Experimentation
Program Design.
More experiments. Same evidence bar. I design experimentation systems that increase useful test velocity while every experiment is sized before launch, tied to a customer or revenue decision, and closed with a scale, stop, or learn call.
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 turning observed user problems into falsifiable hypotheses, revenue-linked metrics, and explicit decision rules.
Statistical Methodology
Sample-size planning, sequential testing protocols, and guardrail metrics that prevent an interim probability from being treated as a completed business decision.
Test Prioritization System
RICE scoring adapted for decision value. Reach, detectable effect, confidence, and delivery effort stay visible instead of collapsing into an unsupported revenue forecast.
Reporting & Learning Cadence
Weekly experiment reviews, monthly insight synthesis, and quarterly business reviews that compound organizational knowledge.
Assess to sustain
in five phases.
Assess
Experimentation maturity audit across all seven dimensions. Identify gaps, quick wins, and the biggest structural blockers.
Design
Build the hypothesis framework, statistical methodology, prioritization model, and governance structure tailored to your organization.
Build
Implement the tooling, templates, and workflows. Set up the experiment backlog and first batch of revenue-connected tests.
Train
Hands-on workshops with your team. Hypothesis writing, statistical interpretation, and experiment design until the framework is second nature.
Sustain
Ongoing advisory to maintain velocity, refine methodology, and scale the program as your team grows in capability and ambition.
From scattered tests
to a decision system.
Program Velocity
In historical in-house work at NRG, scaled annual experiment velocity from roughly 20 to 100+ while maintaining revenue measurement standards.
Intake and sizing gates required a falsifiable hypothesis, sufficient traffic, a revenue-linked metric, and an agreed decision rule before build work began.
Methodology
Replaced gut-feel prioritization with a transparent framework that made test feasibility, uncertainty, and delivery cost visible before launch.
Sample-size calculations, declared analysis protocols, and guardrail metrics reduce avoidable false-positive risk. They do not make an uncertain experiment certain.
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. A program adds shared hypothesis, statistical, prioritization, and repository standards.
What is the PRISM hypothesis framework?
PRISM stands for Probe, Revenue Rank, Implement, Score, and Multiply. It turns observed customer behavior into a falsifiable hypothesis, sizes the test against baseline data, and requires a scale, stop, or learn decision at readout. Behavioral frameworks guide the hypothesis; they do not guarantee a winning result.
How long does it take to build an experimentation program?
The build schedule depends on data access, instrumentation, team capacity, approval cycles, and traffic. The scope commits to controllable deliverables — the operating framework, measurement standards, powered backlog, governance, and team enablement — rather than guaranteeing a test count or business impact by a fixed date.
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.
Ready to build a real
experimentation program?
Start with an Audit + Activation Sprint, a proposal-only engagement from $12,500. The engagement is accountable for the agreed operating framework, measurement standards, powered backlog, and team cadence. Launch and readout dates are set only after access, implementation, and sample requirements are known.
Discuss an Audit + Activation Sprint →Revenue Frameworks
for Growth Leaders
Every week: one experiment, one framework, one insight to make your marketing more evidence-based and your revenue more predictable.
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