lightweight_mmm
pymc-marketing
| lightweight_mmm | pymc-marketing | |
|---|---|---|
| 5 | 2 | |
| 797 | 535 | |
| 4.6% | 8.8% | |
| 5.5 | 9.3 | |
| about 2 months ago | 3 days ago | |
| Python | Python | |
| Apache License 2.0 | Apache License 2.0 |
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lightweight_mmm
- Lightweight (Bayesian) Marketing Mix Modeling (Google Unofficial)
- Show HN: Marketing software for solopreneurs who don't like marketing
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Mixed Marketing Modeling Approach for attribution?
Other packages to consider are LightweightMMM (from Google), which takes a Bayesian approach and is in Python (vs. R for Robyn). It's not as fully featured as Robyn (you don't get all the nice one-pagers and graphs output so easily), but it's still a great option, especially if you have some data scientists on the team who understand MMM.
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Is Hierarchical Bayesian Modelling used in industry?
LightweightMMM - python package
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Two More Years
Interestingly, Google did introduce an MMM framework: LightweightMMM 🦇 is a lightweight Bayesian Marketing Mix Modeling (MMM) library that allows users to easily train MMMs and obtain channel attribution information. https://github.com/google/lightweight_mmm
pymc-marketing
What are some alternatives?
Robyn - Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is to democratise modeling knowledge, inspire the industry through innovation, reduce human bias in the modeling process & build a strong open source marketing science community.
advertools - advertools - online marketing productivity and analysis tools
mta - Multi-Touch Attribution
keras - Deep Learning for humans [Moved to: https://github.com/keras-team/keras]
trimmed_match - This Python library implements Trimmed Match for analyzing randomized paired geo experiments and also implements Trimmed Match Design for designing randomized paired geo experiments.
statsmodels - Statsmodels: statistical modeling and econometrics in Python
GeoexperimentsResearch - An open-source implementation of the geo experiment analysis methodology developed at Google. Disclaimer: This is not an official Google product.
matched_markets - Matched Markets is a Python library for design and analysis of Geo experiments using Matched Markets and Time Based Regression.