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.
Eric BradlowProfessor of Marketing, Statistics, and Education, Chairperson, Wharton Marketing Department, Vice Dean and Director, Wharton Doctoral Program, Co-Director, Wharton Customer Analytics Initiative
Peter FaderProfessor of Marketing and Co-Director of the Wharton Customer Analytics Initiative
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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Bastante interesante, especialmente cuando se ven las aplicaciones reales que existen de diferentes marcas a nivel mundial. Me gusto mucho para ser mi primer curso y pocas cosas malas que decir de el.
Though I have worked on Customer Analytics with my previous work experiences and also on Surveys etc at George Brown College Canada, this module was more than insightful. Lots of learning to learn eh!
This course includes a comprehensive overview of the all the basic models that are used to analyze data concerning customer behavior. The real-life examples made it easier to relate to those theories.
The material was interesting, current and communicated clearly. However, i did feel that some of the quiz questions were poorly phrased which created confusion. Would certainly recommend it to others.
关于 商业分析 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.