USING LOOKALIKE AUDIENCES TO SCALE FACEBOOK ADVERTISING

If you’re in the digital marketing game these days, you can’t ignore a powerful channel to bring traffic and sales. While your results from the SEO campaign could take months, you should use Facebook (or another PPC channel) to gain an initial boost for your digital marketing efforts.

 

 What Are Lookalike Audiences?

 

Lookalike audiences allow marketers to take advantage of the incredible amounts of data Facebook has to arrive at those best-performing audiences without excessive trial and error.

 

To put it simply, a lookalike audience is a tailored audience similar to one that you’ve already created within Facebook. These can be based on current customer lists, page likes, and website custom audiences. You can even create an audience based on people who have watched your videos, but that’s getting a little more advanced.

 

Basically, Facebook goes through the list of people in your custom audience to find the people with the most shared similarities.

Once Facebook a good understanding of who the people in your custom audience are, Facebook will create a new audience (with new people) that are closely related to your custom audience.

 

How It Works

 

The first step in building  a Lookalike is to set up a seed audience. This is the set of people you want the audience for your campaign to resemble.

To do this, first, create a custom audience.

You can build this audience by uploading your database of customers, or on the basis of traffic to your website or app.

Keep in mind that in order for a custom audience to serve as the basis of a Lookalike, it has to include more than 100 people from the same country who have Facebook accounts that match the uploaded data.

Once you’ve created your seed audience, input it in the “source” field of your new Lookalike audience.

From there, Facebook will get to work crunching data to find the users most similar to your seed audience.

 

Why You Should Use A Lookalike Audience

 

When it comes to direct response advertising, retargeting is amazing. Why? Because the people being shown your ads have already interacted with your brand and shown some interest in it.

The next best audience to target is your current customer lists. Once they’ve purchased from you, they have a higher chance of giving you more money. Actually, they are 60-70% more likely to buy from you again in the future.

But what if you’ve exhausted both of these audiences, and they’re simply not responding to any more ads?

That’s where lookalikes come in.

If you upload your list of customers, you can ask Facebook to find more people that are similar to them. This is a lot easier than trying to find specific interests to target and hoping that it works.

It just makes sense. If you have an audience and they’re all into crafting and sewing, then wouldn’t you want to find other people that have a high probability of liking crafting and sewing?

This really helps when you want to scale up your campaigns. There is a lot of conversation around scaling Facebook ads and everyone wants to share their “secret” tip or idea. But not everything works for everyone.

Lookalike audiences are one of those audiences that you should at least attempt to hit when scaling up your campaigns.

 

Summing Up

Facebook ad targeting has evolved significantly since the ad platform was introduced. While conventional performance marketing tells us it’s best to define and segment as much as possible to optimize at the most granular level, Facebook Lookalike audience challenge that assumption.

The trade-off is less visibility and control for more audience relevance and scale. For performance marketers like ourselves looking to seek out every bit of efficiency, this can be tough to swallow. Even while using lookalike audiences, we still rely on segmentation to boost performance further (more to come on how to effectively combine Lookalikes with segmentation in the future post).

The overall takeaway is that Lookalike audiences are a great way to scale Facebook advertising much more efficiently and quickly than manually finding and testing various targeting combinations.

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