Testing Business Ideas & Voice of Customer

Systems to align teams, reduce uncertainty, and make better product decisions

Overview

A connected system for making assumptions explicit, focusing research where it matters, and building a continuous learning engine.

Sector:

Enterprise SaaS
Healthcare data
Product organizations
Startups

The Challenge

Product teams rarely lack ideas. They lack a shared way to decide which ideas are worth pursuing — and which assumptions need to be tested before committing resources.

In this engagement, a product organization was moving quickly from ideation into discovery, but without a common framework for evaluating risk. Research was happening, but inconsistently — often focused on what was easy to validate rather than what was critical. Insights weren’t carried forward. Teams entered each new initiative without knowing what evidence already existed, what risks remained, or what success actually required.

The result: duplicated effort, slow decisions, and low confidence in go/no-go calls.

The Work

Tools & Craft:

Figma
Strategic frameworks
Research repository design
VOC hub
Concept testing
Journey mapping
Workshop facilitation

Making assumptions explicit

The work started with a single orienting question: What would need to be true for this idea to work? Teams mapped hypotheses across three dimensions - desirability (does anyone want this?), feasibility (can we actually build it?), and viability (does it work as a business?) - and then ranked them by importance and evidence. This immediately surfaced the highest-risk, least-understood areas and redirected research away from safe, low-value validation.

Connecting research to decisions

Each high-risk assumption became a structured test with a clear hypothesis, defined method, and success criteria. Research stopped being a general activity and became a targeted, decision-linked practice. Teams knew before they started what they were trying to learn and what they'd do with the answer.

Building a continuous learning system

To make this sustainable, I established a Voice of Customer infrastructure: a Product Advisory Council for ongoing customer engagement, structured concept testing and usability sessions, and a centralized research repository so insights accumulated rather than disappeared. Feedback loops combined qualitative and quantitative signals - and critically, were tied to decisions, not just documentation.

Outcomes

A shared hypothesis framework adopted across product teams - reducing time spent on low-confidence ideas and focusing discovery on what actually mattered
A Product Advisory Council established as an ongoing customer engagement channel, providing a steady stream of real-world signal throughout development
A centralized research repository that made prior learning accessible and reusable, eliminating duplicated discovery work
Measurably improved confidence in go/no-go decisions, with teams reporting clearer alignment before moving into build

Key Insight

The bottleneck wasn't research - it was the absence of a shared framework for deciding what to research and why.

When teams make their assumptions explicit and connect them to a system of continuous learning, they stop debating opinions and start acting on evidence.