Why Download?

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Intro: Get a practical framework for structuring experiment metrics so your team can actually trust every result.

✅ The four metric buckets — primary, secondary, guardrail, and learning — clearly defined
✅ The specific technique for catching cross-vertical cannibalization before you ship
✅ A worked example walking through a real scenario, metric by metric
✅ A one-line decision rule for aligning your whole team on ship/no-ship calls
✅ What to do when you can't run a clean A/B test

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Why this matters

Most experimentation programs don't fail because they lack ideas: they fail because a "win" on one team's dashboard can quietly be a loss somewhere else in the business. The teams that scale experimentation aren't the ones running the most tests. They're the ones who've built the discipline to trust every result, even as more people across the org start shipping tests of their own. This framework is one piece of that discipline — the kind of practice that turns individual tests into a program that compounds.

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This playbook is built directly from a live conversation: not just a summary of it.

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Watch the full session: 5 Lessons Learned from 1000s of Experiments: Guest Speaker Dr. Simon Jackson (Cherto)
→YOUTUBE LINK HERE

Bucketing your metrics is one piece. See the whole picture.

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Adasight's Experimentation Gap Analysis is a free, structured look across the four places programs typically get stuck — data, insights, practice, and AI.
→ [See the four gaps]

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Who is this for?

• Product & Growth — Growth and product leads who want a repeatable way to structure experiment metrics before every test
• Analysts & Data — Analysts and data scientists who need a clear framework for separating decision metrics from exploratory ones
• CRO & Marketing — CRO and marketing teams running tests across multiple product lines or verticals who need to catch cannibalization early

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