Build Faster With Shared Proof
Today we dive into the Community-Validated Growth Experiments Library—a living, peer-reviewed collection of growth ideas tested across diverse teams, industries, and stages. Explore experiments with transparent evidence, replication notes, and practical templates, so you can skip guesswork, reduce risk, and prioritize what actually moves metrics. Contribute your own learnings, compare contexts, and collaborate with peers determined to trade folklore for measurable, repeatable results.
Why Collective Evidence Accelerates Growth
Signals That Matter
Not all results deserve equal attention. Focus on uplift magnitude, variance, power, sample realism, and downstream quality impacts, not just top-of-funnel spikes. When evidence describes audience, channel saturation, and counterfactuals, you can generalize wisely, avoiding seductive outliers while honoring rare exceptions through careful replication designs.
From Anecdote to Reproducibility
Stories inspire, but reproducibility persuades. Move beyond motivational narratives by including pre-registered hypotheses, linked code, instrumentation screenshots, and raw conversion tables. When another team can rerun the steps and reach similar directional conclusions, confidence rises, politics quiet down, and resources flow toward ideas with verifiable leverage.
Avoiding Cargo-Cult Tactics
Copying tactics without context creates wasted effort and brittle systems. Evaluate constraints, staffing, seasonality, and user intent before borrowing. The library’s annotations emphasize when tactics failed, which segments resisted, and what enabling conditions mattered, helping you adapt principles thoughtfully instead of pasting superficial playbooks that unravel under pressure.
Designing Experiments People Can Trust
Trustworthy experiments begin long before implementation. Clear hypotheses, guardrail metrics, and pre-defined success thresholds reduce confirmation bias and prevent moving goalposts. Instrumentation must capture both primary outcomes and quality signals, while segmentation plans anticipate heterogeneous effects, documenting why some cohorts should be excluded, controlled, or specifically over-sampled.
Hypothesis Craftsmanship
Write falsifiable statements that connect user motivation, proposed change, and measurable behavior. Avoid mushy aspirations. Reference prior evidence from similar audiences, and clarify minimum detectable effects relevant to business value. When everyone understands the causal story upfront, implementation choices align, and the postmortem reads like science rather than persuasion.
Sample Size and Power, Demystified
Underpowered tests mislead; overpowered tests waste time. Use baseline rates, desired uplift, variance, and acceptable risk to calculate required exposure. Share the math openly, invite critique, and commit to honoring the plan. Transparent planning reduces cherry-picking and anchors decisions in probabilities instead of wishful interpretations.
Pre-registration and Transparency
Publish hypotheses, metrics, segments, and stopping rules before launch. Link dashboards and data dictionaries so reviewers follow your logic. When analysis choices are predetermined, surprises become discoveries rather than rationalizations, and your peers can replicate the sequence confidently, respecting both positive results and instructive nulls.
Evidence Tiers and Confidence Scores
Distinguish exploratory notes from validated patterns using tiered labels and numeric confidence intervals. Provide links to raw data where permissible, and document limitations candidly. As entries climb tiers through replications, prioritization models shift accordingly, enabling product leaders to justify bets with transparent, auditable rationale rather than charisma.
Replication Badges and Notes
Awards are not cosmetic. A replication badge summarizes who reproduced the result, in what environment, and with what deviations from the original plan. Detailed notes help teams anticipate pitfalls, port instrumentations, and avoid reinventing the initial mistakes that often undermine otherwise promising ideas.
B2B SaaS Onboarding Lift
A mid-market tool introduced task-based email nudges connected to in-app milestones. Power analysis set expectations before launch. Activation improved meaningfully, yet churn rose among rushed trials. A follow-up added pacing controls and help-center deep links, preserving activation gains while restoring retention through calmer, user-driven progression.
Marketplace Supply Activation
A marketplace seeded supply with a concierge onboarding squad, pairing checklists with weekly office hours. Early matches surged, but cancellations spiked when qualification slipped. Introducing a structured readiness score and staged exposure throttling maintained liquidity while protecting experience quality, demonstrating the compounding value of layered operational safeguards.
Submission Checklist That Saves Time
Before posting, confirm hypothesis clarity, metric definitions, power calculations, and segment justifications. Include screenshots or notebooks, and link to raw tables when possible. Tag context, stage, and audience precisely. Thorough submissions accelerate review, reduce back-and-forth, and maximize your chance of replication, acknowledgment, and lasting impact.
Ethics, Consent, and Guardrails
Respect users and colleagues. Obtain proper approvals, communicate risks, and uphold consent standards appropriate to your product and region. Guardrails should protect user experience, accessibility, and fairness while experiments run. Share how you enforced boundaries, proving that growth and integrity can reinforce each other rather than compete.
Tooling, Data, and Next Steps
Resources should remove friction, not add it. Use calculators for power, checklists for design, and templates for storytelling. Integrations ingest metrics while preserving lineage. Subscribe for updates, propose new categories, and join working sessions where we co-build utilities that translate curiosity into reliable growth momentum.
