How Lookalike Audiences Can Increase Advertising Efficiency

By Sam Sprague

April 19, 2021

Lookalike audiences are used on all social media platforms as a great way to target consumers based off your past customers, specific website events, or even email lists.

Essentially, these lookalike audiences allow you to target people who have similar interests, traits, and buyer behaviors as your current customers.

What is a Lookalike Audience?

Lookalike Audiences are created by placing your past customers into a database that has the characteristics of your target market.

For example, if you own a content marketing agency, you would target your email list and the customer data you have on file with Google Analytics for the same segment of people who are interested in content marketing.

Creating these lookalike audiences is important because they emulate an audience’s behavior or interests without requiring any additional effort from the marketer.

Rather than targeting all of your current customers based on their behaviors, interests, and demographics, lookalike audiences give marketers a way to target consumers who have similar traits as their previous customers.

Let’s break it down:

  • The business finds a list of customers who are already on the platform (e.g., Facebook).
  • The business creates an ad that displays the same characteristics of their current customer base, such as age, gender or zip code.
  • That ad is then sent out to people who are in that similar demographic location around the world (or in specific geo locations).

This type of advertising is effective because it allows businesses to expand their reach and target new people who may be interested in their products based on what people similar to them have already said.

Facebook has an advanced Ad Create tool that allows businesses to create a customer list and then find other users that are a good match for those customers.

Here’s how it works:

  1. Step 1: Start with your current customer base. If you don’t have a list, just input a few key profiles of the people that are likely your customers (e.g., age, gender, zip code).
  2. Step 2: Lookalike audience is created by filtering users based on what you input. Facebook identifies similar users to your current customers.
  3. Step 3: Ad targeting is based off these lookalike audiences. Which means that if you were to send an ad out to potential customers, those who match the characteristics of your initial customer base will get the ad on their Facebook feed.

There are several benefits to lookalike audiences:

  • They are easy to set up and can be set up within minutes.
  • They allow businesses to target the right buyer, based on what people who are similar said about their products.
  • They save time as it allows businesses to achieve the results needed without having to spend months or even years searching for a new buyer demographic.

The main argument against lookalike audiences is that they do not provide enough unique information.

Because people have similar traits, interests, and behaviors to those in your customer base, they may not be different enough to springboard into a purchase.

Let’s take an example:

Let’s say you are a shoe company (you know your demographics – let’s use the average shoe size in the US as an example).

You could create a lookalike audience of 1,000 people who are around your average shoe size.

This means that if you wanted to target the exact same audience that is already buying your shoes, you would need to get 100 people into those 1,000 lookalikes.

This is obviously not very useful.

However, with a lookalike audience, you could target the right buyer demographics (i.e., people who like your product and are in an area where they are likely to purchase).

If you showcased ads to these 1,000 people that were a similar match to your current customer base, chances are they would get the ad that you would have been able to target.

Another argument against lookalike audiences is that it relies on past data.

People on a platform today do not represent the buying behavior of a brand’s past customers.

This can be especially useful in an environment where there are so many brands.

If a business’s customer base is large enough, they may find that they have to create a lookalike audience of customers who had similar traits, interests, and behaviors as their own main customer base.

As we mentioned above, this is a problem because most people do not share their buying habits with the brands they purchase from.

However, if more businesses used lookalike audiences and placed ads to these more loyal customers based on their past customers’ traits, interests and behaviors – those that shared their habits with the brand – those ads would probably be more effective.

In summary, lookalike audiences are great for businesses that have a small customer base, and when things are more in sync with what their customers are buying.

They do not work as well to target new customers and for larger businesses who would need to devote more resources to create these customer lists.

NOTE: When using the Lookalike Audiences tool:

  • If you want to use the US as the example, you must be using a Facebook Page or a Business Page rather than a personal profile.
  • It is recommended that you use these audiences mostly for non-US audiences (e.g., UK, Australia, New Zealand).
  • It is also recommended audience size are between 2,000 – 4,000 people. Any more or less tend to give poor results.

Sam Sprague Administrator
CEO & Founder , Sprague Media
Sam is the Founder & CEO of Sprague Media. He has over 10 years of experience in the Digital & Social Media Marketing world, on the agency and client-side. A Marine Veteran and Father, Sam is an avid Football and Basketball connoisseur who likes nothing better than to spend quarantine watching games!
follow me

Leave a Reply

Your email address will not be published. Required fields are marked *

You may use these HTML tags and attributes:

<a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <s> <strike> <strong>