Most marketing decisions rest on numbers that cannot carry them.
A conversion test that needs ninety-one conversions to detect a one point difference gets run on twelve. An attribution model reports a channel's contribution to two decimals from a sample that supports none of them. A content programme gets judged on traffic that turns out, on inspection, to be datacenter bots in a single country.
I do the arithmetic first and the work second. Over a decade in B2B demand generation, more than two thousand conversion tests, upwards of a thousand inbound campaigns, and one community that reached 245,000 people before I handed over the admin rights and found out what owned media actually means.
This is where I write it down.
What I write about
Marketing Economics
What marketing actually costs and what it actually returns. Test budgets, customer acquisition cost, attribution, and the statistics behind numbers that sound precise but are not.
4 piecesGo-to-Market
How a company decides who to sell to, what to say, and where to show up. Positioning, value propositions, owned channels, and the sequencing that separates a plan from a launch.
8 piecesSearch and AI Visibility
Being found, by people and by models. Intent research, information architecture, internal linking, and what changes when the answer is generated rather than listed.
4 piecesAI in Practice
What AI changes inside a marketing organization, judged by work that shipped. Operating models, the first projects worth doing, and the ones that look impressive and produce nothing.
4 piecesRecently updated
If you are building something where these questions decide the outcome, I am reachable.