Most API Product Managers go with the metrics collected by engineering.
But your Datadog dashboards alone won’t help you make informed product decisions.
Here’s what you should be tracking instead and why:
🙋 USER ENGAGEMENT ➡️ Adoption Rate (of feature) Q: I want to know who’s using my newly released API
➡️ Active Keys (D/W/MAU) Q: I want to understand overall growth
➡️ Retention Rate/Cohort Q: I want to see insights about how well my campaigns are performing
🚅 API PERFORMANCE ➡️ Latency (avg/max, P90/99) Q: I want to know if my API is slow, affecting my users’ experience
➡️ Error Rate (per minute) Q: Are errors above or below an acceptable threshold? Is there a problem?
➡️ Uptime (%) Q: Am I meeting my Service Level Agreement?
📈 BUSINESS IMPACT ➡️ Revenue Attribution/feature Q: How much revenue is each feature bringing?
➡️ Expansion Revenue/tier Q: Are we expanding more than we churn?
➡️ Vanity (absolute numbers - yes you should still track them) Q: Give me the number of Signups, API Calls, Subscriptions
🧑💻 DEVELOPER EXPERIENCE ➡️ Time to First Hello World (TTFHW) Q: How easy is it for prospects to understand our value?
➡️ Support Ticket Volume Q: Is our product hard to use?
➡️ Version/Feature Adoption Q: Are developers migrating quickly enough?
📊 You can also combine metrics to measure the effectiveness of a funnel:
- Number of visitors
- % and average time to sign up
- % and average time to TTFHW
- % and time to N API calls (where N signifies adoption)
- % and time to publish an app
- % and time to sign up for a paid plan
- % expanding
What metrics do you track as an API PM? Let me know in the comments on the original LinkedIn post.