"I try not to spend my time talking people into things."
Chuck Hill said this while explaining how he filters prospects for his AI business. It's the kind of statement that sounds obvious until you realize how few people actually do it.
Most business owners are trained to chase every lead. Close every deal. Never leave money on the table.
But the best operators I know spend as much time defining who they won't work with as who they will.
The Filtering Script
Chuck's approach to prospecting starts with a filter, not a pitch:
"Hey, this is Chuck. My records indicate you're actively growing your business still in 2026. Is that true?"
If the answer is no, the conversation ends. Not rudely—just efficiently. "No problem, maybe we'll connect another time."
If the answer is yes, he continues: "In a world where customers expect near-instant responses, I work with professionals who are willing to admit they occasionally miss opportunities. Not because they're bad at sales, but because time and availability aren't scalable. Does that sound relative to you?"
Notice what's happening. He's not pitching. He's filtering. He's asking the prospect to self-identify as someone with the problem he solves.
If they don't see the problem, he moves on. No convincing. No persuading. Just: "We've got 10,000 more people that look just like you. We'll talk to you next year."
The Cost of Convincing
Why walk away from someone who might buy?
Because people you talk into buying will talk themselves out of staying.
Chuck learned this selling newspaper subscriptions and website services. He could convince almost anyone to sign up. But the ones he had to convince? They cancelled. They disputed charges. They became problem customers.
"Instead of like $2,000 commission, it's like minus your chargeback, so you're down to 800."
The math isn't just about the immediate sale. It's about the lifetime value—and the lifetime cost—of each customer relationship.
A customer who clearly sees their problem and wants your solution will:
- Implement what you deliver
- Stick around long enough to see results
- Refer others like them
- Be low-maintenance to support
A customer you convinced will:
- Second-guess the purchase
- Blame you when results take time
- Cancel at the first friction point
- Drain your support resources
The first customer type builds your business. The second type erodes it.
Knowing Your "Not"
Most businesses define their ideal customer profile (ICP). Few define their anti-ICP with the same rigor.
Your anti-ICP isn't just "people who can't afford us" or "people outside our service area." Those are obvious filters. The harder filters are:
People who don't believe they have the problem you solve. If someone thinks their phone coverage is fine, you're not going to convince them to care about missed calls. Move on.
People who want to solve it themselves. Some prospects want to learn enough from you to DIY. They'll take your advice, ghost on the proposal, and implement a worse version themselves. Let them.
People who need to be managed. High-maintenance customers who require constant hand-holding, endless revisions, and emotional labor aren't worth 2x the price. They're often not worth any price.
People who are shopping on price alone. If the only thing that matters is cost, you're competing with everyone. The customer will leave as soon as someone undercuts you. Let them leave before they arrive.
The Emotional Difficulty
Walking away from a sale feels wrong. Especially when you're growing. Especially when you need the revenue.
Tom Marcy admitted this: "I try to get everybody. But I'm I've definitely figured that out now."
The instinct to close every deal is strong. It feels like leaving money on the table. It feels like giving up.
But consider what you're actually protecting:
- Your time to serve good customers well
- Your margin from customers who won't nickel-and-dime you
- Your energy from customers who won't drain it
- Your reputation from customers who won't damage it
Every bad-fit customer you take on has a cost. Some of that cost is visible (refunds, chargebacks, support time). Most of it is invisible (opportunity cost of not serving better customers, team morale, your own stress).
The Long Game
Chuck's filter-first approach isn't about being picky for ego. It's about building a sustainable business.
When you only work with customers who clearly need what you offer, several things happen:
Your close rate goes up. You're not wasting pitches on people who were never going to buy. Your "wins" to "conversations" ratio improves dramatically.
Your churn goes down. Customers who understood the value before buying are more likely to see the value after buying.
Your referrals improve. Good-fit customers refer other good-fit customers. They know people like them.
Your business gets easier. You're not constantly fighting fires with customers who shouldn't have signed up.
The Filter in Practice
If you want to implement this in your business, start by asking:
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What problem do we actually solve? Be specific. Not "we help businesses grow" but "we make sure service businesses never miss a lead call."
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What does someone look like who has this problem and knows it? What industry? What size? What behaviors indicate they're aware of and frustrated by this problem?
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What does someone look like who has this problem but doesn't know it? These people might become customers later, but they're not ready now. Don't waste time convincing them.
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What are the red flags that someone is a bad fit? Price shopping? Wanting extensive customization? Asking questions that suggest they don't trust the solution?
Build these into your sales process. Ask qualifying questions early. Make it easy for bad fits to self-select out.
And when someone doesn't pass the filter? Let them go. Gracefully, professionally, but completely.
You're not rejecting them. You're protecting them from a purchase they'd regret—and protecting yourself from a customer who'd drain you.
Know who your customer is. Know who your customer isn't. The second one might be more important.
Sources
References & Further Reading
- The Anti-Ideal Customer Profile — Framework for defining both ideal and anti-ideal customer profiles
- Customer Fit and Lifetime Value — Research on how customer fit impacts retention and lifetime value
- The True Cost of Bad-Fit Customers — Analysis of direct and indirect costs of serving wrong-fit customers