Granted we have a whole team supporting just that experimentation platform, but it's pretty cool. They even expose an MCP server for us to have agents do experiment analysis for us using.
Audience is decided by analytics tool -> Feature flag server maps audience to feature flag value -> Analytics tool tracks its events and includes feature flag value as attribute
Analytics is a much broader set of tooling. It can (and should) report similar things.
The main point of a FF system is that you have a runtime-controllable mapping from user attributes to feature flags, where a set of logic rules can dictate who is exposed to what feature. With most analytics-tool based rollouts, you would be able to only directly set an attribute and you then hard-wire that attribute to the feature toggle in app code, which gives you a lot less flexibility and always requires a engineer in the hot path when it comes to doing rollouts.
Besides checking if something is true or false what else is there to do ?
What else can it do aka "feedback loop" ?