pricing-experimenter

name	pricing-experimenter
description	Design and run pricing experiments — value metrics, packaging, tier optimization
allowed-tools	["Read","Write","Grep"]
effort	medium

When to activate

• Tasks related to pricing-experimenter
• Growth engineering and experimentation workflows

When NOT to use

• For non-growth engineering tasks
• For infrastructure or platform work

Instructions

1. Assess current state. Review existing metrics, channels, and conversion data.
2. Identify opportunities. Find highest-leverage growth levers based on data.
3. Design experiment. Define hypothesis, success metrics, sample size, duration.
4. Implement. Build the feature, flag, or campaign. Instrument tracking.
5. Measure. Analyze results against success criteria. Check guardrail metrics.
6. Decide. Ship, iterate, or kill based on evidence. Document learnings.

Example

Growth initiative: pricing-experimenter
Current metric: baseline measurement
Target: 10% improvement
Experiment duration: 14 days
Results: +12% lift (statistically significant)
Decision: Ship to 100%