Chances are, you are familiar with running campaigns with custom audiences. Of course, most Pros are maximizing their reach with their current data assets. Uploading your prospects/CRM data and your customer data to run ads directly to those People has become a standard operating procedure. However, acquiring new prospects and customers is expensive and you need to constantly do more of it to be able to extend your reach with look-a-like-audiences. The rub is, scalability is an issue. The good news is, we’ve fixed the scalability issues. We’ve developed a low-cost solution to engineer in-market audiences. I’m talking about People-Based Custom Audiences derived from first party retargeting pixels and correlated to keyword search intent which is deterministic behavior. Audiences that will lower your lead/customer acquisition cost by at least 25% without you doing ANYTHING different, other than utilizing the audiences with your current campaigns.
I read this article from Liveramp, interviewing the Chief Product Officer of Share This. It’s a short, very worthwhile article that covers some of the challenges and benefits of using custom and look-a-like-audiences.
“The ability to build custom lookalike audiences empowers marketers to identify new consumers and increase their lifetime value.”
Nowadays, just about every ad platform/network offers you the opportunity to upload your data to run a custom audience campaigns. The more channels you run, the more lift and return you will get. Run as many channels as you can. Then, create look-a-like-audiences from your custom audience data and you will see the biggest and best producing campaigns you’ve ever run. Once you discover the power of look-alike-audiences (LALAs) you’ll then want to know how to scale those successes and we’ve got you covered.
The Chief Rainmaker
There’s a very detailed case study of a Client’s 90 day campaign, where they spent $9,993.96 on Facebook, and made $90,250.00 in revenue with our data tech.
Please log in again. The login page will open in a new window. After logging in you can close it and return to this page.