Case Study: FactSet achieves 2X chat agent productivity and 66% faster chat resolution with NICE Systems CXone

FactSet Solves the Support Formula with NICE CXone

FactSet Research Systems provides data and analytics to over 200,000 investment professionals and fields more than 50,000 monthly support contacts—about 75% via chat. As volumes and complexity grew (many inquiries involve technical data‑formula questions), maintaining a custom, engineer‑heavy contact center became unsustainable and diverted engineering resources from core product work.

FactSet moved to NICE CXone CCaaS (plus workforce and quality management, NICE MAX) and integrated those capabilities with its internal formula AI via APIs and a unified chat interface. The solution routes chats to the best agent, surfaces AI‑recommended formula answers, and enables agent use from any approved device. Early results include a 2x increase in chat agent productivity, preliminary estimates of up to 66% time savings on chats, 10% tool adoption so far (exceeding expectations), and improved quality management while freeing engineers to focus on product innovation.

FactSet

Avinash Sridhar

Vice President and Principal Software Engineer