BTYDplus | BTYD | |
---|---|---|
2 | 1 | |
180 | 6 | |
- | - | |
2.8 | 2.6 | |
about 1 month ago | about 2 years ago | |
R | HTML | |
GNU General Public License v3.0 only | - |
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BTYDplus
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How often are Bayesian methods used in practice? If so where?
Certain flavors of BTYD CLV models are purely Bayesian - some examples can be found in this R Library
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Data Science and Marketing
CLV (R): BTYD and BTYDplus
BTYD
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Data Science and Marketing
CLV (R): BTYD and BTYDplus
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.
causalml - Uplift modeling and causal inference with machine learning algorithms
EconML - ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.