Case Study: a major car manufacturer improves customer experience with Expleo’s big data and predictive diagnostics

Big data improving the customer experience through the predictive diagnosis of in-service failures

A major car manufacturer faced the challenge of processing and analyzing vast quantities of unstructured feedback data from sources like surveys, workshop reports, and social media to anticipate vehicle quality issues. To gain an exhaustive overview of customer satisfaction and predict in-service failures, they turned to Expleo for its expertise in data science, textual analysis, and RAMS engineering.

Expleo implemented a solution combining natural language processing (NLP) algorithms, the Python programming language, and data visualization platforms like TIBCO Spotfire. This approach automated the analysis of field reports, drastically reducing processing time from several days to minutes and cutting the manual readback rate by 50%. The implementation allowed the manufacturer to classify potential issues into 600 failure scenarios with 80% accuracy, significantly improving the speed and relevance of their diagnostic process and enabling them to meet customer expectations more effectively.