Why SellerDragon exists

It started with a spreadsheet subscription that made me angry.

I run a seven-figure Amazon account. My P&L lives in Google Sheets, like every serious operator I know. So I paid for a connector that pulls Amazon data into sheets. It was slow. Then the vendor changed the sync cadence on the base plan – data I'd been getting fresh now arrived late, unless I paid more.

Delaying data you already have, to sell it back faster – that offended me as an engineer and as an operator. I've been building software since before the web existed. So I built my own pipeline: faster, into my own sheets, with a rule I've kept ever since.

Data is never delayed, on any plan. As we get it from Amazon, you see it.

Then the dashboard happened.

The pipeline solved the numbers. But I was still paying for a research suite whose market figures I'd stopped trusting, and doing the daily PPC work across eleven browser tabs. The data was already flowing through my own warehouse – so I built the cockpit on top of it. Daily overview, PPC workbench, dayparting, listing work. A dashboard where seeing the problem and fixing it happen on the same screen.

Then AI changed how I work.

I connected my account to Claude through MCP, mostly as an experiment. Managing campaigns by talking to an AI that sees your real numbers – ranks, spend, stranded inventory – and stages the changes for your approval is the biggest shift in how I work since the spreadsheet itself. That experiment became the third way in, with every write staged for approval: the AI proposes, you approve, then it ships.

That's the story.

There wasn't a grand product plan. SellerDragon grew out of the tools I needed to run a real Amazon account: reliable data in my own spreadsheets, a dashboard built for the daily pass, and AI that can analyze the whole account without losing context between systems.

– Christian Holmgreen
Founder, SellerDragon (Epium Ltd). MSc in Computer Science and AI, neural networks since the 90s, a seven-figure Amazon account today.