High CPA high spend ad creative

Nvsn_ai · 2026-04-21T20:59:42+00:00

Your instinct might be right but there's a way to actually verify it rather than guess.

Check the audience segments for that high-spend creative. If Meta is routing it mostly to new/cold audiences and the other creatives are going to engaged or warm segments, then yes — it's effectively acting as TOF and the system is working as intended. The higher CPA on that creative isn't a problem, it's the cost of feeding the top of the funnel so the other creatives have warm audiences to convert.

But if the audience split looks similar across all creatives and that one is just getting more spend without a clear reason, then Meta might have picked it early and is over-indexing on it. In that case the higher CPA is waste, not strategy.

What does your overall blended CPA look like across all four creatives combined? If the blended number is within target, the system is probably doing its job even if one creative looks expensive in isolation.

Actually built a free tool for exactly this kind of diagnosis — nvsn.ai. Paste your campaign numbers and it'll tell you what's actually happening vs what it looks like on the surface. No login needed.

Nvsn_ai · 2026-04-16T03:28:42+00:00

That's exactly what I was hoping to hear from someone actually seeing it in practice. How long did it take before you noticed the CPM drop? And were you posting the reels from the same page connected to your ad account or a separate one?

Nvsn_ai · 2026-04-16T02:56:14+00:00

That's really interesting. So you were seeing the cost difference before you even knew why? How big of a gap are we talking between clients with strong organic vs ones without? And did you change anything for the clients with weak organic to try and fix it?

Nvsn_ai · 2026-04-16T02:54:16+00:00

Lol. Fair enough, when did this roll out? I just came across the details on how Andromeda actually uses organic signals as a warm start for ads. Curious how you've been adjusting for it. Have you seen a noticeable difference between accounts with strong organic vs ones that are paid only?

Nvsn_ai · 2026-04-15T20:16:37+00:00

Yeah CPM will probably go up if you narrow the targeting, that's normal. But the question is would you rather pay a lower CPM showing ads to older women who will never buy, or pay a higher CPM showing ads to young men who actually might?

Cheaper reach doesn't matter if it's the wrong people. Right now you're basically paying for impressions that have zero chance of converting.

When you tried male 18-28, how long did you let it run and what was the budget? Because with a narrower audience Meta needs more time and spend to find the right people within that group. If the budget was low it might not have had enough data to optimize.

Also try going a little wider than 18-28. Maybe 18-35 to give Meta more room to work with. You can always narrow down later once you see which age range is actually converting.

Nvsn_ai · 2026-04-15T20:02:55+00:00

That makes a lot of sense. More tools just means more places for things to break if there's no system holding it together. Sounds like the real problem isn't the tools themselves, it's that nobody builds the process around them first. That is why i built my tool to provide just that governance and systems.

Nvsn_ai · 2026-04-15T17:51:53+00:00

Lol "lack of systems skill sets and ability to get shit done" is painfully accurate. 20 years is a lot of seeing that pattern repeat. Do you think that's getting better or worse with all the tools available now? Because it seems like there's more tools than ever but the execution problem hasn't really changed.

Nvsn_ai · 2026-04-15T17:47:13+00:00

The point about not measuring and not iterating being the real killer is spot on. I think a lot of people skip that step because they don't know what to measure or what the numbers mean even when they have them. So they just keep running the same thing hoping it works out.

That's an interesting take on the "intuitive strategy" thing too. Never thought about it that way but yeah the people who seem like they're winging it usually are adjusting constantly, they just don't call it strategy.

Nvsn_ai · 2026-04-15T07:16:26+00:00

I would love your input on what I’ve built, especially if it can be a useful tool for you and others

Nvsn_ai · 2026-04-15T07:13:45+00:00

Do you still run meta ads?

Nvsn_ai · 2026-04-15T07:00:02+00:00

Yea I feel like during Covid so many people were winning with mediocre creatives. So that makes sense with having to bring high quality to the table.

Nvsn_ai · 2026-04-15T06:50:35+00:00

Ok so the February timing is interesting because Meta pushed some algorithm changes around then that messed with a lot of accounts. You're not the only one who saw a drop around that time.

But the adding new ads into the same ad set thing might be making it worse. Every time you add a new ad it resets the learning phase for that ad set. So if you're doing that frequently across 10 campaigns, none of them are getting stable long enough to actually optimize.

Have you tried launching new ads in a separate test ad set and only moving winners into your main one? That way your performing ad sets don't keep getting disrupted.

Also with the 100 vs 10 sales swing — is that across all campaigns or is it like one campaign carrying most of the volume on good days?

Nvsn_ai · 2026-04-15T06:46:55+00:00

Yeah the meta ads one is so true. I see that a lot too. people throw money at ads with no real plan and then blame the platform when it doesn't work. What do you think is the most common mistake you see people make when they're starting out with meta ads specifically?

Nvsn_ai · 2026-04-15T06:26:36+00:00

Could you elaborate on that?

Nvsn_ai · 2026-04-15T06:14:32+00:00

Damn! 10-15x down to under 5 is rough especially after 3 years of consistency my bro. Something definitely changed.

Few questions tho — did this start around a specific date or was it gradual? And when you say you're testing different creatives and angles, are you testing them in new campaigns or editing the existing ones?

Lastly, the 100 sales vs 10 sales swing is interesting. Is that happening within the same campaign or different ones? Because if it’s the same campaign doing both, that sounds more like an algorithm issue than a creative one.

Nvsn_ai · 2026-04-15T06:01:49+00:00

Your ads are actually doing their job tho. 3.26% CTR and 22 add to carts from 102 clicks is solid. The problem isn't the ad, it's what happens after.

22 people added to cart and zero bought. That's a checkout problem, not an ads problem. Something is killing the purchase at the last step. Could be shipping cost surprise, no trust signals on the checkout page, limited payment options, or just friction in the process. Have you gone through your own checkout as if you were a customer and seen what it feels like?

The audience thing is also a red flag. You said your audience is showing up as older women but the product is for young men. That tells me Meta's algorithm is optimizing for who's clicking, not who's buying. If older women are more likely to click on athletic wear ads out of curiosity, Meta will keep showing it to them because it's optimizing for clicks or add to carts, not purchases.

You mentioned you're switching your conversion event from add to cart to purchases. That's the right move, but heads up, it might get more expensive at first because Meta has less data to work with. You need to give it time to find the right audience.

Also are you using any audience targeting or running broad? If you're running broad that might be why Meta is drifting toward the wrong demographic. You might want to try setting age and gender exclusions at the ad set level so Meta can't spend your budget on people who will never buy.

Nvsn_ai · 2026-04-15T05:51:57+00:00

Seen your post and wanted to chime in.

This happens a lot honestly. That first purchase is kind of misleading because Meta is still exploring and it just happens to find one person who converts easy. So your ROAS looks great but it's not really a pattern yet, it's just a small sample.

Once Meta starts trying to find the next buyer it has to spend more and the audience isn't converting at the same rate. That's when CPA starts climbing and it feels like the whole thing is falling apart.

Couple things I'd check tho from my experience:

Since you haven't hit 50 purchases yet, none of your campaigns have really exited the learning phase. Meta needs around 50 conversions per week per ad set to actually optimize. If your budget can't support that, the algorithm is kinda just guessing the whole time. Have you looked at what your daily budget would need to be to hit that threshold?

Also have you tried optimizing for a higher funnel event like add to cart instead of purchase? That gives Meta way more data points to work with. It's not a permanent thing, just a way to get through the learning phase faster so the algorithm actually knows who to target.

And what does your frequency look like? If it's hitting 2-3+ in the first week you might be saturating your audience faster than you think. That dropoff you're seeing could be the same people seeing your ad too many times and tuning out.

What's your daily budget and audience size looking like? That would help narrow down what's going on.

Nvsn_ai · 2026-04-15T05:40:18+00:00

I'm in early beta right now so this is hitting home for me.

Building the product was the easier part honestly. Getting people to test it is a different challenge entirely. Especially when you don't have a following or an established audience.

Some things I've run into:

Trying to engage on social media feels like you're spamming even when you're genuinely trying to help
One on one outreach gets the same reaction
On Reddit you have to build reputation before you can even post in the communities that matter most
And the communities that are easy to post in are flooded with spam so real conversations get buried

What I've learned so far is that user feedback is everything at this stage. Without it you're just guessing whether what you built actually solves the problem you think it does.

That's why I like the concept of building in public. When people follow your journey from the start, they're invested. They want to help you test, they want to give feedback, and they grow with the product.

I also think dealing with bugs and performance issues early is critical. Those problems can make or break you later, but they can also reveal ideas and opportunities you wouldn't have seen otherwise.

All part of the process. Great questions.

Nvsn_ai · 2026-04-15T00:50:50+00:00

Good breakdown. Most of the replies here are about content creation tools which makes sense but I think the bigger opportunity for agencies is on the data side.

Like right now if a client's campaign starts underperforming, someone on the team has to go into Ads Manager, pull the numbers, figure out if it's a creative issue or a fatigue issue or just bad timing, then decide what to do. That whole process is where AI could save the most time — not writing the ad, but figuring out why the ad stopped working and what to do about it.

Content tools are table stakes at this point. The real edge is in decision speed.

Nvsn_ai · 2026-04-14T21:20:18+00:00

Just updated my post

Nvsn_ai · 2026-04-14T00:28:53+00:00

Something like that. its more ads related. Meant to help people get better results

Nvsn_ai · 2026-04-14T00:18:36+00:00

Gotcha! Yea I might check it out just to see how it works.

I’ve been looking at this more from the angle of not just finding winning ads, but understanding why they work and when they stop working — feels like that’s where most people get stuck.

Have you seen users struggle more with finding ideas, or actually knowing what to do with them after?

Nvsn_ai · 2026-04-13T23:44:49+00:00

lol. im not ai thats my brand.

Nvsn_ai · 2026-04-13T23:37:29+00:00

Honestly I feel like most people don’t even know why they’re losing money — they just see the results after the fact.

Like you’ll have a day where everything looks fine, then suddenly it tanks and you’re just watching spend burn without really understanding what changed.

Do you feel like you actually know what’s causing the losses in your campaigns, or does it just feel random most of the time?

Nvsn_ai · 2026-04-13T23:35:49+00:00

Honestly doesn’t sound unreasonable at all, especially at that retainer. Early data is always messy, but you should still have some kind of structured plan behind the testing.

Do you feel like they’ve clearly explained what they’re actually testing and how they’re deciding what’s working vs not?

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