The List Problem

Hey there,

Kevin from Astris Partners with another edition.

Most B2B founders think their cold email problem is messaging. They spend hours perfecting the copy, testing different angles, tweaking the call to action.

Then they send it to a list from Apollo or ZoomInfo and get crickets.

Here's what they're missing: everyone else is emailing the same people.

the database problem nobody talks about

Generic B2B databases have a dirty secret. They sell the same contacts to thousands of companies. That VP of Sales you're emailing? They got 47 other cold emails this week from your competitors, all using the same database.

The data backs this up. When we audit client campaigns, we consistently find 40-70% of contacts in mass-market databases have invalid emails, outdated job titles, or have changed companies entirely. You're paying to email people who don't exist anymore or can't receive your message.

But the bigger problem is saturation. Even when the data is accurate, these contacts are exhausted. They've been hit so many times they've gone blind to outbound entirely.

why this matters more in 2026

With Google's new AI Inbox filtering emails by importance, engagement history matters more than ever. If someone's inbox is flooded with cold emails, yours gets buried with the rest. The AI sees patterns. Low engagement from a contact means your email gets deprioritized, even if your infrastructure is perfect.

You're not just competing for attention. You're competing for inbox real estate against an AI that's learned this person ignores cold email.

what actually works

Companies getting meetings in 2026 are building lists differently. They're identifying prospects with actual signals that they need the solution right now. Recent funding rounds. New executive hires. Product launches. Expansion announcements. Conference attendance.

These aren't demographic filters. They're behavioral signals that indicate timing and need.

We built custom data processes specifically for this. Instead of pulling "all SaaS companies with 50-200 employees," we find companies that just raised Series B and are hiring their first revenue operations person. Instead of "all healthcare VPs," we target people who just spoke at industry conferences about the exact problem we solve.

The difference in response rates is massive. Generic database lists get us 0.5-1% replies. Signal-based custom lists get 5-8% replies. Same messaging, different prospects.

the real question

Before you write another email, ask yourself this: is your list actually unique, or are you emailing the same burned-out prospects as everyone else?

If you're using a database that anyone can buy, you already know the answer.

Talk soon,

KP

P.S. If your reply rates dropped and you're not sure if it's your list or your messaging, let's look at it together. I'll show you exactly where the problem is and how signal-based targeting could change your results. Book a strategy call here.