For analytics, a full-stack system has to include its own user interface, query engine, persistence and data ingest framework. That is, it has to include functionality for every service on the backend but also have the frontend user interface that makes it usable.
The key here is that good full-stack analytics solutions should be flexible enough to allow you to really get into answering questions with your data. You should be able to do more than just set a few parameters on a funnel, like some out-of-the-box solutions. You should be able to create the metrics you need easily within your analytics interface.
Full-stack analytics also need to be able to scale to your needs with ease. Any good full-stack solution should be able to handle however much data your product and users can throw at it. Having the capacity to scale is crucial for any full-stack solution.
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