Practical frameworks and hard-won perspective from 30 years inside B2B SaaS post-sale organizations.
Eight posts on why most B2B SaaS companies can’t prove their GTM AI is actually working, and what it costs to keep operating on faith instead of evidence.
Sales, Marketing, and CS aren’t just scoring the same account differently. Half the time, they’re not counting the same account at all.
Read article →Three AI tools can each reach a defensible decision about the same account in the same week, and still add up to a customer who thinks you don’t have your act together.
You can’t govern, measure, or prove the ROI of an AI tool you don’t know is running, and most GTM leaders can’t produce a full list of what’s already live.
If you’re still budgeting for AI experimentation and can’t show what it returned, you’re not early. You’re behind.
Exit-ready CS isn’t a maturity score. It’s whether someone outside the company can explain a save or a churn using only what’s written down — the question that closes the series.
Same revenue. Different operating maturity. Three moments — a forecast, a save, and a dependency — that separate a CS org running on instinct from one that will hold up in diligence.
NRR above 100% isn’t one story — it’s at least three, and only one of them is the growth story a board assumes it’s seeing. The diagnostic that tells them apart, and the one question that surfaces each.
Having the function isn’t the same as having the model. Here’s the one question that separates a relationship-oriented CS team from an outcome-oriented one — and why it matters before the divergence shows up in your numbers.
Reactive CS and proactive CS can produce identical GRR numbers for 18 months. Then they don’t. Here’s what each model looks like from the CEO’s chair.
PE boards watch GRR and NRR. Almost none of them ask how those numbers are being held. That gap is where risk hides — and where the exit story gets complicated.
GRR improved by 20 points and the board celebrated. Nobody asked how they got there. What purchased inertia actually costs — on one account, over two years.
GRR went from 65% to 85% and everyone exhaled. But stable metrics can mask a broken model. The fix that moves the number isn’t always the fix that builds the business.
For twenty years I opened every CSM JD the same way. The philosophy was right. Everything underneath it wasn’t.
Most CS organizations are caught between two wrong models. Both are wrong. Both fail. Here’s what the right model actually looks like.
When CS leaders push their teams toward commercial conversations, they lose the one thing that actually drives revenue. Trust.
The outputs have never looked better. The judgment gaps have never been harder to see. What AI actually changed about CS — and what it exposed.
We built Customer Success around the wrong definition of success. The three-link chain — business pain, solution value, outcomes achieved — is how we fix it.
Usage data tells you what happened. Business intelligence tells you what matters. The framework that separates strategic partners from account babysitters.
Even today’s overworked PCP has disciplines most CSMs don’t. A framework for proactive customer health monitoring — and how AI makes it possible at scale.
Advocacy is reactive by nature. The CSMs delivering real retention and expansion aren’t advocates — they’re strategic partners.