Shipped. And still running.

One sale event for a specialty coffee brand, run end to end. The offer architecture, the budget curves and a revenue target for every single day were locked before it opened—then I operated the sale like a live system: actuals against target every morning, budget moved between offers and audiences while there was still sale left to matter, weak creative cut the day it flagged. Most sales get launched and then watched. This one was driven. It cleared $2m in sales and $1m of it was profit—and the mid-year sale for the same brand runs seven figures too, its strongest stretch averaging $126k a day for twenty straight days.

A roaster mid-rebuild. May 2025 closed at $1,775 in online revenue off 28 orders. May 2026 closed at $37,952 off 470 orders—a 21× year-on-year multiple with Meta, Google and Klaviyo run as one system. No single lucky sale carrying it: evergreen creative, signal-led budget moves, and the same daily read as every other brand on this page.

Same brand, different job: I treated the June sale and Black Friday as acquisition events rather than discount events—the offer, the creative and the budget all built around who we'd own after the sale, not just what we'd bank during it. Together they brought in 9,300 new customers, $500k of post-sale revenue from those cohorts, and a 10.6% conversion into coffee subscriptions from the June intake.

An EOFY sale for a 4WD gear brand, built as full-funnel architecture: offer structure across 70-plus creatives, budgets ramping on a curve set before launch, and a revenue target for every day of the sale. By lunchtime on day one the read said it was running hot—and because every offer and budget step was already sequenced, pushing harder meant feeding a sale that was already winning, with the extra spend landing on creative that had earned it. Day one closed at 185% of its revenue target.

The quiet week after Black Friday is where most brands quietly hand back their gains. A gourmet pantry brand banked $40k in the eight days after the sale ended—because the retention layer was built before the sale even started, so every discount buyer landed in a flow designed to bring them back at full price.

I tuned a content engine to the brand's own voice and had it rewrite the entire catalogue—titles, descriptions and metadata—with every page checked by a human before it shipped. 4,134 descriptions in one pass; work a copywriter would price in months, shipped in days. A comparable deployment correlated with a 37.5% revenue uplift on organic product pages.

A 600-plus SKU automotive catalogue where buying the wrong part means a return. I put an LLM intent layer over verified fitment data—the model parses what the customer's asking, but the part itself only ever comes from the verified data, so it answers like a counter salesman with twenty years behind him and it can't hallucinate a part number. Search turned into the highest-converting entry point on the whole site.

The in-house build that reads eight signals per brand every morning—spend, revenue, creative, email, tracking health—and hands down a verdict before 6am. It has run every brand on this page, every day, for the life of the engagement. It's also the reason one operator can carry 14+ brands without dropping any of them. I've documented the whole thing on its own page.

Elevar server-side installs across multiple ecommerce brands—including Hydrogen storefronts, where half the usual tracking assumptions break—plus a HubSpot-to-ads offline conversion sync for a lead-gen business. The upshot in every case: the ad platforms finally optimise toward sales that actually happened, instead of the fraction the browser managed to report.

I mined reviews, community groups and DMs into persona and messaging frameworks for a four-brand automotive portfolio, then validated every persona against 90 days of real order data—so they describe buyers who verifiably exist, with the receipts attached. That corpus now writes the creative briefs and powers an on-site answer layer too.