Every analytics engagement I take starts the same way: not "which platform," but "what decision is this supposed to inform." Get that wrong and the most sophisticated implementation in the world just produces expensive noise.
Here's what that looks like across the industries I've spent the most time in.
Healthcare data comes with a floor most industries don't have to think about. Every tag, every event, every data layer decision has to survive a HIPAA review before it earns the right to tell you anything useful. I build analytics frameworks and tag governance with that constraint built in from day one, not bolted on after legal flags it. The result isn't just compliant reporting. It's a reporting framework that ties patient engagement metrics back to real organizational goals, so providers can track what's working without ever putting a patient's data somewhere it doesn't belong.


Financial services has its own version of the healthcare problem: regulators, auditors, and a customer journey that has to survive scrutiny at every step. I've modernized data ecosystems for institutions where Adobe Analytics and Tealium had to work together instead of getting layered on top of each other, and led platform migrations where losing historical data wasn't an option. The goal was never just visibility into the customer journey. It was visibility that would hold up when someone with a compliance checklist came asking questions.
For a mission-driven organization, bad data doesn't just cost money. It costs impact. I worked with a major national nonprofit when 550-plus fragmented analytics properties meant nearly one in four online donations was invisible or wrong in reporting. Rebuilding that infrastructure with Tealium iQ, Tealium AudienceStream, Adobe Web SDK, and Adobe Customer Journey Analytics wasn't the interesting part. What mattered was what it unlocked: donation tracking variance dropped from 22% to 7%, and a single A/B test on the donation form lifted conversion 42.7% site-wide.


Automotive buyers move across dealership sites, manufacturer pages, and third-party listings before they ever talk to a salesperson, and most measurement setups only see one piece of that path. I've modernized digital ecosystems for dealerships and manufacturers, pairing Adobe Analytics and GA4 in a way that follows a buyer across that fragmented journey instead of losing them at the handoff. The point isn't more dashboards. It's knowing which touchpoint actually moved someone closer to a sale.
High-traffic eCommerce sites break analytics in a specific way: every new tag slows the page down, and every slow page costs conversions you'll never see in a report because the visitor already left. I've rebuilt analytics frameworks for high-traffic sites with that trade-off in mind, cutting tag deployment time while making the tracking underneath it more reliable, not less. Faster and more trustworthy aren't usually the same direction. Getting both is the actual work.


Entertainment audiences don't stay in one channel. Someone streams a trailer, buys a ticket on an app, and walks through a physical venue gate, and most measurement stacks treat those as three unrelated people. I've built cross-channel tracking that blends digital engagement with physical venue visits into one picture, so a brand can actually see the full path instead of guessing at the gaps. That's the difference between a report that describes what happened and one that tells you what to do next.

















