More signal, less noise.

I've spent my career in B2B sales from every side: the operations and research that feed a sales team, the customer success work that makes adoption stick, and the quota-carrying front line. Having worked all three sides is why I know where a team's hours actually go, and it's why colleagues came to me for help getting real results out of AI.

One thread runs through all of it. For much of that time my work has lived in and around analytics and market intelligence, supporting the research and data products that sales teams depend on at companies like S&P Global Market Intelligence. The tools keep changing. The job underneath them does not. A seller still has to walk into a room knowing more than the person across the table.

Signal Driven grew out of watching capable sales teams get buried under AI tools that added more noise than signal. The patient account research and the sharp competitive read, the work that actually wins deals, kept getting crowded out by fast output nobody quite trusted. I built it to set that right, helping teams turn AI into workflows they can rely on and keep building on as the tools change.

Inside the workshop, that experience becomes something a team can repeat: practical processes it can use right away, coached to fit the way it already sells. The three-session format reflects a lesson from my years in customer success. Adoption takes hold in the weeks after a session, so the sessions run one to two weeks apart and the team tests every workflow on live deals before anything is final. What breaks in the field becomes the next session's agenda, and a toolkit the team runs on its own is what the workshop is built to leave behind.

My market research training sharpens the research side of that work. Account research and competitive intelligence are where AI most often produces confident but shaky output, and where knowing how sound research gets built keeps the speed honest.