Curated library of real product experiments
Browse a structured repository of experiments run by real teams, with goals, designs, outcomes, and methodological commentary. Use it as case material for your product team or research.
Why Experiment?
Randomization Visualizer
Free Experiment Review
Experiment Library (preview)
Unlock the full dataset
One‑time purchase for the complete library, delivered as a clean, structured CSV.
- 63 experiments across SaaS, consumer, and marketplace products.
- CSV columns: experiment_id, title, product_name, sector, goal, experiment_type, primary_metric, design_summary, sample_size, outcome_summary, p_value, decision, methodology_notes, source, year, tags.
- Methodological commentary: threats to validity, design notes, and analysis hints.
- Ready for use in R, Python, SQL, or BI tools.
Want early access or a custom export? Email: jared@productscience.consulting
Research papers on online experiments
Curated bibliography of academic work on online experimentation, A/B testing, and related causal methods (2000–2025). It comes from a PRISMA-style systematic literature review and is separate from the product case-study library above. A sample of rows is embedded so the table works even when you open this file locally. On a live site the full list loads from the CSV, or you can download the file below.
If you use this dataset, please cite:
Return-Aware Platform Experimentation: New Directions for Research, 2025.
Authors: Jacqueline Doremus, Joel Persson, Brian St. Thomas, Carlos A. Flores, Sebastian Ankargren, Mårten Schultzberg, Kyle Kretschman.
Dataset available at: https://github.com/jopersson/online-experimentation-literature-review/
| Title | Year | Venue | Field | Micro | Macro | Database |
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How teams use this library
Product managers, data scientists, and researchers use this as a reference when planning new experiments, teaching methodology, or quantifying patterns across many tests.
Where do these experiments come from?
The library curates experiments from public case studies, talks, and research reports, then standardizes them into a consistent schema with added methodological notes.
Can I use this in teaching or training?
Yes. The commentary is designed to be used as case material for internal training, workshops, or university courses. You can slice the dataset by sector, goal, or method.
Will you add my experiments?
If you run a substantial experiment program and want anonymized entries included, reach out. Contributions can be credited and included in future dataset releases.