Bayesian statistics

This is Learning Vision Statistics, episode 168, recorded September 30, 2026.

Welcome to Learning Bayesian Statistics, a podcast about Bayesian inference, the methods, the projects, and the people who make it

possible.

I'm your host, Alex Andorra.

If you're interested in one-on-one mentorship, online courses, or statistical consulting, feel free to reach out and book a call at topmate.io slash alex underscore and Dora.

See you around, folks, and best patient wishes to you all.

Santiago Barreda, welcome to Learning Bayesian Statistics.

Thanks for having

So what we're doing is taking your historical financial information, your historical marketing activity data, so your impressions, your clicks, your GRPs for TV, marrying that up with our own intelligence.

So it's a Bayesian process where we start with our priors and then every data point, data signal is actually pushing and pulling those priors in the direction of the data.

And it's all being done algorithmically within the system with a click of a button, right? So as soon as data is getting in, you click a button, you have a measurement model.

So you're getting all of your historical ROIs and contributions.

A brand could come in and have a new measurement model every week to then make the next decision that feeds directly into the buying platform.

So it's completely automated and kind of drives the process directly from the data coming into the system.

You also have, I guess, your Bayesian network.

I think you call it the marketing elasticity engine that happens.