How a leading DTC home services brand cut $100K+/month in wasted leads and qualified appointments with Credit Score Proxy

For over a century, this leading DTC home services brand has delivered innovative, high-quality products that improve everyday life. But as a forward-thinking company, they’re constantly evolving their customer acquisition strategy to stay ahead. And in today’s market, that means solving one of the toughest challenges in lead buying: separating high-potential prospects from those that will never convert.

The challenge of ping-post

Like many brands in home services, this Faraday client acquires leads from third-party sources using a real-time bidding system called ping-post. In this system, lead sellers send basic lead details (the "ping") to potential buyers, who then evaluate the lead based on predefined criteria. If a buyer decides to proceed, they purchase the full lead details (the "post").

While this system allows for rapid lead distribution, it also presents a major challenge: identifying which leads have real potential versus those that are unlikely to convert. Without an efficient filtering process, businesses risk wasting marketing dollars on low-quality leads that never became customers. And at over $40 per lead (in this brand’s case), these mistakes can quickly add up to a serious financial loss.

Although this brand had always been able to hit their numbers with their existing lead engagement strategy, they weren’t happy with “good enough.” They wanted excellence, and in this case that meant actively assessing the quality of all leads before they even entered their sales funnel to maximize the value of their lists.

Real-time lead rejection with Faraday

To add this functionality to their tech stack, this brand partnered with Faraday to integrate custom predictive datapoints trained on their own historical data directly into their lead buying workflow—allowing them to reject the least-likely-to-convert prospects before ever placing a bid.

This process works by scoring each ping in real time. When a lead becomes available for purchase, the brand automatically requests a custom datapoint: likelihood-to-convert, through Faraday’s real-time Lookup API. The result is routed back via our integration with ActiveProspect’s lead routing software LeadConduit, so leads that fall below their selected threshold can be rejected—avoiding the purchase entirely.

The results were immediate: in just the first five months, more than 13,000 low-quality leads were rejected, saving over $500,000 in wasted spend.

If you’d like to learn more about our integration with LeadConduit, check out this blog from our team and ActiveProspect.

Extending value with Credit Score Proxy

Building on this success, the brand wanted to reduce wasted time at the appointment stage. The answer came from another type of Faraday data: an off-the-shelf consumer datapoint called Credit Score Proxy, delivered through the Faraday Identity Graph (FIG).

FIG contains over 1,500 consumer datapoints available from day one, covering everything from demographics to financial proxies. Unlike custom predictive datapoints—which are trained on a brand’s historical outcomes and tuned to specific goals—consumer datapoints come prebuilt and can provide immediate predictive value.

Credit Score Proxy, for example, ranks U.S. households by purchasing power and conversion potential. It serves as a privacy-safe stand-in for financial reliability, helping brands flag leads likely to fail credit checks—without requiring homeowner consent or a bureau pull.

By mapping Credit Score Proxy into their lead management system, this brand now flags low-likelihood leads at the appointment confirmation stage. The results are clear: leads in the bottom tiers (as identified by Credit Score Proxy) fail credit checks about 75% of the time. By identifying these upfront, this brand avoids wasted appointments and ensures their sales team stays focused on prospects most likely to succeed.

Don’t just take it from us

We're excited about our partnership with this client—but we’ll let their team speak for themselves. Here’s what their Director of Marketing had to say:

"In just six months, Faraday has become the centerpiece of our entire go-to-market strategy. We now prioritize calls based on Faraday scores, kick back low-quality leads, and save thousands of dollars every week.

We treat every lead according to its potential value and a high Faraday score goes to the front of the line. And now, we’re even applying Faraday’s scores to qualifying appointments. It’s been a complete shift."

Here’s why it matters

This brand’s approach shows how both custom predictive datapoints and prebuilt consumer data can optimize various stages of the funnel. In this case a custom model filters out low-quality leads before bids are placed and Credit Score Proxy suppresses appointments unlikely to succeed, preserving sales resources.

What’s important is that this wasn’t about more data for its own sake. Faraday worked with this brand to identify which specific datapoints would matter most at specific stages of the funnel. The team cut wasted spend, improved close rates, and freed up staff to focus on the prospects most likely to convert.

Working with Faraday doesn't just mean getting best-in-class data, it means getting the strategic guidance to use it to drive concrete value, and this client - as well as all our other clients - are seeing that value every day.

Want to see how Faraday’s predictive datapoints can transform your funnel and drive similar value for your brand? Let’s talk.