u/Frontend_Lead

Standard setup: Test campaign with 1 creative per ad set to validate. Move winners to the Scale campaign after 7-10 days. The handoff is where it breaks.

Three approaches I've tried all have the same issue:

1. Multiple winners in one ad set

Scale Campaign (ABO)
└── Ad Set (one budget)
    ├── Winner A   ← 80% of spend (had early lead)
    ├── Winner B   ← 12% of spend
    └── Winner C   ← <5% (starved despite better ROAS)

Meta picks an early favorite (usually the one with the most history) and starves the rest.

2. One winner per ad set

Scale Campaign (ABO)
├── Ad Set A (own budget)  ← Winner A
├── Ad Set B (own budget)  ← Winner B
├── Ad Set C (own budget)  ← Winner C
├── Ad Set D (own budget)  ← Winner D
└── Ad Set E (own budget)  ← Winner E

Solves starvation, but now I'm managing way more ad sets, each running its own learning phase. Lose Meta's intra-day budget shifting.

3. Just bump budgets in Test

Test Campaign (ABO)
├── Ad Set 1 ($150/day) ← Winner, scaled up
├── Ad Set 2 ($150/day) ← Winner, scaled up
├── Ad Set 3 ($40/day)  ← Still testing
├── Ad Set 4 ($40/day)  ← Still testing
└── Ad Set 5 ($40/day)  ← Still testing

Cleaner, but pollutes my testing structure, and scale exclusions don't apply.

The trade-off seems to be: consolidate and trust Meta (accept starvation) vs. isolate and enforce a fair budget (lose algorithmic optimization).

Questions:

1. How do you actually handle this in practice?
2. Anyone using automated rules to cap dominant ad spend share? Does it work or just create pause/unpause cycles?
3. Does the 20-creatives-per-ad-set Andromeda approach actually work, or does it only work at high spend?

Not looking for "trust the algorithm", looking for how you've structurally solved this. I have tried "trusting algo and following meta rep advice", which just destroyed my roas.

How do you stop Meta from just spending almost the entire budget on one ad within an ad set?

It feels like the platform quickly picks a “winner” before the other creatives even get enough spend/impressions to properly prove themselves.

Running fully isolated creative tests for every ad also doesn’t seem sustainable because of variance. A creative might underperform one week, then suddenly work later, or fatigue changes everything over time.

How are experienced advertisers handling this at scale? Are you separating testing from scaling campaigns entirely, using ABO over CBO, minimum spend rules, or something else?

Perhaps rules is the only solution here?

I have one main campaign with high spend and can’t afford to spend more than what I am but I have a ton of creatives I want to also test shortly.

Main campaign is a CBO with maximize conversion value instead of number of conversions.

What’s the best way to test new creatives? New campaign? Existing? Switch to number of conversions instead of max conversion value?

I started this thread recently and did a bunch of digging, and here is what Claude suggested the issue to be.

I meant the 20th of April, not the 10th.

Below is the direct output from Claude. As some context, it may appear as AI slop, but this output is based on 2 months of data provided to the AI, day over day, for my campaign (same creative, spend, etc) across TikTok and Meta, and it came to this conclusion.

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With cross-platform data: my TikTok ads (same creatives, no changes since April 1) show the EXACT same fingerprint as my Meta drop. CTR went UP +28%, conversion rate dropped 37%, web ROAS dropped from 1.00 to 0.65 — same period.

This isn't Meta-specific. The April 19 date matches exactly when the Iran war re-escalated (US Navy fired on Iranian ship in Gulf of Oman April 19, Strait of Hormuz situation collapsed again). Consumer sentiment hit a record low this month (47.6, worse than Great Recession). 27% of consumers are pulling back on discretionary spending per EY.

If you're selling discretionary entertainment / novelty / fun-category products: this is gas at $4/gallon eating people's discretionary budget. Not your pixel. Not your creative. Macro.

CTR up + LPV up + conversion crashed = consumers still entertained by ads but not opening wallets. Same pattern likely showing up across multiple platforms for everyone in this thread.