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所在平台: Udemy |
课程主页: https://www.udemy.com/course/customer-analytics-with-r-and-tableau/
课程评论：没有评论
课程名称：使用 R 和 Tableau 进行客户分析 课程概述： 在当今竞争激烈的市场中，理解客户对任何企业的成功至关重要。本课程介绍了客户分析，教授如何利用 R 和 Tableau 进行市场研究、细分受众、分析客户流失以及做出基于数据的决策。通过实际案例研究，您将掌握描述性分析、预测性分析和规范性分析的关键技术，以推动以客户为中心的战略。 章节内容： 第一部分：引言 您将踏上客户分析的旅程，了解其在各行业中的重要性和应用。本节概述了如何使用 R 和 Tableau 从客户数据中提取洞察，并将其转化为可行的战略。 第二部分：市场研究与分析 通过实际案例深入市场研究，例如分析银行的净推荐值（NPS）。学习区分客户的期望与感知，并探索特别针对航空业的市场细分技术。本节总结了集群组及其相关性，结合描述性和预测性分析揭示公司绩效指标。 第三部分：电信客户流失与案例研究 探讨客户分析的现实应用，分析电信行业的客户流失情况。理解预测模型中的敏感性和特异性，并利用规范性分析解决流失问题。本节通过引人入胜的案例研究巩固您应用分析解决客户相关挑战的理解。 课程总结： 本课程为您提供了在使用 R 和 Tableau 进行客户分析方面所需的技能和工具。到课程结束时，您将能够进行深入的客户分析，发现趋势，并制定提高客户满意度和留存率的策略。
Course IntroductionUnderstanding customers is vital for any business aiming to thrive in today's competitive market. This course introduces you to customer analytics, teaching you how to leverage R and Tableau to conduct market research, segment audiences, analyze customer churn, and make data-driven decisions. Through hands-on case studies, you'll master key techniques in descriptive, predictive, and prescriptive analytics to drive customer-centric strategies.Section-wise WriteupSection 1: IntroductionBegin your journey into customer analytics by understanding its significance and applications across industries. This section provides an overview of how R and Tableau can be used to derive insights from customer data and transform them into actionable strategies.Section 2: Market Research and AnalyticsDive into market research with practical examples, such as analyzing Net Promoter Scores (NPS) of banks. Learn to differentiate between customer exceptions and perceptions and explore market segmentation techniques, specifically for the airline industry. The section concludes with a summary of cluster groups and their relevance, along with insights into company performance metrics through descriptive and predictive analytics.Section 3: Telecom Churn and Case StudiesExplore a real-world application of customer analytics by analyzing telecom customer churn. Understand sensitivity and specificity in predictive modeling and leverage prescriptive analytics to address churn issues. This section culminates with engaging case studies that solidify your understanding of applying analytics to solve customer-related challenges.ConclusionThis course equips you with the skills and tools necessary to excel in customer analytics using R and Tableau. By the end of the course, you'll be capable of conducting in-depth customer analyses, uncovering trends, and developing strategies to improve customer satisfaction and retention.
