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课程信息
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4,889 个评分
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
您将获得的技能
Predictive AnalyticsCustomer AnalyticsRegression AnalysisMarketing Performance Measurement And Management
教学大纲 - 您将从这门课程中学到什么
Week
1Introduction to Customer Analytics
What is Customer Analytics? How is this course structured? What will I learn in this course? What will I learn in the Business Analytics Specialization? These short videos will give you an overview of this course and the specialization; the substantive lectures begin in Week 2.
2 个视频（共 4 分钟）
Week
2Descriptive Analytics
In this module, you’ll learn what data can and can’t describe about customer behavior as well as the most effective methods for collecting data and deciding what it means. You’ll understand the critical difference between data which describes a causal relationship and data which describes a correlative one as you explore the synergy between data and decisions, including the principles for systematically collecting and interpreting data to make better business decisions. You’ll also learn how data is used to explore a problem or question, and how to use that data to create products, marketing campaigns, and other strategies. By the end of this module, you’ll have a solid understanding of effective data collection and interpretation so that you can use the right data to make the right decision for your company or business.
7 个视频（共 73 分钟）, 2 个阅读材料, 1 个测验
7 个视频
Descriptive Data Collection: Survey Overview16分钟
Descriptive Data Collection: Net Promoter Score and Self-Reports11分钟
Descriptive Data Collection: Survey Design16分钟
Passive Data Collection4分钟
Media Planning8分钟
Causal Data Collection and Summary8分钟
2 个阅读材料
Descriptive Analytics Slides10分钟
Additional Readings: Descriptive Analytics10分钟
1 个练习
Descriptive Analytics Quiz20分钟
Week
3Predictive Analytics
Once you’ve collected and interpreted data, what do you do with it? In this module, you’ll learn how to take the next step: how to use data about actions in the past to make to make predictions about actions in the future. You’ll examine the main tools used to predict behavior, and learn how to determine which tool is right for which decision purposes. Additionally, you’ll learn the language and the frameworks for making predictions of future behavior. At the end of this module, you’ll be able to determine what kinds of predictions you can make to create future strategies, understand the most powerful techniques for predictive models including regression analysis, and be prepared to take full advantage of analytics to create effective data-driven business decisions.
10 个视频（共 79 分钟）, 4 个阅读材料, 1 个测验
10 个视频
Asking Predictive Questions3分钟
Regression Analysis, Part 1: The Demand Curve5分钟
Regression Analysis, Part 2: Making Predictions5分钟
Beyond Period 210分钟
Making Predictions Using a Data Set8分钟
Data Set Predictions: Mary, Sharmila, or Chris?10分钟
Probability Models10分钟
Implementation of the Model16分钟
Results and Predictions5分钟
4 个阅读材料
Reading: Customer Lifetime Value10分钟
Predictive Analytics and Regression Analysis Slides10分钟
Implementation of the Model Spreadsheet10分钟
Additional Readings: Predictive Analytics10分钟
1 个练习
Predictive Analytics Quiz20分钟
Week
4Prescriptive Analytics
How do you turn data into action? In this module, you’ll learn how prescriptive analytics provide recommendations for actions you can take to achieve your business goals. First, you’ll explore how to ask the right questions, how to define your objectives, and how to optimize for success. You’ll also examine critical examples of prescriptive models, including how quantity is impacted by price, how to maximize revenue, how to maximize profits, and how to best use online advertising. By the end of this module, you’ll be able to define a problem, define a good objective, and explore models for optimization which take competition into account, so that you can write prescriptions for data-driven actions that create success for your company or business.
7 个视频（共 42 分钟）, 1 个阅读材料, 1 个测验
7 个视频
What is Prescriptive Analytics?4分钟
Using the Data to Maximize Revenue6分钟
Parameters of the Model10分钟
Market Structure9分钟
Competition and Online Advertising Models5分钟
Conclusion(s)5分钟
1 个阅读材料
Prescriptive Analytics Slides10分钟
1 个练习
Prescriptive Analytics Quiz20分钟
4.5
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热门审阅
创建者 SS•Nov 15th 2016
Amazing course for even beginners in the field of customer analytics. Highly recommend to do this course for enhancing the analytical skills. Examples and case studies explains the concept very well.
创建者 AA•Apr 6th 2017
Perfect Course for those who want to inquire insight and knowledge of how tons of data that we generate in our day to day life is being utilized by big organizations in optimizing their productivity.
讲师
Eric Bradlow
Professor of Marketing, Statistics, and Education, Chairperson, Wharton Marketing Department, Vice Dean and Director, Wharton Doctoral Program, Co-Director, Wharton Customer Analytics InitiativeThe Wharton School
Peter Fader
Professor of Marketing and Co-Director of the Wharton Customer Analytics InitiativeThe Wharton School
Raghu Iyengar
Associate Professor of MarketingThe Wharton School
Ron Berman
Assistant Professor of MarketingThe Wharton School
关于 University of Pennsylvania
The University of Pennsylvania (commonly referred to as Penn) is a private university, located in Philadelphia, Pennsylvania, United States. A member of the Ivy League, Penn is the fourth-oldest institution of higher education in the United States, and considers itself to be the first university in the United States with both undergraduate and graduate studies.
关于 Business Analytics 专项课程
This Specialization provides an introduction to big data analytics for all business professionals, including those with no prior analytics experience. You’ll learn how data analysts describe, predict, and inform business decisions in the specific areas of marketing, human resources, finance, and operations, and you’ll develop basic data literacy and an analytic mindset that will help you make strategic decisions based on data. In the final Capstone Project, you’ll apply your skills to interpret a real-world data set and make appropriate business strategy recommendations.
常见问题
When will I have access to the lectures and assignments?
Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?
Is financial aid available?
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