I help companies find the gap between what their customers say, what they actually need — and what they're willing to pay for. Then I build the positioning, GTM strategy, and systems to close that gap — and turn it into revenue growth.
I started my career in PR. And one of the first things I was told was that a PR specialist shouldn't touch the product — your job is to sell what exists, full stop.
That never sat right with me. I kept finding myself in conversations with customers who were telling me exactly what was missing, exactly what would make them stay, exactly what they'd pay for — and feeling like I had nowhere to take that information. So over time I moved toward product marketing, because that's where the two things I care about actually connect: understanding what the market genuinely needs, and building something that delivers it.
That combination — research, positioning, and measurable growth — is what I've been doing for 8+ years across EdTech, AI healthcare, HRTech, and B2B events.
One thing I've noticed about myself: I need to see the result. When I talk to customers, map their pain points, shape a product or a message around what I've heard — and then watch conversion rates climb, churn drop, or leads come in qualified rather than cold — that feedback loop is what drives me. It's also what keeps the work honest. Metrics don't lie about whether the positioning actually landed.
I use data and I use AI — to find patterns in customer interviews faster, to track what competitors are doing while I'm focused on something else, to stress-test hypotheses before I spend budget on them.
But I keep coming back to one thing that no model replaces: a real conversation with a real person. In an era where AI is generating more and more content and strategy, the companies that stay close to their people — customers and teams alike — will build things that feel human. And human things are what people keep paying for.
Before I write a strategy, I talk to people. The customer who already bought, the one who almost bought, the salesperson who hears objections every day. Their words go directly into positioning. Their unmet needs go directly into the product brief.
I track what moves the business — CAC, LTV, churn, conversion rate, pipeline contribution. These tell me whether what I built is actually working, and they give me a shared language with every stakeholder in the room.
Whether it's a partner acquisition framework, an automated qualification flow, or a community retention mechanic — I build for repeatability. A result that happened once is interesting. A result that keeps happening is a system.
I set kill criteria before a test starts. If a hypothesis isn't generating signal after a defined number of iterations, I move on. The goal is to find what works — which means actively discarding what doesn't, early.
Zero budget, no existing network, two weeks to conference day. These conditions have produced some of my best work, because they force prioritization down to what actually matters.
"Research is how I stop guessing. Metrics are how I know I stopped."
I work best in environments where I can get close to the customer and close to the product at the same time. I ask a lot of questions early — of customers, of salespeople, of the team — because that's where the real brief usually lives.
I move quickly and I like seeing results fast. I'm comfortable making decisions under uncertainty when the research gives me enough signal. And I'm good at aligning cross-functional teams around a shared direction — not through authority, but through clarity about what we're trying to achieve and why.
I'm also honest about what I don't know, and I'll tell you when a hypothesis needs more validation before we spend money on it.
Maria did a good job managing timelines and attracting new clients. She is very keen on what she is doing. She cares about tutors and students — she knows their pain, their problems.
Maria did what everyone in the market was afraid to do — she built the Externship program, and it took an unknown new product and made it a visible player in the market. It created a completely new USP.
Not as an occasional tool, but as infrastructure.
On the research side, it's changed what's possible. I can process interview transcripts and find patterns across dozens of conversations in the time it used to take to go through five. I can track competitor moves and market trends in parallel with everything else. Hypothesis testing is faster. Analysis that used to take days now takes hours.
On the operational side, I capture everything — notes, voice memos, stray thoughts — and use AI to surface what actually needs action. Nothing waits, nothing gets lost.
The one thing I'm careful about: AI is good at finding patterns in what people have said. It's less good at understanding why they said it, or what they meant underneath the words. That's still a human job. So my research always starts with AI and ends with a conversation.
Eight projects across EdTech, AI, events, and community. Each one started the same way — with a question I didn't yet have the answer to. Here's what happened next.
If you're working on positioning, GTM strategy, or community-led growth — or if you're not sure which of those is actually your problem — let's talk.