Product
Learning System
Expanding product learning capacity without
increasing team size.
Role
Product Design Lead • System Architect
Scope
System Design • Research Strategy • Cross-functional Alignment
work
Built an unmoderated feedback system combining scalable surveys with targeted co-design sessions.
IMPACT
Turned weeks of product guesswork into confident execution within days
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opportunity
Urgency often beats evidence, leading to late redesigns, unclear product direction, and missed product goals.
Existing Tensions
Traditional methods require researches to choose between quantitative (breadth) or qualitative (depth).
Opportunity
Urgency often beats
evidence.
Late redesigns and missed
product goals frequently
stem from decisions made in
an evidentiary vacuum
Methodology A
Moderated Interviews
Deep nuance, but high
resource cost and slow
feedback loops
Methodology B
Surveys
Wide reach, but often lacks
the 'why' behind the
quantitative data
product
Best of Both Worlds
Product teams need a timely, scalable, lightweight system for continuously gathering of real-world interaction feedback during development.
01
product team
Asks product question
02
product learning system
Generates measurable feedback structure
03
user
Provide real-world signal
04
research team
Deeper investigation & Synthesis
Key Decisions
Design the system
to scale across the
organization
Prioritize scalable signal over exhaustive research
In order to support typically small research teams, the
system needs to generate useful product signal without heavy moderation.
01
Separate signal generation from deep learning
Surveys generate scalable feedback first, followed by targeted
co-design sessions for deeper exploration.
02
Extend research capacity without increasing headcount
Product teams gather feedback independently while researchers focus on higher-impact investigations.
03
Product Learning
System Workflow
A hybrid model combining scalable
feedback with targeted co-design
Process
Team submits prototype
Users interact with Prototype
Structured feedback captured
Performance signals generated
Targeted follow-up
Design iteration
Unmoderated interaction feedback
Teams submit a prototype or product question. Users interact
with the experience and provide structured survey feedback.
This generates scalable signal within days.
1
Targeted follow-up & co-design
Teams engage more deeply with specific user segments—
particularly those with low scores or unexpected responses.
These sessions enabled deeper insight and collaborative exploration of new solutions.
2
OUTCOME
Team generated actionable product insight within days instead of weeks
The system was used by high-priority product teams, including Oculus and Metaverse.
Interaction feedback surfaced design issues early, transforming a slow research process to a lightweight part of everyday product development.
Across iterations, teams saw improvements in design performance scores and achieved clearer product direction.
Research that operates outside the product development loop struggles to influence decisions.