Leadership

Stories, Hypotheses, and Metrics: Learning Every Day

Transform user stories into systematic learning experiments—using hypotheses, metrics, and structured funnels to validate assumptions and build products that grow with understanding

Into the Unknown

In July 2018, I took the BA Brazil stage in São Paulo with a simple but powerful challenge: how can we actually learn during product development?

Too often, teams write user stories, ship features, and move on—without validating the value delivered, the problem solved, or even if the user behavior matched what we imagined. In this keynote, I introduced a lightweight framework for continuous learning: combining stories, hypotheses, and metrics to make decisions in environments of uncertainty.

Stories are Just the Start

Everyone knows the classic user story format:

As a [persona], I want to [action], so that [value].

But even when stories look well-written, they are still assumptions. A story like:

As a user, I want to save articles to read later, so I can revisit them in the future.

…is not a guarantee of behavior. It’s a guess. That’s where hypotheses come in.

Hypotheses: From Guess to Systematic Experimentation

Every story can be turned into one or more hypotheses, mapping expected user behavior step-by-step:

  1. The user accesses the news portal.
  2. The user reads and likes an article.
  3. The user saves the article for later.
  4. The user comes back and reads it again.

We transform “desire” into a structured funnel, from initial interaction to the desired outcome. And crucially, we assign metrics to each stage.

This lets us move from intuition to learning.

Facilitating Hypotheses: How Teams Can Co-Create

We used pair-based facilitation dynamics inspired by Managing Dojo:

  • Brainstorming in pairs, with role rotation (pilot/copilot)
  • Everyone contributes
  • Emphasis on observation, not only solutioning

This format helped break silos, clarify assumptions, and ensure each voice was heard. Over time, this structure became our foundation for team-level discovery rituals.

Kanban for Learning

Just as we track stories through a delivery Kanban, we created a board for hypotheses:

TO DO → DOING → MEASURING → LEARNING

Each item is paired with:

  • A metric to watch
  • A feedback loop to close
  • A release strategy (MVP style)

This gave our iterations a dual purpose: shipping value and validating learning.

Measuring What Matters

Examples of metrics we used:

  • % of users who saved an article
  • Return rate to the saved articles page
  • Median time between save and revisit
  • Drop-off rates across the funnel

Not every metric led to an action. But every metric led to a conversation.

We stopped building features just to say we were done. We started building understanding.

The Emotional Side of Product

Products aren’t just functional. Our MVPs must also aim for:

  • Functionality
  • Reliability
  • Usability
  • Emotional design

Shipping fast doesn’t mean shipping ugly. The goal is to test value, not frustrate users.

Closing Message

“Don’t discard your ideas—yet.”

Everything is a hypothesis until proven. Every story is a bet. What makes great product teams stand out isn’t vision. It’s how quickly and effectively they learn.

Let’s stop assuming. Let’s start experimenting. Let’s build products that grow with our understanding.

Presented at BA Brazil 2018 – São Paulo. Follow me: @helmedeiros