So a question you might be wondering in your sleep–since this is of course what you dream about late at night!–is: how to create a great list of managed placements to upload to Adwords / Google Ads?

Yes, that keeps me up at night. You have no idea!

But first, let’s explain the context of the question. For Display and programmatic campaigns, there are lots of ways to target them. You can define audiences and give them characteristics, such as interests or what they’re in the market to buy. You can narrow it by demographic info, like male or female, and parental status. You can narrow it by geography and lots of other criteria.

But still… you often want the even-further granular target, the best way is to find the sites you want to advertise on and upload that list. This feature is called “Managed Placements” on Adwords/Google Ads and other systems. Basically, you upload a list of sites–domains, directories, or specific pages–and it only shows the ads on those pages/sites (in addition to the other targeting criteria you’ve specified).

The great thing about managed placements is you get to be as on-target as possible these days, and you can avoid spammy, low quality sites as well. You have your ads appear on precisely the sites you want them to appear on: no more, no less.

But there’s a problem with managed placements: finding them, compiling them.

How do you find a list of placements you want to, well, manage (that is, upload to your site)?

Google. Google some more. Do a variation of your Google search query. Go to results on the 33rd page in Google. Click on every Google result. And so forth and so forth.

Doing that takes time–but it’s worse than that. It’s time you can’t outsource to someone else. Why? To figure out which sites are on-target as placements requires enough sophistication, and as such, anyone you can hire to do that will be expensive.

It requires sophistication because you need to:

  • Understand the target market and product, to be sure the page or site is on-target
  • Understand which sites smell spammy or low-quality
  • Understand which sites are off-brand so you wouldn’t want to appear on
  • Understand which sites get so much traffic they will overwhelm the whole list
  • Understand which sites likely get so little traffic they’re not worth the energy

And so forth. It is a process but it requires a lot of smelling and judgment.

And you know what machine learning and artificial intelligence are good at? Smelling and judgment. Well, at least in a restricted domain such as this; our AI/alien overlords aren’t here yet (wait until February 6th 2022 for that!).

That’s why I happen to love the solution to this problem developed by Managed Placements. In short, it gives you the best of managed placements–the white lists of on-target sites–without the worst (the endless Googling and qualification of every. Single. Site. Again. And. Again.)

How does it work? Basically by streamlining the Googling process for you and doing the heavy lifting. You put in a bunch of words related to the product and target market. It then spends a few hours compiling a list. It automatically disqualifies off-target, likely spammy, and other ones. Then it comes back with the list for you to review. You tweak it, train it, and possibly let it run a few more iterations based on your training–and voila! There’s a list for you to use!

What makes it even better is the cost: it’s free. Well, just because it’s in a free beta mode. I’m presuming there will be a cost eventually and the team is just now trying to figure out the right model. Here’s a hint: you want the number that’s the highest amount that your average PPC would pay but that’s the lowest amount to help you profit–you want to find the Venn Diagram overlap there.

So, give it a whirl, and let me know your thoughts on how it goes–we’ll write more articles about them in the future, I’m sure.