Hey everyone, I've been deep-diving into Helicone for monitoring our OpenAI API usage, and one feature that's been a game-changer for our analytics is tagging requests by user ID. It lets you slice and dice performance, cost, and usage data by actual users, not just API keys.
Without this, you're flying blind when trying to answer key questions:
* Which user segments are driving the most token costs?
* Is latency spiking for specific users or regions?
* What does the typical request pattern look like for a high-value vs. a trial user?
Setting it up is straightforward. You just need to add a custom property in the request header. Here's how we implemented it in our Node.js service:
`headers: {
"Helicone-Property-UserID": "user_12345",
"Authorization": "Bearer YOUR_OPENAI_API_KEY"
}`
The real power comes when you hop into the Helicone dashboard. You can immediately filter logs by a specific UserID, set up alerts for abnormal error rates per user, and even track cost attribution. We've coupled this with our internal lead scores to see that our enterprise-tier users generate more complex (and expensive) queries, which justified adjusting our pricing tiers.
Anyone else tagging requests with custom properties? I'm curious if you've found other Helicone property keys particularly useful for marketing ops analysis. Cheers, Henry
Cheers, Henry
Totally agree on tagging being a game-changer. We've used a similar approach to connect OpenAI usage directly to our CRM's account and contact records.
A small caveat we ran into: if you're using a serverless setup with connection pooling, just watch out for header propagation. We had to make sure our middleware was passing the `Helicone-Property-AccountID` through every async hop.
But once we sorted that, the ability to filter by account in the dashboard was magic. Instantly showed us which free-tier accounts were burning through prompts with high complexity, which helped us redesign our onboarding flow 😅
> instantly showed us which free-tier accounts were burning through prompts with high complexity
So you discovered that free users are the ones costing you money. Groundbreaking.
Look, tagging headers is fine for quick debugging. But calling this a data pipeline is a stretch. You're relying on an HTTP header making it through a chain of async handlers in a serverless function. One middleware update, one misconfigured proxy, and your "magic" dashboard is showing you garbage.
If you really want to analyze user behavior vs. cost, dump the raw request logs into a proper warehouse. Join on user ID from your CRM there. Then you can actually run SQL to find out which free accounts are abusing the system, not just stare at a dashboard that breaks the moment someone forgets to pass a header.
SQL is enough