One thing I’ve seen in the more than two decades that I’ve been in the digital advertising industry is that there’s no better return on investment than when you serve the right ad to the right consumer at the right moment.

But right now, the industry is trying to solve the return-on-ad-spend equation amid a unique set of circumstances. We’re beginning to adapt to a soon-to-be cookie-less world, privacy laws are evolving, and ad budgets seem to change with the weather.

What worked for marketers in the past is no longer effective today. Advertisers need to know that their ads aren’t being overserved and that the bids they’re making at auction are optimal.
 
That’s also why there’s an urgency among marketers to build first-party data strategies that leverage AI-focused tactics, optimizations, and platforms. Clean room providers have emerged as crucial facilitators, allowing advertisers to activate their first-party data and extract granular, AI-fueled insights while preserving user privacy.

So you know what AI promises to do. But how can you tell whether the AI you are using can keep those promises? It’s important to look beyond the bells and whistles at a few foundational differentiators.

SOLVING THE PARADOX OF CHOICE
 
The digital advertising universe has gotten incredibly complex. Based on our data, there are 25 million ad-supported websites, 7 million ad-supported mobile apps, and at least 50,000 CTV options. Advertisers can use these channels (and more) to target any one of more than 300,000 audience segments. And they can target those segments with more than two dozen ad formats. All told, there are nearly 98 trillion ways that an ad can reach consumers. But there’s only one way to be the most efficient and cost-effective at it.

In grade school, teachers always said we wouldn’t be allowed to use calculators in real life. But navigating the permutations of possibility in advertising simply isn’t possible for the human brain, especially when tasked with hitting specific KPIs within that campaign. Many advertisers face choice overload, and it can be paralyzing.

That’s where AI comes in. Using AI to optimize these decisions can help marketers get back to the work they love: Creating and experimenting with breakthrough ideas.
 
DON’T CODE, CHAT

Many of us have marveled at how chatbots have composed content marketing and bylines in seconds. But the true power of these chatbots is in their ability to transform how you interact with the tools, technology, and data you use.

When we use natural language as our primary interface, we can democratize programmatic advertising and lower the barrier to entry for small businesses, as well as for their advertising agencies that previously might not have been able to afford the data scientists and analytics experts required to play in this space. While there is increasing technical sophistication within the marketing function, marketers shouldn’t have to know how to write code to do their jobs.
 
DATA QUALITY

In the realm of AI, data quality is the foundation of success. The age-old saying “garbage in, garbage out” holds true in the AI realm as well. It can be challenging to make sense of large data sets, and maintaining and managing them is also a complex task.

But when machine learning models are trained with diverse, clean, and well-curated data sets, their performance and reliability are significantly enhanced. That’s why it’s critical to work with partners who are veterans in the industry and have a solid track record in collecting and managing first-party data.
 
With the deprecation of cookies coming, some believe advanced measurement will be diminished. However, the rise of clean room technology is showing this not to be the case and allowing advertisers to apply AI to large data sets while preserving privacy. 

By adopting a comprehensive and well-curated data approach, organizations can maximize the performance and reliability of their AI solutions, aligning with their specific marketing objectives.

CONTINUOUS OPTIMIZATION
 
In the old way of advertising, advertisers had a budget. They’d use a portion of that budget to create an advertising spot that was, at times, extremely expensive. Then, they’d spend the rest on distribution and evaluate the results. Sometimes, they’d learn their money was well spent. And other times, they’d blow through millions of dollars only to learn the campaign didn’t move the needle.

But what if you could do it differently? What if you could spend just a fraction of your ad budget and then evaluate and make improvements across both the ad’s creative content and its distribution? What if you could harness the power of AI to optimize bids so you could efficiently distribute content?

AI-powered data technologies and the emerging class of generative AI tools have taken center stage in the programmatic data ecosystem because they give marketers the ability to answer those questions. 
 
There is a new way of doing business. It’s powered by AI, and it’s a path that harnesses the power of automation to help marketers drive efficiency and growth for their brands.