The dashboard says you're winning. Your bottom line disagrees.
Hey, I'm Corey. A fractional CRO and marketing analyst with 10+ years experience working with SMBs and international enterprise clients. People tend to bring me in when the numbers don't add up, the website isn't pulling its weight, or the out of the box reports aren't agreeing with your other tools.
What you get
Outcomes graded on the metrics that actually matter — passthrough conversion rate and revenue per product or feature impression. Leave the vanity metrics at the door.
Your GA4, Adobe Analytics, and other BI dashboards get a tune up, as self serve as you need them.
You'll know where your funnel is dropping off, how much it's costing you, and what to fix first — by segment, channel, and device.
Guardrail metrics, up-front MDEs, and protection against SRM so a conversion win doesn't quietly cost revenue. Winners are real winners, not p-hacked artifacts.
Rates, ratios and deltas that show how one metric pulls on another.
I play nicely with the whole org chart and speak fluent marketer, developer, data scientist, and CFO.
Dashboards your team will actually check. Tests they can run on their own. Playbooks they can hand to the next hire.
The Game Plan
Three phases. We start where the work is — usually at the foundation, but not always.
Rebuild trust with your data layer
- Web analytics, data layer and event tag audit
- Custom event parameters to track what matters to you
- BigQuery / Snowflake pipelines
Understand the full power of your funnel
- Conversion and checkout flow analyses by segment, device, and channel
- Step drop-off deltas with revenue impact, opportunities for improvement
- Do more of what works, less of what doesn't
Test to learn.
Test to confirm.
- Hypothesis design tied to real data signals
- Implementation in testing tool of your choice
- Performance analysis, roll out recommendations & honest post-mortems
Tools & stack fluency
Built for the stacks ecommerce and retail teams actually run on.
Writing
Field notes from the work. Occasional rather than scheduled.
Why I still measure UA-style bounce rate in 2026.
The Universal Analytics definition was crude on purpose, and that's exactly what made it useful for page-level work. Here's how to get it back.
Read the pieceGA4 didn't kill Page Value. It scaled it.
How I rebuilt Page Value in GA4 after the migration retired it, and how you can too with the tools you already have.
Read the pieceAbout Corey
Senior analyst, recovering Science Fair Kid.
I've spent 10+ years with e-commerce analytics teams and the agencies that support them — leading GA4 migrations, rebuilding broken testing programs, and translating data into decisions specialists and executives actually act on.
Previously Dr. Martens and Palo Alto Software. Speaker at Rightscon and BarCamp Philly. Occasional LinkedIn Philosopher on CRO experimentation in retail and SaaS DTC.
Based in Eugene, Oregon. Working remote with brands across the globe.
Common Questions
Both. Agencies often hire me as a fractional analytics lead for their clients (white-label or openly). Direct ecommerce brands also hire me as their analytics consultant. I'm flexible on how we structure it. White-label work, retainers, project-based — all are on the table.
Yes. That's often the first thing I do. Bad tracking, misconfigured events, data thresholding in GA4 — I audit it, find the breaks, and fix them. Then we build dashboards and run tests on clean data. This usually takes 2–4 weeks depending on complexity.
Analytics: GA4, Adobe Analytics, GTM, BigQuery, Snowflake, Looker Studio, Power BI. A/B testing: Convert, Optimizely, Monetate. CDP & CRM: Amperity, HubSpot, Salesforce. Commerce: Shopify, BigCommerce. I'm also hands-on enough in HTML, CSS, and JavaScript to get things done without handing everything off to a developer.
That depends on where you're starting from, which is exactly why establishing baselines matters first. Once we know what "normal" looks like, we can identify what's underperforming, prioritize the biggest opportunities, and measure the impact of every change. Results follow from that foundation — not the other way around.
An audit or single dashboard build is usually 2–4 weeks. An ongoing fractional analytics lead engagement is typically 3–6 months, renewable. Some clients scale back after we've built systems they can run themselves. Project-based, retainer, or hourly — all work depending on what you need.
Most likely. If you have a website that generates data and things you care about tracking, I can help. I've worked with international retail, national healthcare, SaaS startups, and small local businesses. The tools and rigor are the same — the metrics just change.
Based in Eugene, Oregon. I work remote for most clients — anywhere in North America and beyond. Local clients in Oregon can meet in person if useful. Slack, email, Zoom, and Google Meet work fine.
It's a pun. Frequentist and Bayesian are the two major schools of thought in statistics. Most A/B testing tools default to frequentist methods — which is why so many "winning" tests don't hold up in the real world. I lean Bayesian: more interested in updating my understanding based on evidence than declaring a winner at an arbitrary threshold. The name is a joke for the one person in the room who gets it; the philosophy is the whole point.
Ready to dig in? Let's do this.
Let's talk shop. Give me the lay of the land and we'll figure out what we can do together.