Eliminating the Inverse of the Information Matrix

2min Snip

00:00

Play full episode

Summary

Transcript

Episode notes

mat gershof will write these and then say to me like, oh, this will be an easy one. Nothing like getting a slack from gersho saying, i'm going to kill you. So let me just eliminate c, because why the he not? Ye, let's do it. Let's eliminate c, so that i should dowat was u that linear something or other,. E optimality which minimizes the trace of the inverse of the information matrix. I've read that twice now, and still have no idea what has actually been describedso you two are smarter than me? No, i just took a shot in the dark. Yet, we're all pretty much

Hey there, mister. That's a mighty nice multi-touch attribution model you're using there. It would be a shame to see it get mixed up with a media model. Or... would it? What happens if you think about media mix models as a tool that can be combined with experimentation to responsibly measure the incrementality of your marketing (while also still finding a crust of bread in the corner for so-called "click attribution")? According to a 2019 paper published by ThirdLove (which happens to have been Michael's last call on our last episode), that's a pretty nice way to go, and we thought it would be fun to see if we could raise Tim's blood pressure by giving him something to vigorously agree with for once. It was. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.