Stop Guessing: Using AI to Sharpen Your Audience Targeting
It’s not that you are bad at ads, it isn’t your creative team that is failing. No matter how good the ad is, if it is aimed at the wrong people it will be ineffective and inconsistent.
The real reason your ads aren’t working
It’s not your creative, it’s not your offer, it’s not your “call to action.” Most importantly, it probably isn’t your budget either. Chasing that solution gets really expensive, really fast!
The main reason your marketing isn’t converting and your cost of acquisition is so high…the wrong people are engaging with it.
You’re targeting the wrong people—or most likely, and even worse, you are relying on outdated personas built on assumption and targeted based on gut feelings.
The modern digital landscape does not reward guesswork. It rewards precision, and the most powerful tool for getting precise is AI.
From Static Personas to Dynamic Models
The traditional marketing personas we have all been using for decades are similar to cardboard cut outs of people. They are flat, rigid, and worst of all generic.
“Stacey S, 35, soccer mom, married, homeowner, shops online”
“Jeremy F, 28, tech savvy, gym membership, college graduate”
These types are targeting personas don’t work for consistent results. Real people are way more complex than a simple persona and a binary yes or no from a list of interest, and your targeting has to reflect that complexity.
With LLMs you can simulate real buyer behaviors, generate nuanced customer journeys that adjust in real time based on actions, and stress test your messaging from thousands of different directions in minutes. Combine that with behavioral modeling and first-party data, and you have a living, evolving understanding of your actual audience.
Lookalike Audiences VS Predictive Targeting
I have built some massive campaigns in my career and have seen a ton of success with lookalike audiences. They were really great…10 years ago.
The way lookalikes work is by cloning past customers that have converted via your marketing, the problems arise when you have any changes at all in your product, you value proposition, your funnel, or basically anything else. You can end up chasing shadows and burning budgets very quickly.
Predictive Targeting, or predictive audiences generated by artificial intelligence flip that script. Instead of mirroring the past, it gives us the ability to forecast who is most likely to convert based on real time intent signals, evolving engagement data, and in the moment psychographics.
The platforms we are all using like Facebook and Google are dabbling in this technology, but layering in your own tools, ie., SparkToro for intent or Clearbit for enrichment, you gain targeting that adapts with your market, not months behind it.
Building adaptive targeting systems
Good marketers don’t “set it and forget it,” they build systems that actually evolve and learn.
Using the right AI tools you can:
Ingest performance data and update audience segments automatically
Run message simulations to see how different groups are most likely to react
Cluster intent signals to personalize campaigns even before launch
Instead of a one size fits all campaign and generic targeting, you can create a living ecosystem where every customized audience member gets what they need to hear when they are most ready to hear it.
Are you ready to see what AI-Powered Targeting actually looks like?
If you are still guessing who your audience is, you are basically burning cash. Let’s map your actual customer journey, identify your targeting blind spots, and set you up with an adaptive system designed to evolve with your market.
