PRIYANKA PONNAGANTI

Own a portfolio of AI-powered customer experience, enterprise business systems, and operational excellence programs across Product, Engineering, Applied Science, Customer Support, and Operations organizations. Lead cross-functional initiatives that improve customer journeys, enable AI-driven decision-making, and optimize business operations through analytics, automation, and scalable technology solutions.

Customer Self-Service Optimization (Online Return Center)

• Led the analysis of 40K–45K weekly Online Return Center requests using SQL, Amazon Redshift, and Amazon QuickSight to identify customer pain points driving Customer Support contacts.
• Partnered with Product, Engineering, Customer Support, and Operations teams to define and execute a customer experience roadmap that reduced Online Return Center to Customer Support transfers from 18% to 8.75%.
• Designed and operationalized an AI-assisted Voice of Customer framework, increasing weekly customer audits from 200 to 600 cases, accelerating root cause identification, and product decision-making.
• Established executive KPI governance through Weekly, Monthly, and Quarterly Business Reviews (WBRs, MBRs, and QBRs), enabling data-driven prioritization across multiple product teams.
• Influenced product strategy through customer insights, business analytics, and executive reporting, which improved self-service adoption and operational efficiency.

VISTA – AI-Powered Image Assessment Platform.

• Led end-to-end program execution of the VISTA AI platform across Product, Applied Science, Engineering, Annotation, Customer Support, and Operations teams.
• Directed cross-functional planning, stakeholder alignment, and rollout readiness across four international marketplaces, while preparing for expansion into four additional countries.
• Defined business requirements, coordinated User Acceptance Testing (UAT), and partnered with engineering and applied science teams to validate AI prediction quality, metadata integrity, business workflows, and production readiness before launch.
• Influenced product strategy by expanding VISTA capabilities to support damaged and defective return scenarios, reducing manual image reviews, while improving operational efficiency.
• Developed executive KPI dashboards and performance reporting, supporting approximately 15,000 AI-assisted image evaluations each week.
• Managed cross-functional dependencies, launch risks, and stakeholder communications to ensure successful global deployments.

Methods Page Optimization

• Led customer journey analysis to optimize return method selection, and improve self-service experiences.
• Partnered with Product and Engineering teams to perform root cause analysis using SQL and Amazon Redshift, identifying opportunities to improve customer experience and business processes.
• Defined KPIs, monitored customer funnels, and developed executive dashboards supporting product roadmap prioritization, and operational improvements.
• Collaborated with cross-functional stakeholders to drive data-informed decisions that improved customer journey visibility and operational excellence.

• Led enterprise data modernization initiatives using AWS Glue, Amazon S3, Azure Databricks, and PySpark, reducing cloud data processing latency by 40%.
• Partnered with business stakeholders to define reporting requirements and develop SQL-driven analytics and Power BI dashboards, reducing manual reporting effort by 70%.
• Supported enterprise analytics initiatives by translating business requirements into scalable, cloud-based reporting solutions.

• Led AI-enabled automation initiatives, eliminating approximately 80% of manual operational work.
• Collaborated with business stakeholders to identify predictive analytics opportunities and implement machine learning solutions that improved operational decision-making by 40%.
• Modernized legacy automation platforms into scalable, object-oriented applications supporting long-term operational efficiency.

• Delivered enterprise software initiatives supporting large-scale business operations within Agile development teams.
• Partnered with business analysts, product stakeholders, and engineering teams to improve enterprise Java and SQL-based business applications.
• Supported Agile planning, sprint execution, testing, production deployments, and continuous process improvements across cross-functional teams.

• Designed and developed a Python-based plagiarism detection application using Natural Language Processing (NLP), achieving 95% detection accuracy.
• Built a Flask- and MySQL-based backend application, strengthening application performance and maintainability.