# Initial release of PyMC-Marketing: Bayesian MMM and CLV modeling

**URL:** <https://discourse.pymc.io/t/initial-release-of-pymc-marketing-bayesian-mmm-and-clv-modeling/11829>\
**Category:** Announcements\
**Created:** [April 6, 2023, 12:31pm UTC](https://discourse.pymc.io/t/initial-release-of-pymc-marketing-bayesian-mmm-and-clv-modeling/11829 "2023-04-06T12:31:11Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![twiecki](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/twiecki/32/6930_2.png) [@twiecki](https://discourse.pymc.io/u/twiecki)\
**Post date:** [April 6, 2023, 12:31pm UTC](https://discourse.pymc.io/t/initial-release-of-pymc-marketing-bayesian-mmm-and-clv-modeling/11829/1 "2023-04-06T12:31:11Z")

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🚀 Ready to liftoff and take your marketing strategy to new heights?

📈 PyMC Labs has just released PyMC-Marketing, an open-source Python package for Bayesian Media Mix Models (MMM) and Customer Lifetime Value (CLV).

👉 This means that businesses can now optimize their marketing strategies and make data-driven decisions to increase their return on investment (ROI) in both the short term and the long term.

🤔 Why PyMC-Marketing?

💰 By using PyMC-Marketing’s Customer Lifetime Value (CLV) models, businesses can predict the future value of their customers and find opportunities to increase revenue and loyalty.

🐍 PyMC-Marketing is written in Python, making it easy to integrate with other data analysis and visualization tools for a comprehensive view of marketing performance.

🔓 PyMC-Marketing is open-source, allowing businesses to customize and extend the package to suit their specific needs and use cases.

💼 We partnered with industry experts to ensure it stays up-to-date with the latest marketing trends and it empowers in-house marketing teams to optimize their campaigns.

🤝 PyMC-Marketing is not just open-source, but also community-driven, which means anyone can use and contribute to it, making Bayesian marketing models more accessible and user-friendly than ever before.

🔧 PyMC-Marketing is reliable and accurate, thanks to its comprehensive suite of software tests and its foundation on PyMC, a widely-used and well-established Bayesian statistical modelling package.

✅ Whether you’re a seasoned marketing pro or just starting, PyMC-Marketing has something for you.

🙌 Join us on our journey to revolutionize Bayesian Marketing Models! With PyMC-Marketing, we’re making Media Mix and Customer Lifetime Value models more accessible and user-friendly for marketers everywhere.

📚 Want to learn more or get involved? Head over to the PyMC-Marketing GitHub repository or sign up for the PyMC Labs newsletter.

🌐 PyMC-Marketing announcement: [PyMC-Marketing: A Bayesian Approach to Marketing Data Science - PyMC Labs](https://www.pymc-labs.io/blog-posts/pymc-marketing-a-bayesian-approach-to-marketing-data-science/)

📈 Effective marketing is crucial for business success because it helps to attract and retain customers, increase brand awareness, and drive revenue growth.

🎥 Join us for our upcoming webinar on PyMC-Marketing to learn more and ask questions!

🗓 Save the date: 18th April 2023  
📝 Register now to secure your spot!

> **[\[Online\] PyMC-Marketing: Bayesian Approach to Marketing Data Science, Tue,...](https://www.meetup.com/pymc-labs-online-meetup/events/292111160/)**
>
> \## Event Description
> 
> PyMC-Marketing is an open source software project that offers a powerful set of tools for data scientists and senior decision makers in the marketing

GitHub: [GitHub - pymc-labs/pymc-marketing: Bayesian marketing toolbox in PyMC. Media Mix, CLV models and more.](https://github.com/pymc-labs/pymc-marketing)