How to run your first growth experiment
Running your first growth experiment feels overwhelming, but it doesn't need to be. This guide walks you through the entire process from hypothesis to results, with practical examples you can copy.
In-depth guides on running experiments, picking metrics, and building a systematic growth practice. Written for solo founders and indie hackers.
Start running growth experiments today
Proven frameworks for prioritizing and organizing experiments
You have 20 experiment ideas and time for 3. ICE scoring helps you pick the right ones by rating each idea on Impact, Confidence, and Ease. Here's how to use it without overthinking.
AARRR (Acquisition, Activation, Retention, Revenue, Referral) gives you a map of your growth engine. Instead of guessing where to focus, you diagnose the weakest stage and fix it with targeted experiments.
Measure what matters and interpret results
You don't need a data scientist to measure experiment results. This guide shows you practical, good-enough approaches that work for small teams with simple tools like spreadsheets and basic analytics.
Your north star metric is the single number that best captures the value your product delivers. Pick the right one and it aligns everything you do. Pick the wrong one and you'll optimize for the wrong outcomes.
Activation rate is the percentage of new signups who experience your product's core value. It's the most impactful metric most startups ignore. Here's how to find yours and improve it systematically.
Build a systematic approach to growth
A/B tests are just one type of growth experiment, not the whole picture. Most startups overindex on A/B testing and miss bigger opportunities. Here's when each approach makes sense.
As a solo founder, you are your own growth team. This guide shows you how to build a sustainable experimentation practice that fits into your week without burning you out or taking over your roadmap.
Most experiments fail. That's not a bug in the process; it's a feature. Failed experiments teach you more than successful ones, but only if you know how to extract the lessons and decide what comes next.
Experiment velocity matters more than any single experiment. Founders who run 4-6 experiments per month learn 10x faster than those who run one per quarter. Here's how to find the right pace for your situation.
Golden Gecko gives you proven playbooks, AI-powered matching, and structured tracking so you always know what to test next.