Business Analytics 专项课程
Make Data-Driven Business Decisions. Achieve fluency in business data strategies in four discipline-specific courses.
Business Analytics 专项课程
5 coursesUniversity of Pennsylvania
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
Skills you will gain
Marketing Performance Measurement And ManagementMarketing AnalyticsData AnalysisPredictive Analytics
Syllabus - What you will learn from this course
1
Section
Introduction 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 videos (Total 4 min)
2
Section
Descriptive 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 videos (Total 73 min), 2 readings, 1 quiz
7 videos
Descriptive Data Collection: Survey Overview16m
Descriptive Data Collection: Net Promoter Score and Self-Reports11m
Descriptive Data Collection: Survey Design16m
Passive Data Collection4m
Media Planning8m
Causal Data Collection and Summary8m
2 readings
Descriptive Analytics Slides10m
Additional Readings: Descriptive Analytics10m
1 practice exercises
Descriptive Analytics Quiz20m
3
Section
Predictive 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 videos (Total 79 min), 4 readings, 1 quiz
10 videos
Asking Predictive Questions3m
Regression Analysis, Part 1: The Demand Curve5m
Regression Analysis, Part 2: Making Predictions5m
Beyond Period 210m
Making Predictions Using a Data Set8m
Data Set Predictions: Mary, Sharmila, or Chris?10m
Probability Models10m
Implementation of the Model16m
Results and Predictions5m
4 readings
Reading: Customer Lifetime Value10m
Predictive Analytics and Regression Analysis Slides10m
Implementation of the Model Spreadsheet10m
Additional Readings: Predictive Analytics10m
1 practice exercises
Predictive Analytics Quiz20m
4
Section
Prescriptive 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 videos (Total 42 min), 1 reading, 1 quiz
7 videos
What is Prescriptive Analytics?4m
Using the Data to Maximize Revenue6m
Parameters of the Model10m
Market Structure9m
Competition and Online Advertising Models5m
Conclusion(s)5m
1 readings
Prescriptive Analytics Slides10m
1 practice exercises
Prescriptive Analytics Quiz20m
5
Section
Application/Case Studies
How do top firms put data to work? In this module, you’ll learn how successful businesses use data to create cutting-edge, customer-focused marketing practices. You’ll explore real-world examples of the five-pronged attack to apply customer analytics to marketing, starting with data collection and data exploration, moving toward building predictive models and optimization, and continuing all the way to data-driven decisions. At the end of this module, you’ll know the best way to put data to work in your own company or business, based on the most innovative and effective data-driven practices of today’s top firms.
8 videos (Total 84 min), 2 readings, 1 quiz
8 videos
The Future of Marketing is Business Analytics7m
The Golden Age of Marketing16m
Applications: ROI11m
Radically New Data Sets in Marketing7m
The Perils of Efficiency13m
Analytics Applied: Kohl's, NetFlix, AmEx and more18m
Conclusion5m
2 readings
Application/Case Study Slides10m
Additional Reading: the Power of Data10m
1 practice exercises
Applications20m
4.5
32%
83%
Top Reviews
By 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.
By 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.
Instructors
Eric Bradlow
Professor of Marketing, Statistics, and Education, Chairperson, Wharton Marketing Department, Vice Dean and Director, Wharton Doctoral Program, Co-Director, Wharton Customer Analytics Initiative
Peter Fader
Professor of Marketing and Co-Director of the Wharton Customer Analytics Initiative
Raghu Iyengar
Associate Professor of Marketing
Ron Berman
Assistant Professor of MarketingAbout 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.
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