Who am I?
I’m Tom Vladeck. My work lies at the intersection of statistics, causal inference, and marketing. I’m a practitioner, not an academic; I rely on the work of academics and put their theory into practice as part of my work.
I started Gradient when I was getting my MBA at Wharton. We’re a team of seven across the US and Europe, and we do quantitative market research for brands and agencies. We find the consumer segments they should target, the prices they should charge, the ads that work best, and the features they should build next.
Michael Kaminsky and I started Recast after Gradient did a project with him while he was at Harry’s. We both recognized media mix modeling (MMM) as an under-innovated area in marketing science. It took about two years to develop a model that did everything we wanted it to, and now we’re adding clients at pace.
Why should you read this?
The main theme of my work is taking state-of-the-art statistics and applying them to real-world situations: real problems for real clients with real data — and real consequences.
The other theme of my work is that I get to put it to use for a lot of very different clients in very different situations; from working with Fortune 50 brands, to big 3 consulting firms, to startup DTC brands, to political campaigns.
The two together, I think, gives me a unique perspective on the vast landscape that is data science as applied to business.