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Media mix pipeline: adstock, saturation and budget v1.0.0
Use this resource to estimate each advertising channel's contribution to sales
New
- 328 downloads
- 138 likes
- 101 saves
Free
Install with the CLI
In a terminal, from the folder you want:
npx --yes palatekit@latest install mmm-adstock-saturation-budgetWith no option, the skill goes to ~/.agents/skills/; add --agent claude-code (or codex, cursor…) to target an agent.
First time: connect the CLI with
npx --yes palatekit@latest loginThe agent applies geometric adstock and Hill saturation to spend, fits an OLS regression, then optimises the budget split to maximise revenue. You get channel contributions and a proposed allocation.
Mostly picked by
Updated November 2, 2026
Previews
Details
- Install guides
- Generates with
- Your agent's model
- Licence
- MIT
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What you get
- SKILL.md: Python environment setup and project structure
- SKILL.md: adstock and saturation transformations
- SKILL.md: regression, usage example and budget optimisation
Good fit for
- You want to know which channel delivers the most
- You split a budget across TV, search and social
Not for
Tags
- media mix
- adstock
- regression
- budget
- Python
About
You say
“Estimate TV and search contributions to my sales, with 60% carryover on TV.”
Skill published by reason-machines under the MIT license, delivered in its original version.
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How to use it
- Install the skill in your agent's skills folder
- Ask your agent to estimate each advertising channel's contribution to sales
- Review and adjust the result
Content preview
Files
- LICENSE0 KB
- NOTICE-PALATEKIT.md0.5 KB
- SKILL.md16.5 KB
Origin and licence
Listed unmodified
- Author
- reason-machines
- Source
- github.com/reason-machines/marketing-skills/tree/71a14ae6d967c1de101ebe2e73f936db10f43d97/skills/marketing-mix-modeling-pipeline
- Licence
- MIT
Notice
« marketing-mix-modeling-pipeline » (reason-machines, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.
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