Context

The Quality Management System (QMS) is used by Meta’s support teams to improve overall support quality. Senior agents (Quality Analysts) review customer conversations, provide feedback, and assign scores, which frontline agents use to improve their performance.

At the time, QMS had no built-in calibration feature. Each program ran its own manual process, making calibration slow, inconsistent, difficult to scale, and prone to bias. We aimed to automate this workflow within QMS and roll it out across Meta’s support ecosystem.

What I Did

I led the end-to-end product and UX process. I interviewed senior agents to understand their workflows, mapped the calibration journey, and created user flows and high-fidelity screens. Because QMS supported multiple programs, I also introduced one of Meta’s design systems to ensure consistency and long-term scalability.

I partnered with the PM, engineers, and program managers to define scope, align expectations, and deliver an MVP that met operational needs while fitting into the broader support ecosystem.

Results & Impact

The calibration feature reduced senior agents’ calibration time by 41% and replaced a fragmented manual process with a unified workflow. QMS expanded to five support programs, with more than 8,000 agents using the system.

The new experience improved scoring consistency and created a fairer, more scalable quality-review process across Meta’s support operations.