Expertise
Same process, four different problems
Growth, retention, strategy, or AI — doesn't matter which one. I start the same way every time: learn the business first, then build from what's actually there.
Growth
Building the growth engine for what a company is becoming
Design an operating model that scales with the business instead of fighting it.
Where it applies
Companies past product-market fit, moving into their next stage of revenue.
The problem
Every stage has blind spots that are obvious in hindsight and invisible while you're in them.
How I work
Ten years of pattern-matching across companies to spot what's easy to miss from the inside.
The outcome
A growth engine built for the next stage — extending what already works instead of tearing it down.
Retention
The retention function that becomes the next growth engine
Retention systems built to double as an expansion revenue engine.
Where it applies
Companies that scaled acquisition faster than they built what happens after the sale.
The problem
Churn creeps in through the gaps, and the expansion revenue sitting in the existing customer base goes uncaptured.
How I work
Map where customers fall through, then build the infrastructure to catch them — built to scale, not duct tape.
The outcome
A retention function with a name attached to it — one that protects revenue and grows it.
Strategy
Know exactly where the next dollar of growth investment should go
Prioritize growth bets by ROI and time-to-impact, backed by data instead of whoever argues loudest.
Where it applies
Teams with more good ideas than budget or bandwidth to chase all of them.
The problem
Plenty of good initiatives competing for the same budget and the same quarter, and no shared read on which one actually moves revenue first.
How I work
Analyze across teams and build the roadmap together, not hand one down.
The outcome
A roadmap the team actually believes in, because they helped build it.
AI
Find where AI actually applies — then build it
Identify the highest-impact AI applications and build the actual production workflow, not a demo.
Where it applies
Anywhere from "we should probably do something with AI" to a workflow running in production.
The problem
Most of it is noise — attention and budget pulled toward the flashy, low-impact stuff while the application that would actually move the needle goes unbuilt.
How I work
Start with a conversation to find the real opportunity, then build the workflow by hand.
The outcome
A straight answer on whether AI actually helps here, and a working system if it does.
Start with the workflow that annoys you most.
Send your details and I'll get back to you.