✅ Go/Kill Decisions: Make Data-Driven Calls

Track experiment results and decide whether to scale (Go), stop (Kill), or iterate (Adjust). Use clear thresholds to avoid emotional decisions.

📊 Your Decision Matrix

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How to use: After running experiments for 2 weeks, capture your results in the table below. Compare actual results to your targets and make a Go/Kill/Adjust decision using the framework

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Go/Kill Decision Tracker

🎯 Decision Framework

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GO (Scale it)

When: You hit 70%+ of your 2-week target

Action: Increase budget, time, or resources for this experiment

Example: Target was 5 demo calls, you got 7 → GO

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KILL (Stop it)

When: You hit <50% of your 2-week target

Action: Stop the experiment and try a different hypothesis

Example: Target was 100 website visits, you got 30 → KILL

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ADJUST (Iterate)

When: You hit 50-70% of your target

Action: Change one variable (message, audience, channel) and test again

Example: Target was 10 LinkedIn comments, you got 6 → ADJUST messaging and retest

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📝 Example Decisions

Hypothesis Metric Target (2 weeks) Result % of Target Decision
LinkedIn cold outreach to founders Demo calls booked 5 calls 7 calls 140% ✅ GO - scale outreach volume
Blog post on ICP pain point Organic traffic 100 visits 45 visits 45% ❌ KILL - try different topic or channel
Weekly newsletter with tips Open rate 30% open rate 18% open rate 60% 🔄 ADJUST - improve subject lines, retest

💭 Reflection Questions

After making decisions, answer these questions for your next sprint:

Document why this hypothesis outperformed. Can you apply the learning to other channels?