A few problems I have been handed

Enterprise automotive · CDP, identity, lifecycle

A legacy CRM that could not prove its worth

Context. A global automotive manufacturer running an aging CRM with fragmented data and manual suppression. Plenty of activity, little defensible evidence that any of it moved sales.

What I did. Architected a unified customer-data ecosystem across first-, second-, and third-party sources with identity resolution, migrated the legacy platform to a modern cloud stack, and built the measurement framework the program is now governed by.

What changed. A several-fold return measured against control, tens of thousands of incremental sales year over year, and a shift from manual pulls to near-fully automated journeys, plus reporting executives could defend in a budget review instead of anecdote.

Enterprise · Measurement & attribution

Building numbers a CFO could not poke holes in

Context. A program rich in dashboards and poor in defensible attribution. Every result invited the same skeptical question, and the team did not have a good answer.

What I did. Stood up a measurement framework built on holdout controls, incrementality testing, and propensity deciles, and taught the team to lead with the method and volunteer the limitation before being asked.

What changed. Reporting that survived budget scrutiny, decisions made on incrementality instead of last-click, and a team that finally trusted its own numbers, which is its own kind of ROI.

Enterprise · MarTech architecture & vendor strategy

Ten million dollars of tools, and a question nobody could answer

Context. A large MarTech investment with real vendor sprawl, no single owner of the architecture, and leadership that could not name which channel drove the last hundred customers.

What I did. Took ownership of the stack architecture and the vendor portfolio, rationalized tools against the customer questions they were supposed to answer, and renegotiated the contracts that no longer earned their keep.

What changed. Meaningfully lower vendor cost, faster decisions, and a stack mapped to questions instead of logos.

Luxury automotive · Predictive analytics

Teaching a launch brand to see around corners

Context. A luxury launch brand with rich data and no predictive practice to make sense of it.

What I did. Built the models, propensity, in-market timing, and defection risk, and the identity matching underneath them, then wired the outputs into segmentation and suppression.

What changed. Double-digit conversion lift, lower opt-out rates through lifetime-value-informed suppression, and meaningfully faster campaign deployment.

Global medtech · Regulated B2B demand

A demand engine that had to clear compliance

Context. A medical-device business selling across B2B, B2B2C, and DTC in a regulated environment, with eight regional teams and no shared operating model.

What I did. Rebuilt the global demand framework with account-based scoring and marketing-to-sales routing, consolidated the customer journey across regions, and unified the brand voice.

What changed. A measurable rise in qualified traffic and pipeline contribution, a healthier marketing-to-sales handoff, and a seven-point NPS gain across regions.

Want the specifics?

The detailed versions live in conversation

I keep the full case studies, with the real numbers and methods, for interviews and direct conversations where the NDA context is clear. Email me.