Visual representation of experimentation infrastructure strength and capability

Experiment tracking and CRO workflow, done properly

One system for the whole experimentation workflow. Research, hypotheses, experiments, decisions. Have a look around.

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No credit card. No “book a demo to see a price”. Just have a go.

Signature features

The bits that are properly “us”

The three things we've actually named.

The Cycle
The workflow we use end-to-end. Not “agile vibes” - an actual, repeatable loop that keeps research, decisions, and learning connected.
See The Cycle
The Iteration Chain
Follow-ups linked so you can see how a programme evolves.
See the chain
Revenue modelling
Conservative annualisation with transparent factors. Clarity without the nonsense.
See how we model it

The Cycle

A workflow you can actually stick to

The Cycle keeps research, decisions, and learning connected.

ResearchCapture evidence and findings.
HypothesesTurn insights into testable statements.
ExperimentsRun clean tests with proper setup.
AnalysisHonest, uncertainty-aware results.
DecideRecord decisions and next steps.

Honest stats, not victory laps
Bayesian outputs with uncertainty shown. Less “we peaked at day 3”, more “we can defend this”.
Decisions don’t vanish into Slack
Capture what you shipped (or didn’t), why, and what you learned - so the next test isn’t guesswork.

Research Management
Heatmaps in one tool. Session recordings in another. Survey results in a spreadsheet someone made in 2019. User interview notes in... actually, where are those? We give you one place for all of it, linked to the hypotheses it supports.
- Heatmaps, recordings, surveys, interviews - all in one place
- Link findings directly to hypotheses
- Evidence URLs so you can prove it later
- Tagging that actually works
Hypothesis Development
You know that spreadsheet with 200 test ideas? The one nobody's touched since Q2? We built something better. Structure your hypotheses properly, score them honestly, and track them from "good idea" through to "we actually tested it".
- "If X, then Y, because Z" format (no hand-waving)
- PIG scoring: Potential, Insight, Graft
- Research links so you can explain why
- Status tracking from backlog to proven
Design Generation
Getting from "we should test this" to "here's what it looks like" usually involves three meetings and a Figma request. Or you could just... generate it. Accessible, on-brand mockups from your hypotheses. AI does the grunt work, you do the thinking.
- Learns your brand style
- WCAG 2.2 AA by default (not an afterthought)
- Multiple variations per hypothesis
- Approval workflow before anything goes live
Experiment Management
We're not trying to replace your testing platform. We're just giving you somewhere sensible to track what's running, what finished, and what the results actually mean. A/B, MVT, whatever - keep it all in one place.
- A/B and multivariate test support
- Traffic allocation you can actually see
- Minimum runtime so you don't peek too early
- Connect to your existing tools
Statistical Analysis
Most platforms show you a green arrow and confetti after three days. We don't, because that's how you ship losers and call them winners. Bayesian analysis with proper stopping rules. Probability to beat control, not meaningless p-values. Expected loss so you know what you're risking. We tell you when you have enough data. Not before.
- Probability to beat control (plain English)
- Credible intervals you can explain to stakeholders
- Expected loss calculations
- Recommendations that respect uncertainty
Decisions & Learning Capture
The experiment finished. Now what? Most teams just... move on. Then six months later someone asks "didn't we test that?" and nobody knows. Capture what you decided, why, and what you learned. Future you will be grateful.
- Launch, iterate, investigate, or stop - pick one
- Write down why (you'll forget otherwise)
- Optional revenue impact at decision time
- One-click follow-up creation
Revenue Modelling
Ah, the classic CRO slide: "This test will make £2.4M annually." Really? Says who? We help you build defensible projections with conservative adjustments, transparent factors, and confidence ranges. Numbers you can actually present without crossing your fingers.
- Annualised projections with evidence-based adjustments
- Transparent factors (no black-box maths)
- Confidence ranges because certainty is a lie
- Works with your actual revenue data
The Iteration Chain
Good programmes iterate. Bad ones just run random tests and hope. The Iteration Chain links experiments together: what you tried, what you learned, what you did next. So when someone asks "why are we testing this?", you can show them the receipts.
- Parent to child experiment linking
- Full chain view at decision time
- One-click follow-up creation
- Audit trail for "why this test exists"
Guidance & Training
Not everyone on your team has run 500 experiments. That's fine - we built the good habits in. Stage-by-stage guidance, common pitfalls to avoid, and prompts that help junior team members learn without slowing everyone else down.
- Training hub with stage progression
- Contextual guidance at each workflow step
- Checklists and pitfall warnings
- Helps teams build consistent practice
Team Collaboration
Invite your team. Give them the right access. Know who changed what. It's not complicated, but it's surprising how many tools make it complicated. We didn't.
- Up to 10 team members
- Role-based permissions
- Organisation-level access
- Works for agencies and in-house teams
Platform Integrations
Keep your testing platform. Seriously, we don't care which one you use. We're not trying to replace it - we're just giving you a proper place to manage the programme around it.
- Works with any testing platform
- Manual entry when you need it
- Results tracking in one place
- Platform-agnostic by design
Privacy & Compliance
GDPR compliant because it's the right thing to do, not because it's a marketing checkbox. We collect what we need, nothing more. Your data stays yours. We don't sell it, we don't mine it, we don't get weird about it.
- Data isolation per organisation
- Minimal data collection
- EU data residency
- Audit logging for accountability

What you're probably using now vs this

Comparison between Experiment OS and an improvised stack of Airtable plus spreadsheets.
Feature	ExperimentOS	Airtable + Spreadsheets
Research to hypothesis linking	Included	Manual
Bayesian statistical analysis	Included	Build yourself
Platform integrations	Included	API work required
Knowledge retention	Included	Lost when people leave
Setup time	Minutes	Weeks

Why bother?

You could keep using Airtable for tracking, spreadsheets for analysis, and hoping someone remembers what you learned last quarter. Or you could use a system that was actually designed for this.

Everything connected

Research feeds hypotheses. Hypotheses feed experiments. Experiments feed decisions. Decisions feed the next test. No broken links.

Knowledge that sticks around

When Sarah leaves for that agency job, your programme doesn't leave with her. It's all in here.

Stats you can trust

Bayesian analysis with uncertainty shown. Tell stakeholders the truth, not a flattering fiction.

Works with your tools

We don't care what testing platform you use. Just connect it and get on with your life.

All features included in the Standard plan at £59/month. No hidden tiers. See why we built this and how we use it at Another Web is Possible.

In-product snapshots

See the workflow in practice

These are real screens, not concept mockups. Each one maps to a step in the experimentation cycle.

AI design prompts
Generate on-brand variations with clear brief instructions.
AI design variations
Multiple design directions ready for review.
Hypothesis summaries
Concise rationale and scoring in one view.
Revenue modelling overview
Evidence-led projections with conservative adjustments.
Training guidance
Stage-by-stage coaching for better experimentation habits.