Why Creatives Don’t Spend on Meta Ads
Ask any ad buyer or creative strategist what frustrates them most inside Meta Ads Manager, and you’ll often hear the same thing: A great creative that just won’t spend.
The ad is perfect. The messaging is sharp. The visuals feel dynamic and engaging. It should win by all accounts of what a “good” creative is… but instead, it sits at $6 of spend and flatlines.
At its core, a creative that doesn’t spend is an algorithmic decision, not necessarily a creative problem. Meta’s algorithm is AI trained on trillions of human actions to make a prediction on whether your ad is or isn’t worth showing to its users endless scrolling on Meta’s platforms. It’s Meta’s way of protecting its ecosystem from wasting impressions and money. But as any experienced buyer knows, “the algorithm knows best” is a myth that only holds true… until it doesn’t… and it needs some human ad buyer redirection.
Understanding why a creative doesn’t spend requires seeing both masters a great ad must serve: the human and the machine.
This blog post is nerdy, but the information we’re discussing (this topic included) is happening DAILY in the Foxwell Founders membership. If you’re interested in this topic, you’re going to LOVE the collaboration and community we have with over 550 members across the world, all expert marketers in their fields of Meta ads, creative strategy, Google ads, Email, CRO, brand ownership, agency operations and more.
The two masters every ad serves
The best ads speak to both the consumer and the algorithm. Humans are the viewers who make emotional, impulsive decisions, and robots are the algorithm interpreting billions of data points per second. They meet together to provide the ad experience we all see when doomscrolling our feeds.
Humans aren’t predictable. They scroll, stop, and convert for reasons that can’t always be modeled. The algorithm, on the other hand, tries to predict that behavior before it ever happens. When Meta’s system decides an ad shouldn’t spend, it’s because the model believes it won’t convert, and therefore, it won’t keep users engaged on the app.
The irony is that Meta’s AI sometimes protects itself from risk so aggressively that it prevents you from learning. That’s why seasoned buyers often force spend on a creative to give it a fighting chance. Because in the early stages (say, $5–$10 in spend), there’s simply no way for an algorithm (no matter how advanced) to know how a new ad will perform.
Humans aren’t robots. And neither are the buyers testing on their behalf.
Why the algorithm says “No”
When a creative doesn’t spend, Meta is essentially saying: “We don’t believe this will lead to the desired outcome.”
That decision is based on early user behavior signals (scroll velocity, watch time, interaction rates, and engagement decay). If users aren’t stopping, the algorithm assumes they won’t care later either.
This is Meta’s self-preservation loop in action. The platform’s business model depends on keeping users scrolling. Ads that interrupt that flow, whether through weak hooks, poor engagement, or slow pacing, hurt user experience and, by extension, Meta’s revenue. So the system deprioritizes them.
The takeaway here is that non-spending creatives are often collateral damage in Meta’s quest for retention.
The actual cost of not letting ads spend
Every piece of creative that fails to spend represents a missed opportunity for learning. Brands and agencies are pouring more resources than ever into creative production, yet, too often, these assets never see real distribution. They many times die out in the testing phase, not because they failed, but because they were never given enough data to prove anything.
That’s why a smart benchmark for testing spend may be something like roughly 3× the cost of production or 3× your CPA, whichever is higher. If a UGC ad cost $300 to produce, it (in a perfect world) deserves at least $900 of test budget before being judged. Anything less is a string of algorithmic code’s guesswork at best masquerading as optimization.
You can’t learn from no data, and you can’t get data without ad spend. And when you don’t learn, you repeat the same creative mistakes over and over again.
Creative testing is about learnings
Every creative test should generate insights, not just winners.
The point of testing isn’t to find the one and only breakout ad; it’s to build a better understanding of what your audience and algorithm respond to. Even a “failed” ad contributes valuable data—if you let it run long enough to produce a pattern.
That’s why creative testing should be treated as a research & development function, not just a launch pad for scaling campaigns. The more data you collect about what doesn’t spend (and why), the sharper your future creative decisions become.
If your creative stalls, try to not panic. Don’t just tweak a subtitle, add an emoji, or change the background color. The algorithm won’t see those as meaningful differences anymore. In 2020-2021, yes, a single frame change would be seen algorithmically as a net-new creative. However, post-Andromeda, the algorithm is smarter and more astute in its knowledge and findings.
Instead, change the creative so much that Meta sees it as a new ad entirely. That’s the only way to break through the system’s learned bias.
If you’re a UGC creator asking this question on why your creatives aren’t getting spend, or a creative strategist sourcing creators and briefing creatives, we have to introduce you to The Hive Haus. It’s the Foxwell Founders’ sister community that’s an all-access membership to paid brand opportunities, creative strategy education, and a collaborative creator community to share ideas, insights, and opportunities to learn more. We hope to see you there!
Here’s where to start:
1. Change the hook drastically
The first three seconds decide everything. If users aren’t stopping, the rest of your story kind of doesn’t matter because no one’s watching it. Try removing your hook entirely and jump straight into the core message. Or start mid-sentence. Or flip the perspective. Or have the same script but a completely different visual. Try a creator mashup as the hook. Say the brand’s name 8 times from different creators. Do something that screams, “whoa, this is totally different.”
A new hook reframes the ad in Meta’s eyes and resets engagement signals.
2. Change the visual format
Switch from a talking-head to a split-screen. Try motion overlays. Try a talking head on a green screen/background removed with B-roll behind them. Reverse the pacing. The goal isn’t subtle variation, but instead radical differentiation. This is all Meta reps are talking about post-Andromeda. The algorithm must instantly recognize that this is not the same creative.
3. Keep the message & sentiment, but rebuild the delivery
Emotion sells. Concepts work. Angles can be longtime winners. It’s the delivery that needs to be changed up with every new ad creative. For example, keep the same voiceover, but pair it with entirely new footage. Or what about inverting the structure with solution first, then problem? Meta favors novelty, and novelty lives in delivery as much as in concept.
4. Re-examine soft metrics
Look beyond CTR or ROAS. Track where users stop watching… and exactly what happened in the video right before they dropped off. Key custom metrics include:
3-second view rate (thumb-stop ratio)
15-second hold rate
25%, 50%, 75%, and 95% completion rates
If most users are dropping off before 5 seconds, your creative isn’t being rejected for its offer (because no one even made it to the offer, and they may not have made it to the intro of the product at all). If they drop off nearly immediately, the ad creative is being rejected for its pacing.
Why problem-solution ads fail fast
“Have you ever experienced this problem?” is one of the most overused hooks in UGC today. This worked when it was new and different, but that trend is 3 years past its peak at best. Another overused hook: “If you _____, stop scrolling. If you ____, keep going, this isn’t for you.” We could keep going with overused hook trends for hours.
Back to the original issue of traditional problem/solution creatives, leading with a problem can create immediate relatability, absolutely. But if you linger on it too long, users lose patience. They already know they have the problem. They want to know if you’re going to fix it. Get to the point!
Long problem setups are one reason why these ads don’t spend. They create early disengagement, which signals to Meta that users are scrolling away. Once that happens, your ad falls into the platform’s “non-delivery” graveyard—often permanently.
Get to the point faster. Curiosity is good. Friction is fatal.
Meta’s incentives aren’t yours
Meta doesn’t care if your ad performs. It cares if users stay on its platform.
Every design choice from infinite scroll to ad sequencing serves that goal. That’s why the platform punishes content that leads to app exits or disengagement. The more someone scrolls, the more ads they see, and the more Meta earns.
If your ad interrupts that flow, Meta’s machine deprioritizes it. Period. The best-performing creatives feel native to the feed, whether that’s literally feeling native in a low-fi manner, or native to just not looking like a TV commercial. The best ads entertain or educate first, sell second, and reward attention throughout. They make people want to keep scrolling, not close the app.
So when a creative doesn’t spend, it’s not personal or even accurate necessarily, it’s just Meta trying to manage its ecosystem and keep delivering content that people want to see and engage with. Social media feeds are all about “edutainment,” which is educating the viewer while also entertaining them. We all get a dopamine hit every time we scroll to the next Instagram Reel or TikTok video. We want to see what’s next and we want to be entertained. Your ad creatives should do that, too.
Turning “non-spending” into signal
One of the most valuable exercises a creative strategist can run is a spend analysis. Take every ad in your account that spent less than $50 and compare them against those that spent $2,000 or more.
Lay them side by side and ask:
What themes, visuals, or hooks are shared among the high-spenders?
Which patterns repeat among the non-spenders?
Are there consistent traits—like pacing, text overlays, or framing—that correlate with delivery?
Sometimes the differences are obvious (bad hooks, weak thumbnails). Sometimes they’re subtle. Either way, those comparisons turn “failure” into feedback. Ultimately, the algorithm doesn’t decide whether a creative is good or not. It decides whether it fits the system’s understanding of user engagement. Your job as a creative is to learn from what it rejects.
Strategic Takeaways: Aligning creatives with Meta’s delivery logic
If you want your creatives to spend, you have to design them for both people and the platform. That means:
Budget for real learning. Try to spend at least 3× your CPA (or 3x the amount you paid for the creative to be made) before calling it quits. This isn’t always doable, but aim for this. Also keep in mind length of time to test. Ideally your creative would get one or both of these things above AND also run for at least 7 days to get adequate data for different days of the week as well.
Front-load the story. Hook users within 1–3 seconds. Every scroll past that point is algorithmic oxygen.
Iterate aggressively. Change creatives so drastically that Meta sees them as new assets.
Measure more than ROAS. Analyze thumbstop rate, hold rates, and drop-offs to understand why spend stalled.
Think like the platform. Meta rewards engagement loops, not just conversions. Create ads that feel like content worth staying for, content worth talking about, commenting on, sending to a friend, reading the comments, etc. Make the viewer feel something when watching your ad.
When a creative doesn’t spend, it’s not because it failed. It’s because it didn’t fit the machine’s model of what “good” looks like. The smartest ad buyers treat that as a starting point, not a verdict.
The creative’s job is to bridge the gap between human curiosity and algorithmic prediction. And the only way to do that is to spend enough, learn enough, and iterate enough to prove both masters wrong.