Why Brands Can’t Afford to Ignore Similar & Lookalike Audiences

Modern digital marketing campaigns make extensive use of retargeting, showing paid ads to users who have already interacted with a brand’s website, paid ads, or social media content. When implemented correctly, these types of campaigns have far stronger metrics than their non-retargeted counterparts, making them attractive to business and marketers alike.

While retargeted campaigns are well worth the investment, there are drawbacks to retargeting. For one, it takes time and money to develop retargeting audiences. For another, these audiences are limited to users who’ve already interacted with your brand. If you’re looking for new prospects, you won’t find them in your retargeting audience.

While some digital marketers will use the terms “similar audience” and “lookalike audience” interchangeably, it’s important to note that these are two separate tools.

Similar audience is a feature on Google Ads. This feature is based on remarketing lists for search ads (RLSAs), i.e., users you are retargeting because they’ve interacted with your website. When you use RLSAs in a paid search campaign, Google will analyze the search behavior of your RLSA audience. It will then give you the option of expanding your campaign to target a similar audience. This is a group of users whose search behavior closely mirrors your RLSA audience.

But what if there was a simple, low-cost way to double or triple the size of this audience? And what if you could target new users in the process? That’s where similar audiences (on Google Ads) and lookalike audiences (on Facebook) can make a huge difference in your digital marketing strategy.

Lookalike audience is a feature used for Facebook ads, which works similarly to Google’s similar audiences feature. However, Facebook isn’t using search behavior to build this audience. Instead, it bases your lookalike audience on features like user interests and demographic data. Facebook also allows gives you control over the size of your lookalike audience. Smaller audiences will mirror your original audience more closely, while larger audiences reach more users.

In both cases, there are limitations to these tools. Both features require a large enough sample size to create a mirror audience. Google will only give the option of a similar audience if your original RLSA has “at least 1,000 cookies with enough similarity in search behavior.” Facebook requires at least 100 users in your source audience, but it recommends using a source audience of at least 1,000 users.

These concerns aside, the question for marketers is simple: Do similar and lookalike audiences work?

Why You Should Invest in Similar and Lookalike Audiences

If digital marketers have learned one thing over the past decade, it’s that Google and Facebook know what they’re doing. So it should come as no surprise that brands who’ve adopted similar and lookalike audiences have seen impressive results.

In simple terms, these features allow you to target a larger base of potential customers while retaining the positive metrics of retargeted marketing. In numerous case studies, mirrored audiences on Google and Facebook have had similar engagement and conversion metrics to the audiences on which they were based. In terms of purchasing behavior, it’s almost like cloning your most promising leads.

Even better, mirrored audiences can significantly reduce the cost of acquiring new customers. While there is an investment of time and money to develop your initial retargeting audience, it costs much less to mirror that audience via Google or Facebook. Not only are you practically cloning your best leads, but the cloning process also costs pennies on the dollar when compared to traditional lead acquisition.

Ultimately, similar and lookalike audiences are a near-foolproof way to get more value out of your current retargeting data and increase the overall efficiency of your digital spend. However, there’s one important catch. For these features to work, you need to be targeting the right people in the first place. That means investing the time and money it takes to build high-quality source data for your brand.