Recommender System for Improving Customer Loyalty
暫譯: 提升顧客忠誠度的推薦系統
Tarnowska, Katarzyna, Ras, Zbigniew W., Daniel, Lynn
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商品描述
This book presents the Recommender System for Improving Customer Loyalty. New and innovative products have begun appearing from a wide variety of countries, which has increased the need to improve the customer experience. When a customer spends hundreds of thousands of dollars on a piece of equipment, keeping it running efficiently is critical to achieving the desired return on investment. Moreover, managers have discovered that delivering a better customer experience pays off in a number of ways. A study of publicly traded companies conducted by Watermark Consulting found that from 2007 to 2013, companies with a better customer service generated a total return to shareholders that was 26 points higher than the S&P 500. This is only one of many studies that illustrate the measurable value of providing a better service experience.
The Recommender System presented here addresses several important issues. (1) It provides a decision framework to help managers determine which actions are likely to have the greatest impact on the Net Promoter Score. (2) The results are based on multiple clients. The data mining techniques employed in the Recommender System allow users to "learn" from the experiences of others, without sharing proprietary information. This dramatically enhances the power of the system. (3) It supplements traditional text mining options. Text mining can be used to identify the frequency with which topics are mentioned, and the sentiment associated with a given topic. The Recommender System allows users to view specific, anonymous comments associated with actual customers. Studying these comments can provide highly accurate insights into the steps that can be taken to improve the customer experience. (4) Lastly, the system provides a sensitivity analysis feature. In some cases, certain actions can be more easily implemented than others. The Recommender System allows managers to "weigh" these actions and determine which ones would have a greater impact.商品描述(中文翻譯)
這本書介紹了用於提升顧客忠誠度的推薦系統。來自各國的新穎創新產品開始出現,這增加了改善顧客體驗的需求。當顧客在一件設備上花費數十萬美元時,保持其高效運行對於實現預期的投資回報至關重要。此外,管理者發現,提供更好的顧客體驗在多方面都有回報。Watermark Consulting 對上市公司的研究發現,從 2007 年到 2013 年,顧客服務較好的公司為股東創造的總回報比標準普爾 500 指數高出 26 個百分點。這只是眾多研究中的一個,顯示出提供更好服務體驗的可衡量價值。
這裡介紹的推薦系統解決了幾個重要問題。(1) 它提供了一個決策框架,幫助管理者確定哪些行動可能對淨推薦值(Net Promoter Score)產生最大的影響。(2) 結果基於多個客戶。推薦系統中使用的數據挖掘技術允許用戶從他人的經驗中「學習」,而無需分享專有信息。這大大增強了系統的能力。(3) 它補充了傳統的文本挖掘選項。文本挖掘可用於識別主題提及的頻率以及與特定主題相關的情感。推薦系統允許用戶查看與實際顧客相關的具體匿名評論。研究這些評論可以提供非常準確的見解,幫助改善顧客體驗的步驟。(4) 最後,該系統提供了敏感性分析功能。在某些情況下,某些行動的實施可能比其他行動更容易。推薦系統允許管理者「權衡」這些行動,並確定哪些行動會產生更大的影響。