point to GH discussions (#944)

Co-authored-by: Juan Orduz <[email protected]>

docs/source/guide/benefits/why_open_source.md

@@ -18,7 +18,7 @@ There are pro’s and con’s of running your marketing analytics [in-house](htt
 Open source software is often at the forefront of innovation in data science, with new tools and techniques being developed and shared by the community. By building your data science stack on an open source core, you can stay up-to-date with the latest advances in the field and take advantage of new developments and improvements as they arise.
 
 ## Community support
-The Bayesian core of PyMC-Marketing (i.e. PyMC) is supported by a large and active community of developers, who contribute to its development and provide support and guidance to users. For example the [PyMC Discouse](https://discourse.pymc.io) is a very active place where users of PyMC can ask questions and get feedback from peers, core developers, and [PyMC Labs](https://www.pymc-labs.io) members. This can be invaluable for businesses that don't have the resources to hire their own team of data scientists.
+PyMC-Marketing and [PyMC](https://www.pymc.io/) (the Bayesian engine that powers PyMC-Marketing) are supported by a large, active community of developers who contribute to the development of these libraries and provide support and guidance to users. For example the [the PyMC-Marketing Discussions on Github](https://github.com/pymc-labs/pymc-marketing/discussions) allows members of our community to connect with and ask questions of peers, core developers, and members of [PyMC Labs](https://www.pymc-labs.io).  The [PyMC Discouse](https://discourse.pymc.io) is a similar forum for users of PyMC (the engine that powers PyMC-Marketing). This thriving community can be invaluable for businesses that don't have the resources to hire their own team of data scientists.
 
 ## Talent acquisition and onboarding
 Using open source software as a foundation for your data science stack can help attract top talent to your company. Developers and data scientists are often drawn to companies that use cutting-edge tools and contribute to the larger open source community.