About
Built around a belief.
There is always a further. We built Further Labs to help teams find it.
How we engage
Two paths.
One destination.
We work with brands in two different ways depending on where they are. The shape of the engagement changes; the goal doesn't.
Path 01
Embedded consulting.
You have a team. Maybe they're running experiments already, maybe they're just getting started. We work alongside them — sharpening the process, improving test quality, building the infrastructure — so that what they learn while we're there compounds long after we leave.
Good fit for
Teams with an existing CRO function who want to move faster, build better hypotheses, and get more from every test cycle.
Path 02
Full-service programme.
You don't have an experimentation team yet, or you need results while you're building one. We take full ownership of the programme — strategy, prioritisation, test design, execution, and reporting. We operate as your experimentation function until you're ready to run it yourself.
Good fit for
Brands starting from zero, or teams that need to move fast without adding headcount before they've proven the value.
Always the goal
We believe the highest long-term leverage for any brand is owning its experimentation capability internally — not outsourcing the thinking indefinitely. Every engagement is designed with a clear handover in mind: documented processes, a living learnings library, and a team that knows how to keep compounding without us. We measure our success partly by how little you need us eventually.
The team
A full roster, not a one-person show.
Every engagement draws from a core team of senior specialists. Strategy is led by Nils Koppelmann, who is your primary point of contact throughout. Execution is handled by a curated network of practitioners — the same people, engagement after engagement.
CRO Strategy
Hypothesis development, funnel analysis, test prioritisation, and programme architecture.
Test Development
Frontend implementation of experiments across platforms — clean, QA'd, and statistically sound.
UX & Design
Variant design, wireframing, and UX review grounded in behavioural research.
Data & Analytics
Statistical analysis, reporting, tracking setup, and insight synthesis across every test cycle.
Copywriting
Messaging and on-page copy for variants, informed by customer research and test learnings.
QA & Review
Cross-device, cross-browser quality assurance before every test goes live.
How it works
On embedded engagements, we supplement your existing team with whichever disciplines you need. On full-service programmes, we deploy the full roster — strategy, design, development, analytics, and QA — so you get a complete experimentation function without the overhead of building one from scratch.
AI & agents
Machine speed.
Human judgment.
AI agents handle the parts of experimentation work that are high-volume and mechanical. The team focuses on the parts that actually require judgment. The result is higher velocity without cutting corners on quality.
Hypothesis generation & scoring
Agents process session recordings, heatmaps, and analytics data to surface and score hypothesis candidates — in a fraction of the time manual analysis takes. The team reviews, challenges, and selects. Nothing goes to test without a human decision behind it.
Variant briefing & copy drafts
AI generates first-draft test briefs and copy variants based on the approved hypothesis. Designers and strategists refine from there. Starting from a structured draft instead of a blank page cuts briefing time significantly.
Results analysis & reporting
Automated statistical summaries, segment breakdowns, and natural-language result narratives are generated at test conclusion. No waiting for someone to compile a deck — results are ready to review and act on immediately.
Cross-test insight synthesis
As the learnings library grows, agents continuously scan for patterns across experiments — recurring winning themes, segment behaviours, copy signals — and surface them as inputs for the next hypothesis cycle. The programme gets smarter with every test.
The point
AI doesn't make the strategic calls — it makes the team faster at everything surrounding them. The goal is the same as it's always been: more tests, better hypotheses, faster learning. AI is how we get there without growing the headcount to match the ambition.
The Further Manifesto
Most growth teams plateau not because they run out of ideas, but because they run out of learning systems. Knowledge walks out the door, tests repeat themselves, and the organisation stops compounding.
We believe the cure is structure, not creativity. Systematic experimentation beats heroic campaigns. A good hypothesis framework beats a brilliant marketer. A learnings library beats a long memory.
There is always a further. The ceiling you're hitting today is an information problem. Every test you run is a step toward solving it.
"There is always a further."
What we value
Three principles
Evidence over opinion
Decisions grounded in data beat gut feel every time. We build systems that accumulate evidence, not teams that debate opinions.
Speed of learning
The companies that win aren't those with the best ideas. They're the ones that learn fastest. Velocity of learning is the durable competitive advantage.
Compounding growth
One experiment is a data point. A hundred experiments is a compounding machine. We build the infrastructure for the hundred, not just the one.