technologies and tactics and embracing an open mind.
Will ChatGPT take all of our jobs or just make them easier?
I’m optimistic. Even early use cases for AI and tools like ChatGPT have shown to improve our efficiency and quality of life — and the ad tech world holds several early AI success stories. AI is improving performance, enabling us to finally scale up hyper-segmentation, real-time experimentation and one-to-one feedback loops. But, more importantly, AI is freeing up sharp human minds to be more strategic, curious and explore new ideas.
