Location targeting is a big problem, and I talked about it in a recent video. If you’re promoting a business that only appeals to local residents, you’re automatically going to reach people who were recently there, too. The same issue exists if you want to reach visitors.
To get around that, I’ve seen advertisers use geo fencing. Here’s an example…
An Example of Geo Fencing
An advertiser may decide that they only want to reach locals of Anaheim, and not people from Los Angeles who happen to be there. So, they target a four-mile radius around Anaheim, which is about 400,000 people.
Then they exclude people from Los Angeles (which is technically “living in or recently in” LA).
The radii of these two locations do no intersect, so you’d assume the exclusion wouldn’t have an impact. But the audience drops to under 300,000 people, or about a third of what it was.
While this approach removes people living in LA who traveled to Anaheim recently, it also excludes those who live in Anaheim and were traveling in LA. So in an attempt to exclude people you don’t want, you also exclude some you do.
Solutions
There isn’t a great solution, unfortunately. Since Meta no longer allows advertisers to only reach people living in a location, it’s simply not possible. Any attempt to eliminate non-locals will ultimately also exclude the locals you want to reach, too.
Instead, the focus should be on optimizing for conversions and crafting copy and creative that appeal to your target demographic. This combination provides the best chance of success.
The algorithm learns from who performs the action that you want (defined by your performance goal). If you use a performance goal for a light action like post engagement or link clicks, you can expect you’ll get a lot of random clicks from people who aren’t your target demographic.
But, if you optimize for conversions and make the offer something that only appeals to locals, you’ll have much better luck. Combined with ad copy and creative that make it clear you are appealing to locals, you’ll create a situation where the algorithm will begin to learn who needs to see your ad in the future.
