Your method for picking the metrics that show a product or feature is working
Quick Overview
A product manager analytics question on how to decide which metrics define success for a product or feature. It tests whether the candidate can connect goals and user value to a small set of precisely defined metrics, choose a primary metric suited to the product's stage, and add counter-metrics, targets and a review cadence.
Your method for picking the metrics that show a product or feature is working
Company: Amazon
Role: Product Manager
Category: Analytics & Experimentation
Difficulty: medium
Interview Round: Other
Explain how you go about deciding which metrics will show that a product or a feature is succeeding.
```hint Start before the metrics
Pin down what the product is supposed to change, for its users and for the business, before you name a single number.
```
### Clarifying Questions
- Should I describe a general method, or apply it to a specific product, either one I pick or one you name?
- Is the case a new launch, a feature inside an existing product, or a mature product line? The stage changes which part of the funnel matters most.
- Are these metrics for tracking health over time, for judging an experiment, or both?
### What a Strong Answer Covers
- How the goal and the value delivered to users and to the business are established before any metric is chosen
- A path from the user journey to a short list of candidate metrics, each defined precisely enough to compute
- Criteria for choosing the primary metric, and how the product's stage shapes that choice
- Supporting and counter-metrics that expose gaming or harm elsewhere
- How targets are set and how the metric set is reviewed and revised
### Follow-up Questions
- Your primary metric is rising while revenue is falling. How do you work out which signal to trust?
- How would you set metrics for a feature whose value only shows up months later?
- How do you keep a team from improving the metric at the user's expense?
Overview: A product manager analytics question on how to decide which metrics define success for a product or feature. It tests whether the candidate can connect goals and user value to a small set of precisely defined metrics, choose a primary metric suited to the product's stage, and add counter-metrics, targets and a review cadence.