Case studiesEngagements on the record

Investigations, not testimonials.

Three engagements, written up the way they ran: what the client thought, what the numbers said, what moved. Every figure reconciles to the client’s own reporting. Names stay with the clients — some of this work sits under NDA.

  1. File 01
    A 77-year, $20M skincare brand

    The agency reported magical gains. The bank statement told a different story.

    Paid traffic converting at a third of the industry floor, and an agency whose numbers didn’t reconcile. We fixed what was leaking before adding a dollar more.

    0.97% → 2.73%Site conversion, same traffic3× → 9–14×Return on ad spend, same budget
  2. File 02
    A $30M creative agency

    from 5 days to 3 hours: rebuilding ad-variant production without new headcount.

    A full-service agency was spending five days turning one design into fifty placements — by hand. The fix wasn’t new software. It was seeing that the leverage lived in tools they already owned.

    5 days → 3 hrsTime to produce 50 placements−97%Production time cut
  3. File 03
    A $100M, 60-year engineering consultancy

    Seven cascading problems. One question nobody had asked.

    A $3–5M software business had grown almost by accident inside a 60-year consultancy and was straining under its own weight. The problem wasn’t the code. It was a decision no one had made.

    15+Diagnostic interviews5 → 1Competing visions → one owner
On the record

Every client here is anonymised on purpose. The $100M engagement stays nameless at the client’s request, so it stays that way here. The numbers are real; the names are theirs to give, not mine.

The first deliverable in every engagement is the truth about the numbers. If a reported figure doesn’t reconcile to the bank, that’s the first finding — before anything gets optimised.

The control case

The three files above are diagnoses. This is what happens when the levers they name are actually pulled.

In 2026 PerformLine, a marketing-compliance platform for banks and fintechs, needed a product that didn’t exist yet: monitoring what AI assistants tell consumers about their clients’ financial products. I was engaged as fractional product lead, a few hours a week. Not to build it — their own engineers and designers did that — but to own the decisions.

One accountable owner. One product, no parallel bets. One external hire; everyone else already on payroll. Sales in client conversations from the first week, not the last. AI Response Monitor went from build start to public launch in under 70 days — 4 May 2026, on the public record.

It’s the same machinery as File 03 — eight products, five visions, no one who could greenlight — run in the right direction. The capacity was already in the building. What it moved fast on was ownership and clarity, and those are the cheapest things to add.

If growth is stuck, let’s find out why.

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