Operationalizing Research
Research usually lives in decks and docs. Decisions don’t. I built an internal system to help research show up where decisions actually happen—without writing yet another slide deck.
Product & Strategy
Research
Internal Tool
At a Glance
Overview
As the organization grew, research insights were increasingly valuable — but also increasingly hard to use.
Insights lived across decks, documents, and conversations. Teams trusted the research, but accessing it often required time, context, or direct researcher involvement.
This work focused on a simple question:
How can research show up consistently in everyday decisions, not just in presentations?
Designing for Internal Decision Efficiency
Structuring Research for Reuse
Before introducing any AI layer, I focused on restructuring how research was stored and maintained.
This included:
defining a clear hierarchy of insights (foundational vs situational)
linking synthesized findings back to source material
establishing ownership and update expectations to maintain trust
standardizing how competitive and customer insights were documented
This groundwork ensured that any system built on top of the repository would surface reliable, verifiable information.
AI as an Access Layer, Not an Analysis Engine
With structure in place, I introduced an AI-assisted access layer to reduce friction in finding and applying research.
The system was designed to:
answer common questions using existing insights
summarize patterns across studies when appropriate
direct users to source material for deeper context
It was intentionally constrained.
The system did not replace researcher synthesis or generate new conclusions.
Its value came from speed, consistency, and accessibility.
Impact
Operational Impact
Reduced repeated ad-hoc research requests from Sales and Product teams
Enabled faster access to relevant insights during deal preparation and roadmap discussions
Improved consistency in how research was referenced across teams
Business Impact
Over the following year, Sales and Product Marketing cited this system as a key contributor to improved decision efficiency and alignment, alongside measurable outcomes:
96% YoY increase in conversion rate
27% improvement in win/loss outcomes
~$2.7M in incremental revenue attributed to better deal positioning and roadmap alignment
Why This Case Matters
This case demonstrates how research can scale beyond individual studies.
By designing systems that make insights accessible, connected, and trustworthy, researchers can support better decisions across the organization — without sacrificing rigor.
Research
Decision Systems
Internal Enablement
Research Infrastructure
AI-Assisted Workflows
January 12th, 2026