What are NLP use cases for business?
什麼是企業的 NLP 使用案例？
Businesses use NLP software and tools to simplify, automate, and streamline operations efficiently and accurately. We give some example use cases below.
Sensitive data redaction
Businesses in the insurance, legal, and healthcare sectors process, sort, and retrieve large volumes of sensitive documents like medical records, financial data, and private data. Instead of reviewing manually, companies use NLP technology to redact personally identifiable information and protect sensitive data. For example, Chisel AI helps insurance carriers extract policy numbers, expiration dates, and other personal customer attributes from unstructured documents with Amazon Comprehend.
Customer engagement
NLP technologies allow chat and voice bots to be more human-like when conversing with customers. Businesses use chatbots to scale customer service capability and quality while keeping operational costs to a minimum. PubNub, which builds chatbot software, uses Amazon Comprehend to introduce localized chat functionality for its global customers. T-Mobile uses NLP to identify specific keywords in customers' text messages and offer personalized recommendations. Oklahoma State University deploys Q&A chatbot solution to address student questions using machine learning (ML) technology
Business analytics
Marketers use NLP tools like Amazon Comprehend and Amazon Lex to gain an educated perception of what customers feel toward a company's product or services. By scanning for specific phrases, they can gauge the customer's moods and emotions in written feedback. For example, Success KPI provides natural language processing solutions that help businesses focus on targeted areas in sentiment analysis and help contact centers derive actionable insights from call analytics.
企業使用 NLP 軟體和工具來高效且準確地簡化、自動化和精簡操作。下面列出了一些範例使用案例。
敏感資料遮蔽
保險、法律和醫療保健領域的企業會處理、分類和擷取大量敏感文件，例如醫療記錄、財務資料和私人資料。公司並非手動審查，而是使用 NLP 技術來修訂個人身分資訊並保護敏感資料。例如，Chisel AI 可協助保險業者使用 Amazon Comprehend，從非結構化文件中擷取保單編號、到期日期和其他個人客戶屬性。
客戶參與
NLP 技術讓聊天和語音機器人在與客戶交談時更像人類。企業使用聊天機器人來擴展客戶服務能力和品質，同時將營運成本降至最低。PubNub 可建置聊天機器人軟體，使用 Amazon Comprehend 為其全球客戶介紹當地語系化聊天功能。T-Mobile 使用 NLP 識別客戶簡訊中的特定關鍵字，並提供個人化建議。 奧克拉荷馬州立大學部署答疑聊天機器人解決方案，使用機器學習 (ML) 技術來解決學生的問題
商業分析
行銷人員使用 Amazon Comprehend 和 Amazon Lex 之類的 NLP 工具，來了解客戶對公司產品或服務的感受。透過掃描特定片語，他們可在書面意見回饋中衡量客戶的情緒和情感。例如，Success KPI 提供各種自然語言處理解決方案，協助企業專注於情緒分析中的目標領域，並協助聯絡中心從通話分析中獲得可行的洞察。