If you're running some Meta Ads campaigns, you know how crucial it is to keep your ad spend under control and get the most bang for your buck. Using cost caps, now known as cost per result goal, is one way you can maximize your conversion volume and regulate your cost. This quick and easy guide will show you how to apply a cost cap (cost per result goal) in Meta Ads campaigns, as well as some tips on when you should use it and how much should it be. Without further ado, let's get started!
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Looking for help or support on Meta Ads?
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In case you find yourself in need of some video guidance, here's a quick 3-minute tutorial from XYZ Lab's Youtube Channel!
Topics Covered:
Step 1️: Navigate to your Meta Ads Manager
Step 2️: Create a Campaign with any objective
Step 3: Navigate to the Ad Set, under Performance goal, find the Cost per result goal field
Step 4: Insert the cost cap you would like to apply
Step 5: Select bid cap strategy: Cost per result goal
There are two options:
Cost Cap (cost per result goal) - set a maximum of $X per goal (e.g. per lead or per sale)
Bid Cap - set a maximum cap for bidding per 1,000 impressions (more advanced)
Select the cost per result goal (cost cap).
You can apply this cost cap wherever your conversion action is (i.e. whether it is on the website, instant forms, etc), as well as with the any campaign objective and any performance goal (e.g. cost per sale, cost per leads, or other actions you're optimizing for).
When should you apply a cost cap and how much should the cost cap be?
Ideally, you should start your campaigns without a cost cap. Run the campaign for 2 weeks or deliver at least 50 results. Then, apply a cost cap that is -10% lower than your current cost per result and let the algorithm optimize your ad sets to achieve it.
For example, if your cost per result now is $10, you should set a cost cap at $8-9. You shouldn't change it to $5 or $2 because it provides an unrealistic target and your ad delivery will be limited. You should monitor the campaign closely and give the system incremental targets (10% lower) on a weekly or biweekly basis so the optimization can work in the background. If you see good results, then you can progressively decrease the cost per result as the system calibrates.
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