# Analytics In order to help us better understand how the community uses ZenML, the pip package reports anonymized usage statistics. You can always opt out by setting the `MLSTACKS_ANALYTICS_OPT_IN` environment variable to `False`: ```bash export MLSTACKS_ANALYTICS_OPT_IN=False ``` ## Why does MLStacks collect analytics? In addition to the community at large, MLStacks is created and maintained by a startup based in Munich, Germany called [ZenML GmbH](https://zenml.io/). We're a team of techies that love MLOps and want to build tools that fellow developers would love to use in their daily work. [This is us](https://zenml.io/company#CompanyTeam) if you want to put faces to the names! However, in order to improve MLStacks and understand how it is being used, we use analytics to have an overview of how it is used 'in the wild'. This not only helps us find bugs but also helps us prioritize features and commands that might be useful in future releases. If we did not have this information, all we really get is `pip` download statistics and chatting with people directly, which while being valuable, is not enough to seriously better the tool as a whole. ## How does MLStacks and ZenML collect these statistics? MLStacks uses [Segment](https://segment.com/) as the data aggregation library for all our analytics. The entire code is entirely visible and can be seen at [client.py](https://github.com/zenml-io/mlstacks/blob/main/src/mlstacks/analytics/client.py). None of the data sent can identify you individually but allows us to understand how MLStacks is being used holistically. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://mlstacks.zenml.io/reference/analytics.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.