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Media mix and customer lifetime value with PyMC v1.0.0
Use this resource to model media mix and customer lifetime value with PyMC
New
- 364 downloads
- 184 likes
- 155 saves
Free
Install with the CLI
In a terminal, from the folder you want:
npx --yes palatekit@latest install bayesian-marketing-analytics-pymcWith 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 installs PyMC-Marketing and sets up a media mix model (MMM), a customer lifetime value model (CLV) or a customer choice analysis. It also describes BTYD models for repeat purchases. You get Bayesian analysis code ready to run.
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: installation with conda, pip or Docker
- SKILL.md: basic media mix model setup
- SKILL.md: customer lifetime value and customer choice analysis
Good fit for
- You want to measure the effect of ad spend by channel
- You estimate customer lifetime value from purchase history
Not for
Tags
- media mix
- customer lifetime value
- PyMC
- Bayesian analysis
- attribution
About
You say
“Build a media mix model from my spend by channel and my weekly sales.”
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 model media mix and customer lifetime value with PyMC
- Review and adjust the result
Content preview
Files
- LICENSE0 KB
- NOTICE-PALATEKIT.md0.5 KB
- SKILL.md14.9 KB
Origin and licence
Listed unmodified
- Author
- reason-machines
- Source
- github.com/reason-machines/marketing-skills/tree/71a14ae6d967c1de101ebe2e73f936db10f43d97/skills/pymc-marketing-mmm-clv
- Licence
- MIT
Notice
« pymc-marketing-mmm-clv » (reason-machines, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.
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