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University of Pennsylvania

Customer Analytics

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

状态:Predictive Analytics
状态:Business Analytics
课程小时

精选评论

PK

5.0评论日期:Feb 5, 2019

Provides very good overview and understanding of cutomer analytics, how to collect data, measure, predict outcomes and what techniques to use in different scenarios. Highly recommend for beginners.

JB

5.0评论日期:Mar 23, 2021

Excellent for learning different types of analytics, the different tools, learning which type of analytics and tool to use in a specific situation. Furthermore how to implement analytics in business

JL

4.0评论日期:May 9, 2019

Good intro to the course. Would like it if the course had more use cases or technical skills taught, just so we can use the knowledge learned in real life situations. But the overall course is great!

SS

5.0评论日期:Nov 14, 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.

ZH

4.0评论日期:May 31, 2023

enjoyed the lectures especially from Fader and Bradlow, wish the course had more details on model construction and data analysis but i guess they do not fall into the scope of an introductory course

SJ

5.0评论日期:Oct 15, 2017

This course is designed with highly skilled faculties. The way they explains carry a lot of meaning in small format. One may easily understand without having any prior knowledge of this whole area.

EG

4.0评论日期:Apr 27, 2022

W​ell, this course is like a front page of Wharton for coursera users. At the end of the course the only thing I wanted was enroll in Wharton College, crazy idea - it very prestigious thus costly.

AD

4.0评论日期:Dec 3, 2017

In 3rd week Video ,there is less content.Also some question cant be answered though there is no explanation given in video syllabus(Questio_ Genuine data mining Technique) as asked in assignment

GL

4.0评论日期:Jun 5, 2020

Good course for starting to know the important of data and how to manage that into customer development - customer analytics. The presentation really clear combine with explanation from the lecturer.

AA

5.0评论日期:Apr 5, 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.

DM

4.0评论日期:Jan 18, 2018

Great introduction to concepts. I value these courses because they hold the potential to optimize education and provide skills that will be necessary and essential for today's and tomorrow's markets.

KV

4.0评论日期:Jan 31, 2016

The undoubted plus is comprehensible for learners content. A big thank you for that!But in my opinion course is also too abstract, it may be better to give more practical examples of data usage.

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