Case Study: Red Hat achieves a 311% increase in self‑solve rate (7.39% case deflection) with Lucidworks Fusion

Relevancy Empowers Red Hat Customers to Self-Solve

Red Hat, the enterprise open‑source software provider serving over 80% of the Fortune 1000, needed to help customers quickly self-solve issues—finding knowledgebase articles, downloads, and troubleshooting tools—while scaling support across a large, growing product portfolio. The challenge was to surface the right content for varied intents so customers could resolve problems without creating support cases.

Red Hat deployed Lucidworks Fusion to detect user intent with machine learning (including Word2Vec), surface solutions from prior resolved cases, and boost content using clickstream and engineer feedback with time decay. Over a two‑month period in 2020 this drove a 7.39% support case deflection (2,700+ cases), a 311% increase in self‑solve rate versus 2018, a 2.2 average click depth and a 58.4% click‑through rate—improving relevancy, scaling support, and reducing operational load.

Red Hat

Manikandan Sivanesan

Principal Software Engineer