Experimentation & CRO
We embed with your team to design, run, and scale A/B tests that move the metrics that matter — not vanity numbers.
Overview
Most growth teams don't have an idea problem — they have a learning-velocity problem. We work alongside your team to build a systematic experimentation programme: rigorous hypotheses, clean test execution, and a cadence that compounds learnings instead of losing them. AI handles the high-volume, mechanical work so the team can focus on the judgment calls that actually need a human.
Who it's for
- Growth teams with meaningful traffic who suspect they're leaving conversion on the table
- Companies spending heavily on acquisition who want more from the visitors they already have
- Teams running a few tests already, but without the cadence or structure to compound learnings
- Founders and CMOs who want experimentation to become a durable capability, not a one-off project
What's included
- Full funnel audit and opportunity mapping
- Hypothesis development and test design
- Test setup, QA, and statistical analysis
- Results interpretation and roadmap integration
- Team enablement and process documentation
How we work
- 01DiscoveryWe audit your funnel with quantitative data and qualitative research. AI agents process session recordings and behavioural data at scale — surfacing patterns and scoring friction points faster than manual analysis alone.
- 02HypothesisEvery test starts with a clear hypothesis tied to a specific user behaviour. AI assists with hypothesis generation and prioritisation scoring; the team makes every final call. No random changes.
- 03TestWe design variants, set up measurement, and run tests to statistical significance. Automated briefing and first-draft copy accelerate the build phase without cutting corners on quality or QA.
- 04ScaleWinning variants ship. AI synthesises learnings across the experiment history and feeds patterns back into the hypothesis backlog — so the programme gets smarter with every test cycle.
What you get
Funnel audit
A prioritised map of where your funnel leaks and where the biggest conversion upside sits.
Hypothesis backlog
A ranked, living queue of test ideas scored by expected impact and effort.
Live experiments
Designed, QA'd, statistically sound tests shipped on a predictable cadence.
Result readouts
Clear analysis of every test — what won, what didn't, and what it means for the roadmap.
Learnings library
A documented, searchable record of every experiment so insight compounds instead of evaporating.
Process & enablement
The framework, rituals, and documentation your team needs to keep the programme running.
FAQ
- How quickly will we see results?
- Most programmes ship their first experiments within two to three weeks. Meaningful, compounding results typically build over the first two to three months — experimentation rewards consistency, not one-off wins.
- Do we need a lot of traffic for this to work?
- You need enough traffic to reach statistical significance in a reasonable timeframe. We assess this up front — and if volume is tight, we focus on higher-leverage changes and longer test windows rather than chasing marginal tweaks.
- Do you replace our team or work with it?
- Either. We embed alongside an existing team to sharpen process and velocity, or run the full programme as your experimentation function. In both cases the goal is to leave you more capable than we found you.
- Which testing tools do you work with?
- We're tool-agnostic and work across the major experimentation platforms. If your stack needs work first, that's a separate engagement — see Experimentation Tooling Advisory & Implementation.
Ready to run better experiments?
Book a 30-minute call. No pitch deck, just a conversation.