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sibylhe avatar sibylhe commented on September 26, 2024

Hi Nick,

I'm thrilled to know you're creating a library based on this!

I'm not sure about the generability of my code. It was created for this dataset, and will yield only a baseline model. In practice, MMM is very versatile, a couple of things need to be customized and tuned to fit a specific case.

  1. Variables. This model: sales ~ impressions, while someone prefers sales ~ spend (combine model2 and model3), someone has monthly data, etc.
  2. Priors. I used relatively strong priors for coefficients because I normalized the variables. If a user chooses not to normalize the variables, he may need to switch to weaker priors.
  3. Additive or multiplicative model structure.
  4. Adstock parameters need tuning. See #15 for details.

How far do you want to go, what's your plan? And let me know how I can help. I could work on it on weekends and in free time.

Sibyl

from mmm_stan.

sibylhe avatar sibylhe commented on September 26, 2024

Feel free to reopen if you have any updates.

from mmm_stan.

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