• by Felicia Greiff , January 18, 2016

LendingTree, an online lending exchange that connects consumers with lenders, banks and credit partners, came to TruSignal with a challenge: Find the most likely prospects for conversion.

"We’re prospecting and looking for people we may not have had a relationship with," said Nitin Bhutani, VP-marketing, LendingTree. "We’ve been around for 15 years. Maybe [the consumer] had some transaction with us, but not recently. With TruSignal, what we wanted to see was, who is the group actually filing out our form, and how can we make that process more efficient?"

LendingTree works within a certain population, which varies from product to product. For example, mortgages have a slightly older demo, and certain loans like refinancing credit card debt skew younger. For its work with TruSignal, LendingTree focused on mortgage lending, including refinance and purchase products.

That's where TruSignal came in. The ad-tech company builds custom audiences for brands by applying predictive analytics to offline data. The company calculated a score of every U.S. adult based on how likely they were to be a customer for the brand ("Think of it like a credit score, but it's more for retail and in this case, financial services," said TruSignal’s VP-marketing, Pete LaFond.) LendingTree gave TruSignal an idea of who their customer is, and TruSignal used that data to model who was likely and who was unlikely to convert.

"Some people make sense and some don’t," LaFond said. "Even if I see a signal, I don’t want to chase ghosts or shadows. I want to focus on people, and there are so many people we can advertise to. So how do I identify the right people? What we provide is a powerful way of gaining that insight in addition to what [the clients] already have."

So far, so good. Bhutani said LendingTree was successful on two counts: Prospects came in and filled out leads, and the company saw that the prospects identified by TruSignal converted at a higher rate than LendingTree’s general population.