How a multi-brand home services company got 3x more leads from direct mail

A multi-brand home services company brought in 1.8x to 3x more leads from direct mail by scoring its mailing lists with Faraday and sending mail only to the households most likely to become customers.

At a glance

• The challenge: Rising digital and Google costs, along with slower home sales, drove an increase in the company’s cost per lead and cost to win each new customer.
• The solution: The company scored its HVAC mail lists with Faraday, combining its own customer records with the consumer data in the Faraday Identity Graph, and mailed only the households most likely to buy.
• The result: Scored mail brought in 1.8x to 3x more leads, and those leads converted at higher rates. The company has since expanded scoring to plumbing, generators and its other brands, and each new round of models has done better than the last.

Why the company's cost per lead was climbing

The company's central marketing team runs customer acquisition for a family of HVAC, plumbing and electrical brands. In home services that work starts with a lead.

But at the start of 2026, those leads were getting more expensive. Slower home sales meant fewer new homeowners fixing the houses they'd just bought, and Google, one of the company's biggest paid channels, was delivering fewer leads for the same spend. Each new customer cost more to win as a result.

"We were dealing with a turbulent demand environment, especially within digital and Google channels, which drove up our cost of marketing, cost per lead, and cost of customer acquisition. We had to step back, optimize our channel mix, and find more targeted and surgical ways to reach our desired audience."

CMO, multi-brand home services company

For the marketing team, one of the first places to get more surgical was direct mail, a channel it already relied on alongside Google, lead aggregators and print. Unlike an ad auction, mail lets the team decide exactly which households it pays to reach. And because the cost of each piece is set by printing and postage rather than by bidding against other advertisers, better targeting translates directly into a lower cost per qualified lead. The question the team brought to Faraday was which households on its lists were worth mailing.

How the company started scoring mail lists with Faraday

With the decision made to sharpen its direct mail, the company went looking for a partner and found Faraday through a referral. The decision was made to start with HVAC, one of its biggest service lines.

The company already knew who its customers were. What it didn’t know was which of the households on its lead lists looked most like its best customers. To find out, Faraday built a custom prediction trained on the company’s own customer records and enriched with the Faraday Identity Graph, which covers 1,400+ attributes on 240M U.S. adults and their households. That added the household and property details that customer records alone can’t show, giving the model a fuller picture of who actually becomes a customer.

Faraday then scored every household on the HVAC lists from most to least likely to become a customer, and the company mailed the households at the top. From there, the test came down to what showed up in its call centers (read more about Faraday’s approach to lead suppression).

Results: 1.8x to 3x more leads and higher conversion rates

The results were clear: scored mail delivered 1.8x to 3x more leads than the company would otherwise expect from direct mail. For a business where every install starts with a phone call, that’s a big deal, and the CMO was clear about how big: in a category as lead-intensive as home services, he said, leads are “everything.”

These leads weren’t just more likely to respond. They were also more likely to buy. Conversion rates rose for the households Faraday picked, and the CMO believes better targeting is part of why:

“Targeting the right customer with the right message at the right time establishes a little more trust when the technician is in the home. And we see that carry through in conversion rates.”

CMO, multi-brand home services company

How the results held up across the company's other trades

With HVAC working, the company brought the same approach to its other trades, including plumbing and generators. Faraday produced a bespoke model for each trade, built around who buys that particular service, and the results held.

Even better, the models have improved with each round. The company's second generation of models outperformed the first, and the newest models are landing consistently closer to the 3x end of the range.

Ready to make direct mail a revenue channel?

These results didn’t come from a single scored mailing. They came from an ongoing partnership. Faraday built a model for each service line, improved those models with every round of results, and worked with the company’s team on the next questions their mail program raised.

If direct mail is a meaningful part of your marketing, talk to our team about how we can help you get the most out of every piece you send.

Direct mail FAQ

How can I improve my direct mail response rate?

The biggest factor is who gets the mail. Sending to households that look like your existing customers usually does more than changing the design or the offer. Predictive scoring ranks every household on a list by how likely it is to respond, so you can mail the top of the list and skip the rest.

How do I reduce direct mail costs without losing results?

Mail fewer of the wrong households. Every piece costs the same to print and send, so cutting the households least likely to respond lowers your spend while keeping most of your responses. Set your cutoff where the expected return of a household no longer covers the cost of mailing it.

What is predictive targeting for direct mail?

It’s a way to choose recipients using a model trained on your past customers. The model learns what your customers have in common, then scores a mail list so you can see which households look most like them. One multi-brand home services company used this approach to get 1.8x to 3x more leads from its direct mail.

How do I measure whether a direct mail campaign worked?

Tie every response back to the household that received the mail, using unique offer codes, dedicated phone numbers or address matching. To see if your targeting made a difference, mail a small group of lower-ranked households in the same drop and compare their response to your top households.

What data do I need to target direct mail better?

You need records of customers who’ve already done what you want, like booked a service or made a purchase. You also need the list you plan to mail. Adding household details like income, home ownership and life stage helps a model find patterns your customer records alone won’t show.