Experimentation consultant.

An experimentation consultant helps companies build data-driven decision-making cultures through A/B testing, conversion optimization, and disciplined experimentation frameworks. I work with teams to establish experimentation infrastructure, design statistically rigorous tests, analyze results, and create processes that turn insights into action. This includes strategy, implementation, training, and ongoing optimization.

Experimentation consulting rates vary by engagement type. Hourly rates: £150–£250/hour (UK) or $175–$275/hour (US). Project-based: £8k–£25k for experimentation framework setup and initial programs, £25k–£70k for comprehensive transformation initiatives. Retainers: £3k–£10k/month for ongoing experimentation strategy and analysis. Pricing depends on scope, complexity, and whether you need strategy-only or full implementation.

Typical results include 15–35% conversion rate increases for well-executed experimentation programs. In my case studies: 18% trial-to-paid lift sustained over three quarters, 35% conversion increase for SaaS onboarding, and 27% faster experiment turnaround. Beyond metrics, you'll build a culture where data-driven decisions replace guesswork, leading to compounding wins over time.

Building an experimentation culture requires infrastructure, processes, and mindset shifts. I help teams: (1) Set up experimentation platforms and analytics, (2) Establish clear processes for hypothesis formation, test design, and results interpretation, (3) Train teams on statistical significance and best practices, (4) Create shared dashboards and regular review cadences, (5) Celebrate learning from both wins and losses. The goal is making experimentation a default way of working, not a special project.

A/B testing is a methodology for comparing two versions. Experimentation is the broader discipline that includes A/B testing, but also encompasses hypothesis formation, UX research, funnel analysis, strategic prioritization, statistical rigor, and building a culture of continuous learning. I use A/B testing as a tool within a comprehensive experimentation framework.

Initial setup and framework development: 2–3 weeks. First experiments: 4–6 weeks (including design, implementation, and reaching significance). Comprehensive programs: 3–6 months for multiple experiment cycles, infrastructure refinement, and culture building. Most engagements start with a 3-month pilot to establish baseline, prove value, and build momentum.