Nahdi Medical - Customer Success Story
公司规模
1,000+
地区
- Middle East
国家
- Saudi Arabia
产品
- Repustate Arabic Aspect-Based Sentiment Analysis Model
技术栈
- Arabic Natural Language Processing (NLP)
- Named Entity Recognition (NER)
- Arabic Part-of-Speech Tagger
- Arabic Lemmatizer
实施规模
- Enterprise-wide Deployment
影响指标
- Customer Satisfaction
- Employee Satisfaction
- Productivity Improvements
技术
- 分析与建模 - 自然语言处理 (NLP)
- 分析与建模 - 预测分析
- 应用基础设施与中间件 - 数据交换与集成
适用行业
- 医疗保健和医院
- 药品
适用功能
- 商业运营
- 质量保证
服务
- 数据科学服务
- 系统集成
关于客户
Nahdi Medical Company is a Jeddah-based clinic and pharmacy chain that operates a nationwide network in Saudi Arabia, covering 145 cities and villages. It is one of the fastest-growing companies in the region, providing advanced medical care in key areas such as radiology, oncology, cardiology, and pediatrics. In addition to its physical clinics and pharmacies, Nahdi offers online video consultation services for patients who are unable to visit doctors in person. The company is committed to delivering high-quality medical care and personalized attention to its patients and customers.
挑战
Nahdi Medical Company faced the challenge of analyzing a vast amount of feedback from both employees and patients, which included comments on various topics such as employee salaries, vacation time, online pharmacy orders, delivery & pricing, and appointments. The primary issue was finding an error-free, accurate system that could analyze all the comments from patient voice data and surveys in Arabic without losing the nuances of the language. Existing text analytics solutions that translated non-English text into English first for sentiment analysis were not effective, as they diluted the nuances of Arabic text. Nahdi needed a solution that could seamlessly understand Arabic and its dialects, classify and categorize valuable feedback, and provide insights for strategic and focused decision-making.
解决方案
Repustate developed a customized aspect-based sentiment model specifically for Nahdi Medical Company to capture both the voice of the employee (VoE) and voice of the customer (VoC) data. This solution was designed for the Arabic-speaking populace and could understand major Arabic dialects such as Gulf Peninsular, Egyptian, and Levantine Arabic. The model could analyze data from various sources, including videos, audio channels, patient vlogs, social media vlogs, comments, reviews, and surveys. The solution featured a dedicated Arabic part-of-speech tagger, Arabic lemmatizer, and Arabic-specific sentiment models. By leveraging Arabic natural language processing (NLP) and named entity recognition (NER), the model could identify topics and themes in the data for more granular sentiment analysis, leading to key business insights. Repustate's aspect-based sentiment analysis model provided Nahdi with the ability to semantically cluster and group data into several distinct categories. For each comment received, the model computed the sentiment and classified the comment into one or more aspects. Nahdi then processed the output into their larger data warehouse to visualize the results and take appropriate actions.
运营影响
数量效益
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