Case Study: Nahdi Medical achieves accurate Arabic sentiment insights and improved patient care with Repustate's aspect-based sentiment analysis

Nahdi Medical Voice of Customer and Employee Success Story

Nahdi Medical, a Jeddah-based clinic and pharmacy chain operating across 145 cities and villages in Saudi Arabia, needed to mine large volumes of Arabic feedback from patients, caregivers and employees to prioritize improvements. Faced with dialectal Arabic that other vendors mishandled (often by translating into English), Nahdi engaged Repustate to provide an Arabic aspect-based sentiment analysis solution to automatically classify and extract insights from voice-of-customer and voice-of-employee data.

Repustate developed a customized Arabic aspect-based sentiment model — with an Arabic POS tagger, lemmatizer, NER and dialect support (Gulf, Egyptian, Levantine) — to semantically cluster aspects and apply sentiment at the aspect level across surveys, reviews and audio/video content. Integrated into Nahdi’s data warehouse, the Repustate solution delivered faster, more accurate insights than prior vendors, reduced manual review, enabled management to pinpoint clinics and locations needing attention, and supported more targeted, personalized patient care and improved employee-satisfaction tracking.

Nahdi Medical

Ayman Abdelazem

Head of Business Intelligence & Analytics