Kill criteria: deciding when to cut an ad

What kill criteria are

Kill criteria are rules, decided before a campaign launches, that define exactly when an underperforming ad gets turned off. Instead of judging an ad by gut feeling each time you check the account, you set thresholds in advance for spend, cost per result, and time in market, and you follow them consistently.

The point is not to be harsh on ads. It is to remove the emotional and inconsistent part of the decision so that every ad gets a fair, equal test and no ad burns budget past the point where it has already shown you the answer.

Why kill criteria matter

Without a rule, two failure modes show up constantly. The first is cutting an ad too early, before it has spent enough to escape the learning phase or before Meta’s algorithm had a real chance to find the right audience for it. The second is letting a losing ad run too long because nobody wants to be the one who kills it, or because the account owner keeps hoping it will turn around.

Both mistakes cost money. Cutting too early throws away ads that might have worked and forces you to keep testing new, unproven creative. Cutting too late means spend keeps flowing to something that has already demonstrated it will not convert at an acceptable cost.

How to set kill criteria

Base the first checkpoint on spend relative to your target cost per result, not on calendar days. A common approach is to let an ad spend two to three times your target cost per result with zero or very few results before pausing it, since that gives the algorithm a real sample to work with.

Add a minimum time floor as well, often 48 to 72 hours, so an ad is not paused mid-learning-phase purely because it happens to have spent quickly in a short window.

Set a secondary rule for ads that are producing results but at an unacceptable cost. If an ad’s rolling cost per result over its last meaningful chunk of spend sits well above target, with no improving trend, that is a signal to cut even if total spend is still low.

Write the thresholds down before launch and apply them the same way to every ad in the test. Consistency is what makes kill criteria useful, since applying different bars to different ads reintroduces the same bias you were trying to remove.

How to act on it

Review new ads against kill criteria once, at the checkpoint, rather than repeatedly throughout the day. Checking too often invites premature judgment based on small sample sizes.

Distinguish a kill decision from a pause for creative refresh. An ad that is technically still under threshold but flattening in click-through rate might be a candidate for a new creative variant rather than an outright kill.

Common mistakes

Killing ads before they exit the learning phase. Letting a clear loser run because nobody wants to make the call. Using calendar time alone without accounting for spend velocity. Applying different thresholds to different ads based on who created them.

How YieldBI helps

YieldBI applies your configured spend and cost thresholds automatically and flags ads that cross them, so the pause decision follows the same rule every time instead of depending on who is looking at the account that day. Growth Priority and Profit Goal build on the same thresholds to recommend which ads to cut, scale, or keep testing.