At PingPong I owned the cross-border payments line end to end: $76M in year one, past $250M+ in year two, on funnels I built and ran across North America, Europe, and Southeast Asia.
When PingPong handed me the cross-border payments line, the number was revenue, and I treated every channel, workflow and tool as an input to it. Ten years across B2B fintech and SaaS, and I can still defend that number in a finance review line by line.
I chose an 8-tool GTM stack, Salesforce, HubSpot, Webflow, 6sense, Zapier, ZoomInfo, Salesloft and GA4 with Tag Manager, and governed it myself so no report depended on a vendor's version of the truth. I ran the funnels across North America, Europe, and Southeast Asia as one system with regional variants. And when the marketing org needed cover, I took over all of Marketing for 6+ months with no interruption to the business.
As VP of Marketing at ToLocal I ran a $10M annual media budget at 80%+ ROI while leading a team of 7. Since late 2025 I have shipped nine AI GTM tools solo, design through deploy, including CreativeOS for policy-aware ad copy and a fintech marketing compliance checker.
They answer different doubts, so they are grouped by kind rather than by date. The case studies show the number and the conditions it happened under. The systems show what I can build when the stack will not do it. The writing shows how I think when nobody is grading me.
Before I scale anything I make the number trustworthy. At PingPong that meant freezing spend increases for a quarter and rebuilding tracking myself until cost per qualified lead was a figure finance could audit line by line. It is an unpopular first move, because it looks like nothing is happening. The alternative is scaling on a number nobody will defend in the review that follows, and then losing the budget anyway.
A number finance will not defend is not a numberEvery quarter the number is capped by one thing. Once it was acquisition cost, with LinkedIn leads at $300+ each. Later it was a twelve-hour lead handoff bleeding intent while reps slept. I pick the one constraint, size what removing it is worth, and put the rest of the roadmap down. The discipline is in what gets ignored: a quarter spent improving three things at once usually moves none of them far enough to notice.
One constraint a quarter; the rest of the roadmap waitsI test campaign structure, audience, keyword and landing path on a fixed cadence, with the success metric written down before launch so the result cannot be reinterpreted afterwards. That run cut LinkedIn CPL to ~$160 and Google registration cost from $90+ to ~$35, with volume held on both. Holding volume is the part that matters. Efficiency bought by spending less is just arithmetic; the same leads at half the price is the result.
Efficiency with volume lost is just spending lessWhatever works, I wire into infrastructure so it keeps working without me. The 200+ workflows I built took over the routing, enrichment and alerting people used to do by hand, which is how lead handoff went from ~12 hours to 1–2 minutes. I automate only what has already proven itself, because automating an unproven play makes a bad decision repeat faster. If the machine needs me daily, I have not finished building it.
Automate only what has already earned itI rebuilt the acquisition layer from the tracking up and tested my way down the cost curve: LinkedIn cost per lead fell from $300+ to ~$160 and Google registration cost fell from $90+ to ~$35, with volume held on both channels. That efficiency is what let the line I owned scale from $2M to $76M in year one without the budget scaling with it.
Then I removed the human bottleneck. The 200+ workflows I built collapsed lead handoff from ~12 hours to 1–2 minutes, so the demand I paid for stopped going cold in an inbox. Sales owned the close; my part was getting a warm lead into their hands in minutes instead of the next morning. I measured the machine, found its slowest part, and replaced it.
CPL nearly halved · handoff ~12h → 1–2 min · line at $250M+ by year twoGive me the number. I will build the machine that hits it and show you the math.