How would you measure the success of our New AI Agents Launch?
OpenAI Product Metrics Interview Question: How would you measure the success of our new AI Agents launch?
Dear readers,
Thank you for being part of our growing community. Here’s what’s new this today,
OpenAI Product Metrics Interview Question: How would you measure the success of our new AI Agents launch?
Note: This post is for our Paid Subscribers, If you haven’t subscribed yet,
I’ll assume the Agents feature is a new AI-agent product (0 to 1 launch) whose primary objectives are to deliver real user value and build repeatable usage/trust (monetisation is a secondary goal). Below is a detailed, end-to-end measurement plan you can implement: goals, user journeys, the single North Star, full KPI set with definitions & formulas, instrumentation/events, dashboards & SQL, experiment ideas, targets/guardrails, rollout/monitoring, and qualitative research.
1) Clarify Scope & Assumptions
Scope: Measure success of Agents feature only (not whole product).
Primary goal: User value → adoption → retention / monetization path.
Audience: Existing users + early adopters.
Time horizons:
Launch health: Day 0–30
Early retention: Day 31–90
Growth/monetization: 90–180+ days
Assumptions: 0→1 launch, prioritized metrics: activation, successful completion, reuse, and quality (not revenue yet).
2) Goals
User Goal: Users can delegate meaningful tasks to agents and get reliable, useful outcomes with low friction.
Business Goal: Habit-forming usage that increases retention and creates avenues for monetization (upsell, usage pricing, enterprise adoption).
Success = not just trials, but trusted repeated usage.
3) Core User Journey
Flow and the critical behaviours to measure:
Discovery: User sees/learns about Agents (exposed)
Activation: User creates/enables an agent (activated)
First success: Agent completes a task that meets quality / success criteria (first_success)
Reuse: User reuses same agent or creates another (habit)
Outcome: User delegates real work (conversion to paying product or long-term retention)
Two business-critical behaviours:
Users run agents to successful completion (quality + outcome)
Users come back and reuse agents (habit)
