How We Find Commercial Leads That Apollo and ZoomInfo Miss

If you've ever wondered how we find commercial leads for roofing contractors, you're not alone. It's the most common question we get on sales calls.

The short answer: we don't buy leads from a database. We build them from scratch, one property at a time.

Here's exactly how that works.

The Problem With Traditional Lead Databases

Most B2B lead generation tools (Apollo, ZoomInfo, Seamless.AI) get their data from one main source: LinkedIn.

That works great for reaching marketing directors at tech companies. Those people update their LinkedIn profiles religiously. But facility managers? Property owners of commercial buildings? The guy who manages a strip mall or an apartment complex?

About half of them aren't on LinkedIn at all.

Think about it. The facility manager at a manufacturing plant in Richmond doesn't need LinkedIn to do his job. Neither does the property manager overseeing a church or a warehouse. They're not looking for their next career move. They're just trying to keep the building running.

So when you use tools that depend on LinkedIn data, you're only reaching half the market. The other half—the people who actually make decisions about commercial roofs—are invisible to these platforms.

That's the gap we fill.

Step 1: Finding Every Commercial Property in Your Service Area

We start with Google Maps.

Why Google Maps? Because every commercial property with a roof is on there. Churches, warehouses, apartment complexes, manufacturing facilities, strip malls, medical offices. If it exists, it's on Google Maps.

Google Maps has data on over 200 million businesses worldwide. But here's the thing: you can't just export that data. Google limits what you can see and how much you can access at once. If you search for "commercial buildings in Dallas," you'll get maybe 60 results before it cuts you off.

We built our own system to work around those limits. We break your service area into small chunks (zip codes, neighborhoods, specific streets) and search each one individually. Then we stitch all those searches together into one complete list.

For a single campaign, we might run hundreds of individual searches across different property types:

And so on, across every zip code in your service area. The result? A complete list of commercial properties with roofs in your territory. Not a filtered subset. Everything.

Step 2: Finding the Person Who Actually Decides

Having a list of buildings is only half the battle. You can't send an email to "123 Main Street." You need a name.

And not just any name. You need the person who actually approves roofing work.

This is where it gets interesting.

For most commercial properties, the decision maker isn't obvious. It might be:

• The business owner (for small to mid-size companies)
• A facilities director (for larger organizations)
• A property manager (for apartment buildings and retail centers)
• A maintenance supervisor (for industrial facilities)
• A regional director at a property management company (for multi-location portfolios)

The same building might have different decision makers depending on the type of work. A facilities director might handle routine repairs, but a regional VP might need to approve a full replacement.

Our AI agents dig into each property to figure out who that person is.

We don't just guess based on company size. We actually research each one. The system looks at:

The AI looks at all these sources and pieces together who the right person is likely to be.

Step 3: Validating the Email

Once we have a name, we need an email address.

Here's a secret most people don't know: business emails follow predictable patterns. About 90% of business emails are some combination of:

If we know the person's name is John Smith and the company's website is "johnsonproperties.com," we can generate a list of possible emails and test which one is valid.

How do we test? There are tools that can check if an email address exists without actually sending a message. They ping the mail server and see if it accepts delivery for that address.

This validation step is crucial. If we send to a bunch of invalid emails, our deliverability drops and everything starts going to spam. So we only add verified emails to your campaign.

Why This Approach Creates a Data Advantage

Traditional databases get stale fast. Someone changes jobs, a company changes their email format, a property gets sold to a new owner. Within a year, a significant chunk of any purchased list is outdated.

Our data is built fresh for each campaign. When we research a property, we're looking at current information, not a snapshot from 18 months ago.

More importantly, we're finding contacts that don't exist in traditional databases at all. The facility manager who isn't on LinkedIn. The property owner whose name only appears in state business filings. The operations director whose contact info is buried in a company website that nobody else is scraping.

These people get far fewer cold emails than a marketing director at a tech company. A typical VP of Marketing in San Francisco might get 50 outbound emails per week. A facilities director at a manufacturing plant in your service area might get 2 or 3. Fewer cold emails means higher response rates. Simple math.

How It Looks in Practice

When you sign up with Maverick, here's what happens behind the scenes:

The whole process runs on autopilot. You're not spending hours on LinkedIn or cold calling receptionists trying to get past the gatekeeper. The system handles the prospecting. You handle the relationship once someone raises their hand.

The Bottom Line

Finding commercial leads isn't about having access to some magic database. It's about doing the research that nobody else is willing to do.

Google Maps has every commercial property with a roof. State registries have business ownership information. Company websites have contact details. It's all public information.

The hard part is connecting all those dots at scale. That's what we built Maverick to do.

One of our roofing clients put it simply: "Finding out who the right person is, is honestly the most difficult part."

That's exactly the part we solve.

Jonathan Michael

Founder, Maverick AI