Tool

EDA Hypothesis Generator & Prioritizer

An interactive worksheet that captures observed data patterns, maps plausible causal mechanisms, lists required evidence, and helps teams prioritize testable hypotheses using consistent impact and feasibility scales. Submissions are saved to your backlog for experiment planning and follow-up.

Interactive Tool

EDA Hypothesis Generator & Prioritizer

Use this guided worksheet to turn signals from exploratory data analysis into prioritized, testable hypotheses. Fill each field clearly so experiments can be planned and handed off. The form captures the observation, a plausible causal mechanism, required evidence, relative impact and feasibility, and a recommended next step.

Quick example: Observed pattern: Mobile checkout conversion drops 20% on pages with >5s load time. Plausible mechanism: Slow page load increases abandonment. Required evidence: page load times by device, funnel conversion metrics, A/B test that speeds checkout. Estimated impact: ~$50k/month. Impact scale: 5. Feasibility: 4. Recommended next step: Run A/B test on optimized checkout. Owner: Product Lead. Target: 30 days.

Describe the pattern, anomaly, or correlation you observed. Include short examples or key metrics (e.g., conversion drops 20% on mobile checkout).
Optional: paste a short query, notebook link, chart ID, or sample numbers that illustrate the observation.
Explain one or two plausible mechanisms that could cause the observed pattern. These become the focus of your tests.
Who is affected and what outcome would change if this hypothesis is true? Be concrete about metrics or customer impacts.
Optional: estimate in a consistent unit (e.g., $/month or % conversion). Use the same unit across entries for comparability.
Rate expected strategic or financial impact on a 1–5 scale.
1.0 10.0
List the datasets, metrics, or experiments needed to confirm or refute the hypothesis (e.g., cohort funnel, page timing, A/B experiment).
What must be true for the mechanism to hold? What confounders or biases could mislead you?
Rate how easy it is to generate evidence or run a minimal test (data access, tooling, regulation, effort).
1.0 10.0
Rough effort to collect evidence or run a minimal test. Leave blank if unknown.
Suggested calculation: impact_scale × feasibility_scale. Enter the product or your preferred formula; higher means more urgent.
Choose the most useful immediate action to move this hypothesis forward.
Who will lead the test or evidence-gathering? Use a role if a name is unknown.
Target completion date (use YYYY-MM-DD or free text).
Any other context, links, or related hypotheses.
Yes saves this submission to your saved backlog for later review.
You can explore this tool now. Sign in or create an account to save your responses and return to them later.
Sign In to Save Create an Account
Make this tool part of your work

Save a personal copy, bring it to your team, or tailor the questions and workflow to fit what you are hungry to improve.

Member customization and team collaboration are coming soon.
Discuss Ask the Librarian

Discussion

Comments and conversation will live here.