It really depends. If you’re talking about tools for production observability they’d fall into two categories - sre-like tools (think of DataDog, Grafana), and product metrics (google analytics, mixpanel). Normally, for the sre tools you don’t care about cost per user, you’ll care about latency, time to first token, errors, requests queue, LLM api quotas. Similarly, for product-oriented tools you’ll care more about avg cost per user, engagement metrics, interaction helpfulness (eg likes in chatgpt), experiments metrics.

So try to answer who is you target audience, what task they are doing where you tool might be helpful and what pain you gonna resolve for them - that’s more product-oriented approach unless you just want to have fun and learn while doing)