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- 🧠 Hidden Meta targeting red flags that are draining your ad spend
🧠 Hidden Meta targeting red flags that are draining your ad spend
These targeting red flags are keeping you from profitable scaling. Avoid them.
Kody Nordquist
March 08, 2025
Welcome back to the 75th edition of Nord Media
Before we get started, is there anything specific you want to learn about? Let me know, as always, I appreciate all of you who reply each week and share feedback with me.
Lookalike audiences used to be money. Upload a customer list, let Meta work its magic, and boom…. Conversions at scale.
Not anymore.
If you’re still relying on traditional LALs in 2025, you’re probably watching your CPAs creep up while your best audiences shrink. Privacy changes, data restrictions, and Meta’s evolving ad ecosystem have made them way less effective.
It’s not that lookalikes are weaker. Meta’s entire targeting system has shifted. The platform isn’t relying on cookie-based signals the way it used to. It’s leaning harder into real-time behavior, AI-driven audience models, and in-platform engagement data to figure out who is most likely to convert.
The old way of targeting like static lists, pre-defined segments, and recycled customer data is slowly dying.
Fortunately, there’s a better way to target.
Today, we’re breaking down the top Meta targeting red flags to avoid and how to start using smarter alternatives instead.
Let’s dive in.
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🚩 Red Flag #1: Still Relying on Lookalike Audiences to Scale
What to Do Instead: Behavior-Based Targeting & Broad Audiences
Lookalike audiences used to work because Meta had strong, reliable data signals. Now with signal loss, LALs are pulling from weaker data pools, leading to higher CPAs and worse match quality.
Instead of relying on historical lists, start feeding Meta real-time behavior signals.
Broad targeting with high-quality creative gives Meta room to find the best buyers.
Post-click engagement signals (like video views, add-to-carts, and checkout initiations) help the algorithm optimize towards real intent.
Custom events and pixel-based actions give Meta fresher, better data than a static list ever could.
Meta’s AI has evolved. It's time your targeting strategy does too.
🚩 Red Flag #2: Thinking First-Party Data Alone Will Save You
What to Do Instead: Blend First-Party Data with In-Platform Signals
Feeding Meta a customer list is a great start, but it’s not enough.
Meta prioritizes in-platform behavior meaning if you’re only relying on past purchasers or email lists, you’re missing a big piece of the puzzle.
The better approach: Layer first-party data with on-platform engagement signals:
Use video watchers, post engagers, and high-intent site visitors in your custom audiences.
Retarget users who have interacted with specific product pages instead of just past buyers.
Leverage Advantage+ Audiences, which let Meta’s AI find high-converting users based on real-time actions.
First-party data is powerful, but it’s even more powerful when combined with Meta’s in-platform insights.
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🚩 Red Flag #3: Relying on Interest Targeting Like It’s 2019
What to Do Instead: Use AI-Powered Predictive Audiences
Manually picking interests isn’t the move anymore. Meta’s predictive modeling is already better than manual targeting.
Instead of trying to outguess the algorithm:
Test Advantage+ Audiences, which automatically optimize based on past campaign performance.
Let AI-driven models refine your targeting dynamically instead of locking yourself into outdated interests.
Feed Meta strong creative assets and engagement signals, and let the system find the right buyers.
Meta’s machine learning is smarter than human guesswork. Brands leaning into AI-powered audience modeling are seeing higher ROAS and lower CPAs.
🚩 Red Flag #4: Optimizing for Purchases Too Soon
What to Do Instead: Use Multi-Step Conversion Events
Running prospecting ads straight to purchase is an easy way to burn through budget.
The better approach: Optimize for high-intent, mid-funnel actions first.
Optimize for:
Add-to-cart or checkout initiations to train the algorithm on high-intent users
Lead capture for email/SMS retargeting before pushing for the sale
Content engagement events to build retargeting pools for lower-cost conversions
Instead of forcing cold traffic to convert immediately, warm them up first, then scale purchases profitably.
Closing Thoughts
If your Meta strategy still looks the same as it did two years ago, it’s probably not working as well as it used to.
Lookalike audiences are dying. Interest targeting is fading. And first-party data alone won’t save you.
In 2025 you should be shifting towards:
Behavior-based audience building over static lists
AI-powered targeting instead of outdated manual interest selections
Engagement-driven optimization to feed Meta better signals
Meta isn’t getting worse. It’s just changing. The sooner you adapt, the faster you’ll scale.
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