I build the systems that find revenue — ingestion pipelines, performance analytics, forecast engines, and the tooling that acts on what they surface. Twenty years carrying the number is why they are built around the operator’s P&L.
Simpsonville, SC
How I work
The work is a loop, and I have run every stage of it. Instrument the revenue so the data exists at all — ingestion, schema, the joins nobody wants to own. Monitor it so movement is visible while it is still cheap to act on. Pinpoint what is underperforming and rank it by what it actually costs. Prove why, with a method that survives being argued with. Then build the thing that closes the gap, rather than filing a request for it. Everything on this site is a stage of that loop, built against a real operation while it was running.
What makes the analysis worth trusting is where it was done. These are not exercises on a public dataset. The recovery engine was rebuilt bottom-up after I caught my own first version overstating by 2.5× — sized off revenue rather than units × landed cost — before it ever reached a client. The forecast engine reports a distribution rather than a point, because a single confident number understates risk in both directions. The QBR dashboard applies Bayesian shrinkage because an account that activated one of two times is not a 50% account. Every one of those is a decision about honesty first and technique second.
The commercial record underneath it is the reason the models are built the way they are. Twenty years in B2B revenue: founding sales hire who built a commercial function from zero and led a team of six to quota, then a net-new channel revenue stream built from nothing, with millions in annual contract value sourced and closed across it and more than 80% of that self-sourced across my last three roles. That is not a separate career from this one. It is why the unit economics in every model here are the operator’s, why the forecasts get shown to people who have to commit to them, and why I know which number a business actually acts on.
What I want next is a seat where both halves count — revenue operations, performance and data analysis, or a commercial role with real ownership of the systems behind it. I have never needed a category to be handed to me before I could be useful in it, and the shelf below is the evidence: most of it is a domain I had to learn quickly, instrument, and then act in.
Career trace — live, from the work data
The top line is the commercial job and it never breaks. The bottom line is one dot per system on the shelf, read out of the same file that renders the work page. Pick a chapter.
Capability ledger
A skills list nobody can check is decoration. Commercial work is proven by the record; software is proven by something you can open, and those lines cite it. A claim of “shipped” that cites no Live or Built project is demoted in code, not by good intentions.
The stage of the loop that pays for the other four. Ranking a catalogue by margin contribution rather than revenue reorders it substantially, and an exposure spread across separate invoices is invisible until somebody aggregates it.
Not used in production
Graduate electrical engineering coursework, applied to battery state-of-charge algorithm development. Not implemented in anything on this site, and I would not claim it as production experience.
The instrument stage. A pipeline database wired into the company ERP so opportunity scoring and estimated ACV are computed rather than retyped — the first time a system I built was the system of record for someone else’s job.
Haiku for classification, Sonnet for editorial reasoning. Paying Sonnet rates for tagging is a design error, not a rounding error.
The Role Lens on the home page is the smallest example: the model may reorder and annotate, it may not assert a fact that is not already in lib/projects.ts.
Replacing a manual quarterly reporting cycle with a live view and a forward projection. A metric nobody watches between reviews drifts for eleven weeks and then gets explained rather than fixed.
Over 80% of closed revenue across my last three roles was self-sourced — not routed from marketing, not handed over by an SDR queue, not a purchased lead list. The systems cited here are the ones I built to do it at volume without adding headcount.
Evidenced by the record, not by a repo
Twenty years of it, most recently carrying a quarterly number for channel-sourced ACV — cold outbound through multi-stakeholder negotiation and co-sell close. Evidenced by the record below, not by a repo.
Evidenced by the record, not by a repo
Twice. Founding sales hire at an agency, then a net-new channel revenue stream at a commerce SaaS portfolio.
Evidenced by the record, not by a repo
Led a team of six to consistent quota attainment through structured coaching and call reviews, including the onboarding curriculum they ramped on.
Evidenced by the record, not by a repo
Built the hybrid retainer-plus-performance agency model and the exception path governing it; negotiated channel terms and performance expectations across three product lines.
Evidenced by the record, not by a repo
Joint end-customer opportunities worked alongside channel-side sellers across three product lines, with clear ownership where both sides sell into the same market.
Evidenced by the record, not by a repo
Sourced, listed, priced, and scaled my own catalogues with my own capital at risk. The operator experience underneath every model on this site.
Selected results
The commercial figures are carried by the role that produced them. The rest are read from the project that produced them rather than retyped — including the one where the finding was that my own first estimate was wrong.
From the roles
Twenty years · Seller Interactive · Voadera · Threecolts
Seller Interactive · Voadera · Threecolts
Seller Interactive
Seller Interactive · Threecolts
From the work
What I'm looking for
Being vague here wastes both of our time. If three of these four columns are wrong for your role, it is probably not the role.
Résumé
For anyone who wants to skim rather than click. This section is what prints — no PDF is checked in, because a PDF starts disagreeing with the site the first time either one is edited.
Amazon seller analytics and sourcing SaaS platform
Hybrid Amazon brand growth agency — founding sales hire
Amazon FBA wholesale and resale operator
Shipped, and on this site: Business Development CRM & Forecasting Engine
E-commerce SaaS portfolio — MarginPro, CedCommerce, Seller DirectoriesRemote — Simpsonville, SC
Shipped, and on this site: Sales ACV Forecast Engine · Amazon Recovery & Profitability Suite · QBR Dashboard & Revenue Ops Command Center · Weekly Growth Brief Engine · Channel Enablement Portal · Prospecting Command Center · Revenue Pipeline CRM · FBA Deal Analyzer Pro · 3T Recovery Wizard · Sales Enablement System
Acquisition holding company · e-commerce intelligence platformSimpsonville, SC
Shipped, and on this site: Marketplace Beta · Article & Topic Classifier · PriceScope · AgencyForecast · Universal Business Acquisition Analyzer · Acquisition Deal Pipeline & Target Database · Stellar Advisor Platform · LeadPrompter
Bachelor of Science, Business Management — August 2005
Clemson University, Clemson, SC
Graduate-level coursework, Electrical Engineering
Continued development — Battery state-of-charge algorithm development, with prerequisite coursework in electrical fundamentals and battery chemistry across consumer, power tool, and automotive cell types.
Applied acoustics — self-directed
Continued development — Frequency response and target-curve fitting, parametric equalisation, transducer and enclosure characteristics, and frequency-band gain as it relates to speech intelligibility.
Acquisition finance and SMB M&A
Continued development — ETA and SBA 7(a) structuring, financial statement and valuation analysis. Applied directly in BeaconPath Holdings’ screening engine.
If any of the above lines up with what you are hiring for, the fastest way to test it is to send me the job description — the Role Lens on the work page will reorder the whole shelf against it before we ever speak.