Are you utilisng your existing customer data effectively and efficiently? Would you like to know how we drove a CPL of under £8 by purely leveraging a client’s customer data?
One of the most effective ways to utilise your existing customer data is – Lookalikes! In this article, I will be explaining what a ‘Lookalike’ audience is, how it works and why it’s important to leverage these audiences to help you and your business find new & exciting prospects.
So, what is a Facebook Lookalike audience?
Essentially this:
A Facebook Lookalike audience is a fantastic way to help your ads reach new users that are highly likely to be interested in your business and what you have to offer them.
We know this because a Lookalike audience will share similar characteristics to your existing customers or other core audiences i.e. website visitors, previous customers and Facebook followers.
How does a Lookalike audience work?
To create an effective Lookalike audience, you will first need a core or source audience. This can include but is not limited to: website visitors; existing customer data; newsletter sign-ups; existing customers/sales data.
The larger your source audience is, the higher the volume of data you will initially have, providing you with a more accurate picture of the audience you’re trying to replicate. Facebook recommends at least 100 people, but again, the larger the source audience the easier it will be for Facebook to connect the dots and help you reach new users you previously wouldn’t have been able to reach.
Once you’ve prepared your source audience, it’s time to create your Lookalike audience. Facebook is able to create this by leveraging the information contained in your source audience. It will analyse the behaviours, interests & demographics of this audience and then find new users who share similar qualities.
Now you have your Lookalike audience, but you’re not quite finished. You need to decide what percentage range your new audience will be set at. Typically, most Lookalike audiences are set between 1-3%. Smaller percentages will be a closer match to your source audience, but larger percentages will create a bigger, broader audience.
Why are Lookalikes important?
There are over 48 Million Facebook users in the UK alone! Remarketing is an essential part of any marketing strategy, as it’s vitally important to re-engage with your potential customers. But Prospecting is equally as important…
Given the sheer volume of people who use Facebook every day, you’re likely missing out on a huge opportunity to find & target new customers. A Lookalike audience can help you find these people!
A Lookalike audience allows you to find new users who share common traits & behaviours with your existing customers. There are users on Facebook right now who are interested in your business, they just don’t yet know that you exist.
On top of this, you can test the effectiveness of various Lookalike audiences from multiple source audiences. This allows you to learn which audiences are most valuable to you & your business.
It’s time for you to start utilising Facebook’s vast database to find your new customers!
Results from a Lookalike Campaign
The below is an existing client of ours who specialises in home improvements across South Wales. The following results are the last 3 months of Facebook activity, driven by Lookalike audiences alone!
These audiences are incredibly effective and the chances are that you already have the relevant audience & customer data available to you, it’s just not being used.
What are your thoughts on Lookalike audiences? Are you currently using them in your campaigns and have you had a good experience with them? Here at DNRG, we’re constantly finding new ways to leverage these audiences & testing them to measure their effectiveness.
So, now you know the possibilities Lookalike audiences can offer you, it might be time to consider how they could fit into your marketing strategy?
If you’d like to find out more about Facebook advertising & Lookalike audiences, get in touch with our Paid Media team and we’d be happy to talk you through this.
