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Leveraging AI to Hyper-Target Your Programmatic Advertising

Programmatic advertising can be confusing. Ad tech platforms are popping up all over the place with their jargon-filled offerings and next-best-thing attitudes, but few are actually demystifying the process for anyone. 

At the end of the day, all marketers want is to maximize their ROAS by placing the right content in front of the right audience in a seamless way. They want to fit into their customers lives, not interrupt it.

This is all, of course, easier said than done.

In a world that’s gone data- and analytics-crazy, how can you simplify the targeting process and get ahead of your competition? 

What if you could harness the power of AI to do just that? 


How AI Applies to Advertising

Artificial intelligence in advertising is nothing new. But when used in new and creative ways, its data mining capabilities can help marketers achieve more awareness, higher conversions, better engagements, or whatever outcome their business desires. AI’s ability to crunch data and make real-time decisions at the core of it all. 

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If you wanted to target, say, consumers that were engaging with content relevant to you brand (e.g. using related search keywords or reading your competition’s product reviews), you could use AI to pool this data and create a custom segment.

You could then target that audience with programmatic ads in real time. Thus, you have replaced the spray-and-pray model with something much more effective. 

Using these techniques and technologies, we have seen click-through rates up to 4x higher than industry averages, along with significant reductions in costs per engagement (CPEs). That’s a huge success.

By creating these custom audiences, you can be sure that you're feeding ads to relevant people—people who recently showed a high intent to engage with a brand such as yours. The result is higher engagement and lower conversion costs.


How to Get Started

In order for your programmatic targeting to be effective, there is some manual work that needs to happen up front.

First, a research process must take place where your brand’s audience is broken down and the audience data pool is created. This audience is specific to your brand, and the information is used to feed the AI and get it going in the right direction. 

Audience-Buying

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What’s more exciting, though, is that as time passes, the technology gets smarter. Using machine learning, the AI can index thousands of data points to find unique and relevant audiences for your brand—audiences that will be directly in line with the audience data pool that was initially created. 

This data pool will continue to grow and become even more defined over time. If someone enters the pool but then their search behavior changes to a point where they are no longer relevant, they will be kicked out. All of this happens behind the scenes, and only those that stay in the data pool are served your ads. 


Tying It All Together

Now, we realize we're simplifying a very complex process, but that’s the point of this article, isn’t it? To make AI for marketing more approachable by demystifying it.

AI is not a scary thing. It’s an amazing thing, and the brands that embrace sooner than later will have the upper hand.

Advertisements come in all shapes and sizes. They can be in-feed, in-ad, display, video pre-roll—you name it. All that matters is that the person viewing them sees them as relevant. This is what drives acquisition and revenue. 

As your campaign runs, AI can help with optimization as well, making suggestions on who to target, which creative is performing best, and the best time to serve your ads. 

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