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Why just identifying a “look alike” segment will get you into trouble?

When it comes to targeting new customers Facebook Lookalike campaigns are hard to beat. Creating a Lookalike campaign starts when you upload a list of consumers from your Facebook data (pixel, app or page) whose ‘Lookalikes’ you want to target. Facebook delivers your ad to consumers who behave most like your Lookalikes. While Lookalike campaigns are easy to operate there a few tried and true tips for getting the most out of your ad dollars.

1. Upload new customer lists regularly

One of the most common Lookalike Audiences is a list of current customers. This is a fantastic place to get started, but you should think of this as the beginning and not the end. Because Facebook prioritizes the lowest hanging fruit, the customer Lookalike list can see its effectiveness wain over time. This can easily be avoided by regularly uploading new customer lists and creating new Lookalike Audiences.

2. Segment customer lists into smaller groups

Not all customers are created equal. Some customers have a higher lifetime value than others. With Lookalike Audiences, you can take advantage of those differences within your customer base and come up with more advanced lookalike models. Are there natural segmentations within your customer base you could use to create multiple root audiences from?

If you are a B2B company the different stages of your sales funnel (customers, opportunities, sales accepted leads, marketing qualified leads) can serve as your custom audiences segments.

If you’re only uploading one list and calling it “customer list”, stop and take a look at the customer base and try and find natural segmentation within it.

Examples of how to set up and analyze Lookalike A/B tests

Once you have segmented your Lookalike audiences’ the next step is to A/B test which audience performs better. A simple way to do this is to leverage the default ‘Events’ tracking found in both Facebook and Google. For example if you are a e-commerce provider, Facebook’s standard e-commerce relevant events include things like AddToCart, Pageview and Purchase. To run a simple A/B test create Lookalike Audiences from two versions of the same event (for example the purchasing customers of two distinct but similar positioning products) then test to determine which Lookalike audience performs better.

Companies who leverage Outlier can track these campaigns in two ways. One, if you set up two lookalike campaigns, Outlier analyzes their performance on a daily basis via our Root Cause Analysis feature. Meaning you’d see in your daily story that “lookalike campaign A” is contributing more to your KPIs, like page views. The second way is over time, Outlier will model the behavior expected from the A/B test campaigns and you can decide which one is best to optimize around.

Join the ranks of marketers who have turned their data into a competitive advantage with Outlier. Want to know the impossible with your data?