I shape strategy
Turning fragmented Autofill evidence into product direction
Meta’s Autofill experience had evolved through years of research, experiments, product decisions, and incremental changes. The information existed, but the team didn’t have one clear view of the ecosystem or the biggest opportunities. I partnered with Product Design and UXR to bring that evidence together and create a shared basis for product strategy and roadmap decisions.
Problem
The team had plenty of information, but no shared understanding of the product.
Outcome
A common model turned fragmented evidence into five strategic themes, 15 recommendations, and direction that influenced approximately 85% of planned H1 priorities.
The challenge
Research, performance data, competitive findings, and historical decisions were spread across different teams and artifacts.
That made it difficult to see recurring problems across the full experience or know which opportunities were most important.
What I did
I turned disconnected evidence into a product model teams could act on.
I mapped the Autofill ecosystem across core experiences, synthesized research and competitive patterns, and reframed the product around what people were actually trying to do.
That work surfaced recurring issues around trust, control, consistency, and recovery. I translated those patterns into five strategic themes and 15 recommendations spanning content, design, product behavior, and engineering.
Research (UXR) identified the underlying jobs to be done. I interpreted those findings and organized them into the five-part framework below, then used it to evaluate the current Autofill experience and competitive products.
Evidence→Patterns / gaps→5 themes→15 recommendations→Roadmap priorities
The audit converted distributed evidence into a traceable path from finding to investment decision.
Resolution
The audit gave the team a shared view of Autofill and a clearer basis for prioritization.
Instead of evaluating individual screens in isolation, teams could see where the same problems appeared across the ecosystem and make decisions against common evidence and principles.
Impact
Autofill audit impact
That finding directly informed later Autofill optimization work.
Reflection
Strategy often starts by making the problem legible.
The most valuable output wasn’t the audit itself. It was giving Product, Design, Research, Engineering, and Content a shared way to understand the system and decide what deserved attention.