Growth is not a hack. It's a designed system of experiments, learning loops, and iteration. D.GROW™ replaces gut-driven product decisions with a repeatable engine: define a hypothesis, test it, scale what wins, kill what doesn't.
Prioritize my experiments → See pricingMost teams build on gut instinct, stakeholder opinions, or whatever a competitor just shipped. Features launch to applause, then flatline. Nobody can say which release actually moved the number.
The gap between "doing stuff" and "growing" is a validation system. Without one, the loudest voice wins the roadmap and effort never compounds into learning.
Add your experiment ideas and score each on Impact, Confidence, and Ease (1-10). The tool computes the ICE score and ranks your backlog so you know what to test first.
ICE = (Impact + Confidence + Ease) / 3. Run the top tier first — it usually covers most of your upside. Tip: anchor "Confidence" to evidence, not optimism.
Start scoring ideas free. Upgrade when you're ready to run real experiments with rigor.
ICE scores each idea on Impact, Confidence, and Ease, then averages them. It's a fast, transparent way to rank a backlog so the highest-payback bets rise to the top instead of the loudest ones.
Start with the top two or three. As velocity grows, watch for tests colliding on the same surface — that contaminates data. A simple live-test calendar keeps the engine fast and clean.
Re-run it with one variable changed rather than abandoning it. Near-wins often become wins on the second iteration. Every result, win or loss, goes in the learning repository.