Expose optimization of media transformations for alternative priors specification

[wd60622]

The media transformation are defined in pytensor could be leveraged in a function optimization in order to get parameters from more intuitive statements. For instance,

"At (scaled) spend of 1, I will have a contribution of 0.25"

saturation = LogisticSaturation()

# Some lam and beta values
most_likely_parameters = saturation.desired_output_at_value(spend=1, desired_output=0.25)

I think something like this could be possible

What do marketer intuition tend to look like?

[sonriks6]

This is exactly what I need!

[wd60622]

This is exactly what I need!

Hi @sonriks6
Thanks for the feedback. Are there any other media spend spends that resonate well that might be missing?

[sonriks6]

Yes, we look at the ROI level expected regarding the net revenue and the media driven sales, which by default are estimated to contribute 25% (that's the marketers intuition)