Buying a new house while selling your current one is a colossal headache — and a massive financial burden. You’re fixing up your place for the sale and prepping to move, scouring new neighborhoods and going to showings, not to mention finagling your finances to make the transition work while your equity is still tied up in your current house.

COMPANY X is a technology-driven real estate company that’s leading the charge for a simpler, stress-free way to buy and sell a home.

With COMPANY X, you can unlock the equity in your current home to buy and move into your dream home before you sell. Plus, they offer a host of innovative tools to assist you every step of the way, from finding and closing on the new place to prepping, listing, and marketing your current one.

There’s no question that COMPANY is an invaluable resource for home buyers and sellers. But they operate in just eleven specific markets, including Atlanta, Denver, and Houston, and that hyperlocal focus posed a unique set of challenges for COMPANY’s marketing team in their early years.

Getting local marketing right is tricky with Facebook Ads

Like many DTC brands, COMPANY relies heavily on Facebook for top-of-funnel marketing. But, they were struggling to run targeted campaigns. Since they’re a real estate company, they face extra limitations in Facebook right off the bat in order to comply with fair housing and lending laws.

On top of that, Facebook’s native lookalike capabilities couldn’t handle the granular geographic targeting COMPANY needed. “We got so narrow that any of the audience tools that these platforms offer off the shelf, like lookalike audiences or interest audiences, really weren’t that valuable for us,” they explained. “We were forced to go broad within those [regions].”

With broad audiences, Facebook’s algorithm managed to deliver a decent volume of leads, but lead quality was poor. Just a small percentage became mid- and lower-funnel opportunities.

The problem was clear: they didn’t have the kind of data they needed to power more sophisticated targeting efforts. Without that data, they couldn’t reliably reach their ideal leads.

COMPANY looked into a number of solutions, including contracting with third-party data vendors and working with COMPANY’s data science team to leverage that extra layer of data in Facebook.

Ultimately, they chose to work with Lead Intelligence, taking advantage of our responsibly-sourced identity graph and proven predictive models to build the audiences they needed at a fraction of the cost of building their own AI pipeline.

Reaching the right home buyers and sellers

Lead Intelligence started by building a machine learning model to identify people most likely to become COMPANY customers. Since all our models are powered by our own identity graph, which contains consumer profile data on every US adult, it surfaces people that Facebook’s algorithms might overlook. COMPANY’s audience was then uploaded to Facebook via direct integration.

By building a custom audience from scratch, COMPANY was able to target just the most promising home buyers and sellers. They could finally focus on the audience that was likely to deliver the most value, and the difference was immediately noticeable.

“We’re driving higher intent users who really are looking to move, and not just get a valuation on their house.”

How much higher is that intent?

Well, COMPANY has seen a 30% lower customer acquisition cost with Lead Intelligence audiences compared to their original broad audiences. When it comes to ad spend efficiency, that’s a no-brainer.

Improving attribution around iOS 14

When we asked their team if iOS updates and Facebook’s resulting attribution issues have changed how he thinks about their Facebook strategy, they told us it’s going to continue to play a dominant role in their channel mix.

“They give us the option to be hyperlocal in a way that a lot of other channels don’t,”. Running a campaign in specific regions is not something they can do, for instance, on podcasts, which are another important channel for their team.