Requirements
- Day-to-day operations: Assist in managing daily call center operations and workforce planning across multiple regions and 10+ languages, ensuring consistent SLAs and a seamless omnichannel experience (voice, chat, email, social, self-service).
- Training and enablement: Maintain, design, and deliver training for GCSS agents, including new hire, customer service, social media. Review and maintain and update internal knowledge base to ensure accuracy and consistency.
- Global vendor management: Partner with third-party vendors to meet KPIs related to quality, customer satisfaction, and efficiency; drive corrective actions and continuous improvement plans.
- Social and product launches: Facilitate new social support programs and product introductions, ensuring teams and bots are trained and ready before launch.
- Quality and compliance: Conduct quality audits across channels and regions. Ensure adherence to best practices, privacy and data handling standards, and regional regulations.
- Escalations: Support direct customer engagement for internal and external escalations, driving timely, empathetic, and complete resolutions.
- Governance and communication: Lead recurring operational reviews and cross-functional calls; attend QBRs as required; surface insights and recommendations to leadership.
- AI strategy in support: Help define and operationalize the AI roadmap for customer support, including virtual agents, agent assist/copilots, knowledge retrieval, and intelligent routing.
- Virtual agent excellence: Partner with product and engineering to design, test, and iterate chatbots and IVR/NLU flows; improve intent recognition, containment rate, and handoff quality.
- Agent assist and knowledge: Deploy and maintain AI-powered tools that summarize contacts, suggest next best actions, generate responses, and surface knowledge; maintain prompt libraries and guardrails.
- Quality automation: Leverage speech and text analytics, auto-QA, and sentiment analysis to increase coverage and consistency of evaluations; coach teams using data-driven insights.
- Forecasting and WFM: Use machine learning–driven forecasting, capacity models, and real-time analytics to optimize staffing and service levels.
- Experimentation and measurement: Run A/B tests on scripts, flows, deflection experiences, and knowledge content; track impact on CSAT, FCR, AHT, and cost-to-serve.
- Data stewardship: Partner with Security, Legal, and Privacy to uphold data protection, PII handling, and responsible AI principles; maintain model and prompt governance, audit logs, and evaluation frameworks.
- Localization at scale: Use translation, transcription, and multilingual NLU capabilities to deliver consistent support quality across languages.
Additional Information
- Travel: Up to 5%, including international travel as needed
