Case Study: Solimut Mutuelle de France turns member feedback into actionable service quality intelligence with Feedier

Solimut Mutuelle de France cuts untagged verbatims from 30% to 18% with Feedier

Solimut Mutuelle de France, a French mutual health insurer, faced the challenge of gaining actionable insights from its 500,000 members' feedback. Their previous semantic analysis tool only performed basic keyword detection without capturing sentiment or context, making it impossible to measure the impact of improvement actions. The company turned to Feedier to implement a more intelligent customer feedback platform.

Using Feedier's LLM-powered semantic analysis, Solimut created a highly customized topic plan that captures the true meaning of verbatims. The solution enabled them to track topic evolution over time and measure the effect of corrective actions. With Feedier, Solimut reduced its rate of untagged feedback from 30% to 18% and built a reliable foundation for data-driven decisions, transforming scattered member comments into a continuous management system for service quality.

Solimut Mutuelle De France