Case Study: PagesJaunes achieves a 30% boost in category manager productivity and improved customer satisfaction with Dataiku DSS

How PagesJaunes Automatically Targets & Fixes False Query Results to Improve Customer Satisfaction

PagesJaunes, the French Yellow Pages and leader in local advertising, faced the challenge of improving search result relevance and customer satisfaction across hundreds of millions of queries without increasing category managers’ workload. To address this, PagesJaunes partnered with Dataiku and used Dataiku’s Data Science Studio (DSS) to pursue a Predictive Content Management approach that could automatically identify and prioritize problematic queries for correction.

Dataiku built a DSS app that ingests search and navigation logs, scores queries with machine‑learning models (e.g., random forest, logistic regression), and automatically detects and surfaces failed or false queries so category managers can focus remediation. The solution delivered measurable impact: a 30% boost in category manager productivity, faster adoption of Hadoop and ML, training of more than ten PagesJaunes collaborators, and ongoing improvements in customer satisfaction and search quality.

PagesJaunes

Erwan Pigneul

Project Manager