Turning go-to-market strategy into real companies, real people, and real conversations.
Most marketers can build brand awareness, run ads, or create content. But when you need to directly reach decision-makers at specific companies with personalized outreach, that requires a different skill set: data engineering, research automation, and cold outbound execution.
I bridge the gap between "we want to sell to X type of company" and "here are 500 qualified contacts at those companies, with outreach messages ready to send."
You know who you want to sell to. You might even know what to say to them.
But you don't have:
This is where I come in.
We start with your ideal customer profile (ICP). Together, we clarify:
Using data tools like Clay, Prospeo, Apollo, and Apify, I:
For each qualified company, I:
Using AI and research automation, I:
Depending on your needs, I either:
Client needed a master list of all freight forwarding companies globally to fuel their sales pipeline.
Used AI validation, multi-step searches, and deduplication to build a clean list of 40,000+ verified freight forwarders.
Clients had thousands of companies in their CRM but no way to prioritize which ones to focus on.
Built scoring models that pulled in firmographic data, website traffic, funding history, employee trends, and founder LinkedIn activity.
Sales reps spent 2.5 hours manually researching each account before outreach.
Built an automated enrichment workflow that pulled company data, mapped job titles, matched case studies, and drafted personalized bilingual emails.
Open-source platform needed to engage technical decision-makers who were already using their technology.
Used developer activity signals (GitHub contributions, conference attendance) to segment 4,000 prospects. Personalized outreach based on actual behavior, not guesses.
Client helps startups shut down gracefully but had no way to identify which companies were closing.
Built a multi-signal scoring model using funding gaps, headcount decline, website inactivity, and founder LinkedIn changes.
I use automation and AI to do in hours what would take weeks manually.
I validate and cross-reference data across multiple sources. No more bounced emails or wrong contacts.
Every message feels tailored to the recipient because it is. I use real data, not templates.
You get clean spreadsheets, documented workflows, and full visibility. No black boxes.
My clients see reply rates of 5-16%, meeting conversion rates of 1-3%, and 80-90% reduction in manual work.
If this aligns with what Fulcro Insurance and Nave Bank need, let's schedule a kickoff call to: