Meta UXR Internship
Helping Meta teams in their efforts to keep communities safe.
Qualitative research to improve internal tooling
* Specific information has been removed & abstracted to keep confidentiality.
During my 3-month summer internship at Meta in 2022, I conducted a foundational UX research project to enhance the usability of internal tools within Meta's integrity unit. I sought clarity on an elusive but essential customer segment at the heart of the integrity process. Amidst the fluid structure of Meta and its layered integrity tasks, my challenge pivoted around coalescing efforts with a definition about this customer, segmenting usage and gathering insights for tooling teams.
Collaborated closely with PMs, SWEs, Managers, and Integrity Designers + UX researchers.
Designed study, drove research, and shared findings from a comprehensive UX research initiative.
Adopted diverse techniques, including Interviews, Focus Groups, meticulous log data analysis, and exhaustive document reviews.
Customer Definition Offer a clear and standardized lens on an essential 'customer' in Meta's Integrity process. Align tooling teams around the definition, identify segments of this internal customer and clarify their journey.
Tool Enhancement Research Insights and socialization for defragmentation of the experience and sel-serviceability of tools for non-engineers.
Literature Review & XFN Engagement
Interfaced with 12 cross-functional experts spanning design, engineering, and operations to gather requirements and .
Looked through company documentation to identify gaps and diversions in the customer definition.
Crafted and shared a set of definitions for a collective grasp of this customer.
Socialized the terms and definitions and gathered feedback.
Log Data Analysis
Scrutinized log data through SQL queries and data visualization, distinguishing diverse user categories and deciphering their behavioral motifs.
These insights not only enriched stakeholder discussions but also sharpened my recruitment strategy. Identifying the team's multifunctional dynamics, I leveraged data to perceive them as a user spanning multiple roles.
Initiated direct conversations with tool users, gathering insights about their team dynamics, as well as individual challenges and needs.
Focus Groups with Graphic Elicitation
Conducted focus group sessions, incorporating graphic elicitation to empower teams in visually articulating their tool interactions, yielding richer insights.
Journey Map: Constructed an illustrative map pinpointing interactions and touchpoints across team members throughout tooling in a common scenario.
Behavioral Archetypes: Shaped user archetypes, conveying the interactions and needs of various user segments and user teams.
Data Visualization: Represented log data, spotlighting tool interaction patterns, serving as a visual compass for stakeholders.
Reflections & Insights
One of the primary challenges I faced was the varied understanding of 'customers' at different stages of the process. While operations were the direct users, the underlying needs were often steered by machine learning engineers. This differential in perspective sparked direction conflicts for research across technical specializations.
My deep dive unearthed opportunities for tool enhancements. I pinpointed stages in the process burdened by cumbersome and repetitive interactions among team members. Such dense and manual exchanges signaled clear areas where tool optimization could significantly streamline team collaboration and boost overall efficiency.