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In today's newsletter:
Latest Podcasts: What You Missed
Want to Scale? ICP: Do You Know Me? – If your business feels busy but not scalable, this episode shows how a fuzzy ICP quietly kills leverage, margins, and momentum and how dialing it in changes everything.
The 10 Money Skills Every Microteam Should Master - You’re great at what you do. But if the money side of your business feels confusing, stressful, or weirdly fragile, this episode is required listening.
What Can You Learn from 22 Microteam Success Stories? (…Plus 1) - Real microteams, real results, and the repeatable patterns behind outsized growth with tiny teams… and one notable failure.
Interview with Wade Foster, CEO of Zapier - How Zapier scaled with leverage, automation, and focus instead of hiring and organizational bloat.
Win/Loss Analysis: Learn From Everything
You just lost a deal. The prospect went cold. They chose a competitor. They said "not right now."
It stings. But here's the question most founders never ask:
Why?
Not "why me?" in a self-pitying way. But genuinely: What happened? What did we miss? What could we have done differently?
Most founders treat lost deals like bad dates: awkward, forgettable, best left in the past.
But here's the truth: Every lost deal is a goldmine of intelligence. And every won deal has lessons too.
That's what Win/Loss Analysis is. And if you're not doing it, you're flying blind.
The Founder Who Discovered His Product Wasn't the Problem
Let’s start with a fictional example here, but one that could easily be anyone you know. Marcus is a founder of a 5-person B2B SaaS selling workflow automation to law firms.
Marcus had a problem: His close rate was 22%.
For every 10 qualified demos, only 2 became customers.
Marcus assumed it was a pricing issue. So he lowered prices. Close rate stayed at 22%.
Then he assumed it was a features issue. So he added features. Close rate stayed at 22%.
Frustrated, Marcus decided to do something radical: He called the prospects who said no and asked them why.
He called 20 recent losses. 15 of them answered.
And what he learned shocked him.
The #1 reason they didn't buy? "We weren't confident you'd still be around in 2 years."
Not "too expensive." Not "missing features." Not "chose a competitor."
They liked the product. They liked Marcus. But they worried: Is this company stable?
Marcus's website had no customer logos. No case studies. No team photos. The "About Us" page was just Marcus's headshot and a vague bio.
To enterprise law firms spending $50K+ per year, Marcus looked like a risk.
"I thought being scrappy and lean was an advantage. Turns out, in enterprise sales, it's a red flag."
So Marcus made changes:
Added a "Customers" page with 12 logos (he asked existing clients for permission)
Wrote 3 detailed case studies with real results
Updated the "About" page to show the whole team (even though it was just 5 people)
Added a "Trust & Security" page outlining data protection measures
Result: Close rate jumped from 22% to 41% in 90 days.
Nothing about the product changed. Nothing about pricing changed. Just positioning.
And Marcus only learned this because he asked.
Why Win/Loss Analysis Matters (And Why Most Founders Skip It)
Here's the uncomfortable truth: You don't know why you win or lose deals.
You think you do. You have theories. But theories ≠ data.
Common founder assumptions:
"We lost because we're too expensive."
"We won because our product is better."
"They went with the competitor because of [feature we don't have]."
Maybe. But unless you ask, you're guessing.
And guessing leads to:
Building features nobody wants
Lowering prices when price isn't the issue
Doubling down on messaging that doesn't resonate
Win/Loss Analysis eliminates the guesswork.
It tells you:
What prospects actually care about (vs. what you think they care about)
Where your sales process breaks down
What objections keep coming up
Why customers choose you over competitors
What you're doing right (so you can do more of it)
Think of it like a coach reviewing game footage. You can't improve if you don't know what went wrong or what went right.
The Win/Loss Analysis Framework
Here's how to systematically learn from every deal: