客户分析

Customer Analytics

本课程是商业分析专项课程的其中一门课程(共 5 门课程)

宾夕法尼亚大学

Coursera

商业管理

简单(初级)

12 小时

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  • 中文, 英语, 西班牙语
  • 1242

课程概况

人们浏览和购买商品模式的数据随处可见。从信用卡交易记录和网上购物车,到客户忠诚度计划和用户评分/评价,存在着大量数据,可以用于描述人们的历史购买行为、预测未来行为、制定影响未来购买的新方案。本门课程中,四名来自沃顿商学院的顶尖市场学教授将深析客户分析的四个重要领域:描述性分析、预测性分析、规范性分析以及它们在商业领域的实际应用,比如亚马逊、谷歌、星巴克等企业都在运用这些分析方法。完成本课程后,学生将了解到数据应用于描述、分析和预测客户行为的方式;利用数据做出最佳商业决策的方法;以及企业如何利用数据满足 (并塑造) 客户需求、如何创造更大盈利。本课程旨在帮助你在新兴数据结构方面做出更佳的商业决策,以便将所学知识应用于你自己的企业。

Data about our browsing and buying patterns are everywhere. From credit card transactions and online shopping carts, to customer loyalty programs and user-generated ratings/reviews, there is a staggering amount of data that can be used to describe our past buying behaviors, predict future ones, and prescribe new ways to influence future purchasing decisions. In this course, four of Wharton’s top marketing professors will provide an overview of key areas of customer analytics: descriptive analytics, predictive analytics, prescriptive analytics, and their application to real-world business practices including Amazon, Google, and Starbucks to name a few. This course provides an overview of the field of analytics so that you can make informed business decisions. It is an introduction to the theory of customer analytics, and is not intended to prepare learners to perform customer analytics.

Course Learning Outcomes:
After completing the course learners will be able to…
Describe the major methods of customer data collection used by companies and understand how this data can inform business decisions
Describe the main tools used to predict customer behavior and identify the appropriate uses for each tool
Communicate key ideas about customer analytics and how the field informs business decisions
Communicate the history of customer analytics and latest best practices at top firms

你将学到什么

Predictive Analytics

Customer Analytics

Regression Analysis

Marketing Performance Measurement And Management

课程大纲

Week 1 Introduction to Customer Analytics

Introduction to Customer Analytics

Week 2 Descriptive Analytics

Descriptive Analytics
Quiz: Descriptive Analytics Quiz

Week 3 Predictive Analytics

Predictive Analytics
Quiz: Predictive Analytics Quiz

Week 4 Prescriptive Analytics

Prescriptive Analytics
Quiz: Prescriptive Analytics Quiz

Week 5 Application/Case Studies

Applications and Case Studies
Quiz: Applications

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