Accurate Statistics
Bayesian analysis with proper stopping rules. Know when you have enough data — no guessing, no premature calls.
Experiment OS
Run a proper experimentation programme
One system for research, hypotheses, experiments, analysis, and decisions. Everything connected, nothing lost.
Accurate Bayesian stats. Revenue modelling that holds up. Iteration chains that show what you learned. Set up in minutes, not weeks.
Built by Another Web is Possible. Battle-tested on real client work since 2025.
Built for in-house CRO teams
Your whole programme in one place
Most teams cobble together Airtable, spreadsheets, and a testing platform that was never meant to be a source of truth. It’s brittle, slow, and knowledge evaporates when someone leaves.
Experiment OS connects the whole workflow: research, hypotheses, experiments, analysis, and decisions. With iteration chains, revenue modelling, and learning that actually sticks around.
Complete workflow
Everything connects. Nothing gets lost.
Research feeds hypotheses. Hypotheses feed experiments. Experiments feed decisions. Decisions feed the next test. One system that keeps everything linked.
The Cycle
- ResearchCapture evidence and findings.
- HypothesesTurn insights into testable statements.
- ExperimentsRun clean tests with proper setup.
- AnalysisHonest, uncertainty-aware results.
- DecideRecord decisions and next steps.
Research to Results
Link findings to hypotheses to experiments. See the full story, not fragments across five tools.
Decisions That Stick
Capture what you shipped, why, and what you learned. Build iteration chains so learning compounds.
Revenue Modelling
Annualised projections with transparent factors. Numbers you can actually present to stakeholders.
Clear Recommendations
Probability to beat control, expected loss, credible intervals. Results you can explain and defend.
Built-in Guidance
Step-by-step help at each stage. New team members get up to speed without slowing everyone else down.
Privacy by Default
GDPR-minded. Minimal data collection. Work stays isolated by organisation with clear access control.
Stop paying more for less
Most in-house teams improvise their experimentation infrastructure from Airtable and spreadsheets. You’re paying more and getting less than purpose-built infrastructure.
| Solution | Annual cost | Setup time | Statistical analysis | Complete system |
|---|---|---|---|---|
| Experiment OS | £590 | Minutes | Yes | Yes |
| Airtable Team (10 users) | £1,777 | Weeks to build | No | No |
| Enterprise CRO platform | £50,000+ | Months | Yes | Yes |
Airtable Team costs $24/user/month. For 10 team members, that’s £1,777 annually just for experiment tracking - before analysis tools, platform integrations, or development time.
Experiment OS: £590/year for complete infrastructure. Save £1187 annually.
Software that makes the world better
10% of whatever you pay goes to causes that matter: digital rights, accessibility, open source, LGBTQ+ rights, and investigative journalism.
10% of whatever you pay
Not profit. Revenue. Every Standard subscription contributes 10% of whatever you pay to organisations working to make the web and the world better.
You choose where it goes
Pick which causes receive your contribution when you subscribe. See exactly where the money goes, transparently.
Frequently Asked Questions
What is experimentation programme management?
Programme management is the system for running your experimentation practice: research, hypotheses, experiments, analysis, and decisions. It’s not the tool that runs A/B tests; it’s the tool that tracks what you tested, why, what you learned, and what you did next.
How is Experiment OS different from enterprise CRO platforms?
Enterprise platforms cost tens of thousands annually and require consultants to implement. Experiment OS is purpose-built for in-house teams: affordable pricing, no implementation required, and features you’ll actually use daily.
Can I use my existing A/B testing platform?
Yes. Experiment OS works with any testing setup. Use your existing testing tool and manage everything else in Experiment OS.
What’s Bayesian analysis and why does it matter?
Bayesian statistical analysis shows probability and uncertainty honestly. Unlike frequentist methods, you can’t p-hack results or declare winners prematurely. You get clear recommendations based on actual confidence levels.
Is this suitable for agencies?
Experiment OS works for agencies, but it’s optimised for in-house teams running continuous programmes. Multi-client management features are on the roadmap.
Stop improvising. Start experimenting properly.
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