What happens next?

Post-experiment decisions determine whether insights drive action or collect dust. Clear frameworks help teams move from learning to implementation confidently. Every experiment leads to one of 3 decisions:

• Iteration means your core hypothesis has merit but needs refinement. Maybe users want the solution but at a different price point, or the feature works but needs better onboarding.
• Pivoting acknowledges your fundamental assumption was wrong. You're not tweaking details but changing direction entirely. Perhaps you discovered users don't have the problem you thought they did, or your solution creates more friction than value.
• Persevering means strong validation that justifies scaling up your investment and moving toward full implementation.

The key is setting decision thresholds before running experiments. Define what validation levels trigger each response. For example: "If less than 20% of users complete the core action, we pivot. Between 20-40%, we iterate. Above 40%, we persevere." Factor in both quantitative metrics and qualitative feedback. Strong numbers with confused users suggest iteration. Weak numbers but passionate user feedback might also warrant iteration rather than abandonment.

Document your reasoning alongside your decision. Future teams need to understand not just what you decided but why. Build checkpoints into your roadmap to revisit these decisions as you gather more data.