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A/B Testing & Experimentation

Experimentation
Program Design.

Running tests is not the same as having a program. I design experimentation systems that scale from zero to 100+ tests per year, with every result connected to revenue.

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What's Included

From ad-hoc tests
to a compounding system.

Experimentation Maturity Assessment

Evaluate your current testing practice across seven dimensions: culture, process, tooling, statistics, velocity, learning, and revenue connection.

PRISM Hypothesis Framework

A structured method for generating high-quality experiment hypotheses that start with user problems and end with revenue-connected metrics.

Statistical Methodology

Proper sample size calculations, sequential testing protocols, and guardrail metrics. No more declaring winners at 70% confidence.

Test Prioritization System

ICE scoring adapted for revenue impact. Every experiment ranked by expected incremental revenue, not subjective effort estimates.

Reporting & Learning Cadence

Weekly experiment reviews, monthly insight synthesis, and quarterly business reviews that compound organizational knowledge.

How It Works

Assess to sustain
in five phases.

01

Assess

Experimentation maturity audit across all seven dimensions. Identify gaps, quick wins, and the biggest structural blockers.

02

Design

Build the hypothesis framework, statistical methodology, prioritization model, and governance structure tailored to your organization.

03

Build

Implement the tooling, templates, and workflows. Set up the experiment backlog and first batch of revenue-connected tests.

04

Train

Hands-on workshops with your team. Hypothesis writing, statistical interpretation, and experiment design until the framework is second nature.

05

Sustain

Ongoing advisory to maintain velocity, refine methodology, and scale the program as your team grows in capability and ambition.

Program Results

From scattered tests
to a revenue engine.

Program Velocity

Scaled an enterprise program from roughly 20 ad-hoc tests to 100+ revenue-connected experiments per year.

The PRISM framework eliminated low-quality hypotheses and focused the team on experiments with measurable revenue potential from day one.

Methodology

Replaced gut-feel prioritization with a structured framework that increased experiment win rate by a significant margin.

Sequential testing protocols, proper sample size calculations, and guardrail metrics eliminated the false positive problem that plagues most testing programs.

Common Questions

Program design,
answered.

We already run some A/B tests. Do we need a full program design?

Running tests and having a program are different things. A program means you have a hypothesis framework, statistical methodology, prioritization system, and a learning repository that compounds. Most teams run tests. Very few build programs.

What is the PRISM hypothesis framework?

PRISM stands for Problem, Research, Insight, Solution, Metric. It forces every experiment to start with a user problem and end with a revenue-connected metric. It eliminates the most common failure mode: running tests without knowing what you are trying to learn.

How long does it take to build an experimentation program?

The framework and first experiments are live within 3-4 weeks. Full program maturity with 100+ tests per year velocity typically takes 6-9 months, depending on team size and organizational readiness.

Do you work with our existing tools and team?

Yes. I am tool-agnostic and work with whatever experimentation platform you already use. The program design wraps around your existing stack and team. The goal is to make your people faster, not to replace them.

Start Here

Ready to build a real
experimentation program?

Start with an advisory retainer. We will assess your current maturity, design the program, and have your first experiments live within weeks.

Start an Advisory Retainer →
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