About this role
About the team
The Monetization Product Operations (MPO) is responsible for Customer Support and Tools & Workflows within Product Strategy & Operations team. Its mission is to provide Best in class advertising experience by ensuring excellence in customer service and streamlining process & tools to ensure smooth operations.
The team collaborates with Sales to provide post-sales support and works closely with product team on product improvement through feature requests and management of bugs.
Responsibilities
- Run targeted training for Vendor agents on recurring issue types, priority workflows, and quality expectations, including onboarding and refresher courses
- Conduct case reviews and deep dives into repeated escalations, low-quality resolutions, and unclear handoffs to isolate process, SOP, training, or tooling gaps
- Track common failure patterns by category and convert findings into clear improvement asks for GTPS, PMM, or Vendor operations
- Prioritise gaps that directly affect launch readiness, onboarding quality, partner trust, or resolution speed
- Own online SOPs as the single source of truth for Vendor handling, SME review, and escalation decisions, keeping them updated with process changes, edge cases, required evidence, and escalation boundaries
- Remove outdated or conflicting guidance so Vendor agents do not rely on offline knowledge or inconsistent local practices
- Label historical and new cases by issue type, correct resolution path, escalation trigger, and ideal response quality to support AI TPS training data
- Prioritise labeling for high-volume routine tickets and categories where AI TPS can safely automate once quality gates are met, flagging ambiguous cases for human handling
- Review AI TPS outputs for accuracy, completeness, tone, policy alignment, and correct SOP usage
- Compare AI recommendations against best-agent human handling to identify where AI is ready for autonomy versus where it still needs guardrails
- Define quality thresholds for routine closure, escalation, and human review
- Provide structured feedback to AI TPS teams on wrong categories, weak reasoning, missing SOP coverage, poor escalation decisions, and unclear partner guidance
- Convert repeated AI errors into SOP updates, new examples, evaluation cases, or revised automation boundaries
- Use Vendor and SME observations to continuously improve the AI bot and the human escalation model