Defining a Scalable Product Discovery Framework
Context & Challenge
This project was one of the key initiatives we drove to transform Adevinta Spain's culture towards a genuinely customer-centric one.
As the organization scaled, product teams began having fewer problems with delivery and more with deciding what to build next. Through team feedback, retrospectives and direct observation, a series of recurring patterns emerged:
- •Features misaligned with actual user needs
- •Teams focused on outputs rather than outcomes
- •Limited exploration of alternative solutions due to cognitive biases
- •Premature commitment to delivery with high levels of uncertainty
- •Resource waste on initiatives that didn't generate real value
- •Discovery work largely invisible within the organization
The challenge was to improve the quality of discovery and establish a shared way of working, valid for teams with different maturity levels, disciplines and business contexts, without adding friction or slowing down delivery.
My Role
As UX Director, I directly led this initiative from start to finish.
I was responsible for:
- •Framing the problem and defining the strategic scope
- •Creating and coordinating a cross-functional task force with Product, Design, Tech and Data leaders
- •Analyzing internal practices and conducting external benchmarking
- •Defining and co-creating the Product Discovery model
- •Designing the adoption, training and coaching strategy
- •Securing executive sponsorship
- •Tracking the rollout and impact through maturity assessments
What we did
Define our Product Discovery model
The first step was aligning on what Product Discovery meant at Adevinta.
We created a cross-functional task force that worked on three fronts in parallel:
- •Internal analysis: we studied how discovery was being done across different teams and domains, identifying effective practices, gaps and common patterns.
- •External research: we analyzed how other leading organizations structured their discovery work, reviewing frameworks, principles and operating models.
- •Synthesis and definition: combining both learnings, we designed our own model, adapted to our organizational reality and maturity levels.
The goal was not to copy an existing framework, but to create a pragmatic, actionable and scalable model that would help teams make better decisions in contexts of uncertainty.
The Product Discovery model
The model we defined started from a clear distinction between Product Discovery and Product Delivery.
For us, Product Discovery is the process through which teams explore opportunities, reduce uncertainty, define hypotheses and validate assumptions about what should be built. Product Delivery, on the other hand, focuses on implementing and validating solutions in production.
We adopted a Dual Track approach, understanding that discovery and delivery happen simultaneously and continuously. Both types of work coexist within the same sprints, applying the same lean and agile principles. Two tracks, but one team, responsible for both learning and execution.
Within discovery, we defined a model composed of four main phases, understood as a flexible framework, not a linear process:
- •Alignment & Opportunity Capture: team alignment on objectives (through OKRs) and systematic capture of opportunities, using tools like the Opportunity Solutions Tree.
- •Explore & Research: deep exploration of promising opportunities to identify relevant and well-defined problems through qualitative and quantitative research.
- •Ideation & Hypothesis Generation: generation of multiple possible solutions, prioritization and formulation of clear hypotheses that could be validated.
- •Validation: identification of critical assumptions, experimentation and informed decision-making on whether to move to delivery or continue exploring.
The model also clarified how different disciplines participated in discovery, adapting concepts like the Product Trio to our organizational reality. We defined roles for permanent, occasional and support collaboration, ensuring decisions combined user, business, data and technical feasibility perspectives, and that key stakeholders remained informed.
The focus was on providing a shared language, clear expectations and minimum shared practices.
Validate the model through a pilot with real teams
Before scaling the model, we validated it through a pilot with three product teams.
During a full quarter, the UX Research team led an intensive training + coaching program, working with teams on real problems from their day-to-day. The approach combined:
- •Practical training in discovery
- •Facilitation of real exploration, ideation and validation sessions
- •Continuous support in decision-making
This pilot allowed us to observe how the model worked in real contexts, detect friction points and adjust both the framework and the support tools before scaling it.
Iterate and scale the model across the organization and group
After analyzing the pilot results, we iterated on the model and the adoption approach before starting the rollout.
The deployment started at Adevinta Spain, supported by structured training, shared materials and a continuous coaching model. As adoption progressed, teams from other European countries showed interest in the approach.
This led to progressively extending the rollout to the rest of the Adevinta group, turning the model into a common Product Discovery reference at a European level.
Why this mattered
This initiative structurally transformed how product teams across the Adevinta group made decisions.
The model introduced a shared way of working with uncertainty, shifting the focus from early delivery of solutions towards learning, hypothesis validation and evidence-based prioritization. This allowed teams to build with greater confidence and reduce the risk of investing in low-impact initiatives.
The impact went beyond the organization. The model served as the basis for The Hero Camp to launch the first Product Discovery training program in Spanish, a course that remains active today and has trained many professionals based on this approach.
This project demonstrated that frameworks generate real impact when they are connected to teams' reality and when they are accompanied by enablement, coaching and continuous evolution.