Liquidity In Your Meta Ads Campaigns

By Bradley Riley
Paid Social
January 25, 2023

When it comes to running ads, there is a delicate balance to strike between manual guidance to help the ads and giving the algorithm opportunities to achieve the most efficient delivery possible.

This is where liquidity comes in.

When we discuss liquidity in relation to Facebook (or Meta) Ads, we are essentially talking about the level at which the algorithm is throttled or how fluid the delivery opportunities are.

So what does that mean?

When you make adjustments to different parts of your campaigns, ad sets and ads, you are controlling which direction the algorithm is allowed to go on. Some of these adjustments act as good guidance but too many will result in the algorithm being throttled.

What kinds of liquidity are there?

There is budget liquidity. This is where you use ABO or ad set budget optimisation instead of Advantage+ Budget Optimisation (previously known as CBO). While creative testing is likely better performed under an ABO campaign, if you’re looking for maximum delivery and maximum liquidity, you’ll want to use Advantage+ Budget Optimisation.

There is also placement liquidity. This is where you select placements. Are you select Automatic or Advantage placements for delivery everywhere across the Meta Family Platforms? Or are you selecting Feeds only? Or perhaps somewhere in-between? Again, the fewer places you allow ads to be shown, the more the algorithm is throttled or limited. Try to find a balance of a minimum of 4 placements.

There is also Advantage+ targeting expansion, which may be handy for a good top-of-funnel, cold audience but you’ll outright want to avoid this in your retargeting. Targeting expansion offers audience liquidity by receiving the agency to find people outside your selected parameters in the event that the delivery is likely to result in a positive response with regards to your optimisation objective.

As we’ve suggested throughout, Advantage+ and maximum liquidity  is not always the answer- but neither is limiting the algorithm to the extreme.

Try to strike a balance and test as much as possible!

Hope this helps!

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