Customer Analytics

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.

( 627 Reviews )

Created by: Eric Bradlow

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Overall Score : 100 / 100

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Course Description

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 decisionsDescribe 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 decisionsCommunicate the history of customer analytics and latest best practices at top firms

Time: 12h

Instructor Details

Eric Bradlow

5.0 Rating
627 Reviews

Professor Eric T. Bradlow is the K.P. Chao Professor, Professor of Marketing, Statistics and Education, Vice-Dean and Director of Wharton Doctoral Programs, and Co-Director of the Wharton Customer Analytics Initiative. An applied statistician, Professor Bradlow uses high-powered statistical models to solve problems on everything from Internet search engines to product assortment issues. Specifically, his research interests include Bayesian modeling, statistical computing, and developing new methodology for unique data structures with application to business problems. Eric was recently named a fellow of the American Statistical Association, American Educational Research Association, is past chair of the American Statistical Association Section on Statistics in Marketing, past Editor-in-Chief of Marketing Science, is a past statistical fellow of Bell Labs, and worked at DuPont Corporation's Corporate Marketing and Business Research Division and the Educational Testing Service.

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Reviews

5.0

627 total reviews

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By Pranita n on 8-Jan-18

very helpful course if you plan to make your career in service sector.

By Shubham G on 3-Aug-17

Probably one of the finest courses to cover basics of Customer Analytics!

By Michal B on 21-May-17

The most valuable course on Coursera!

By Sunny G on 23-Apr-17

Course was very well structured and taught. Content is top notch and is taught enthusiastically and interactively. What I could've liked more: More mentor support, more details into actual models used in industry and how to construct them, and test answer explanations.

By Ã§Â½Â—Ã¦ÂˆÂÃ¦Â¯Â… on 16-Aug-17

thank you for all , this help me a lot. you people are creating new world!

By Nilim P B on 4-Apr-17

Highly recommended for understanding analytic in general

By Nyanyuki O on 9-Jul-17

This course is highly informative and eye-opening. The lecturers are of top-notch quality.

By JC R on 13-Feb-17

Thanks for a wonderful experience. Please make the quizzes answers more about research or the handouts and less about speaker opinion interpretation.

By Jose M on 21-Aug-16

Really Good course. Lecturers are brilliant explaining the concepts via samples which everybody can understand. You may need to have a little bit of statistic knowledge but it is not essential to do the course.

By Howard S on 30-Jan-17