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Learner Reviews & Feedback for Customer Analytics by University of Pennsylvania

4.6
stars
11,895 ratings

About the Course

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...

Top reviews

AA

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.

PJ

Feb 2, 2020

The course is very good. I have learned a lot from the course. A lot of interesting topics and help me to under the marketing. I will for sure continue learning more courses from this specialization.

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2226 - 2250 of 2,537 Reviews for Customer Analytics

By Asif S

•

Apr 30, 2020

informative

By Arnab G

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Jun 8, 2018

good course

By Robert B C

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Sep 29, 2015

Good course

By Cesar E G M

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May 13, 2020

Buen curso

By Eiman N

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Sep 5, 2024

excellent

By Carmen B

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Nov 6, 2023

Too short

By Adam D

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Sep 27, 2021

Thank you

By Khurram S K

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Mar 25, 2016

Helpful!!

By Gourav S

•

Aug 8, 2019

Good one

By PARK K B

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Sep 9, 2020

success

By Joshua S

•

Apr 29, 2019

Amazing

By Nazatul A B A R

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Nov 4, 2016

awesome

By Alvin L

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Mar 16, 2016

Great!

By Pablo H

•

Aug 1, 2024

great

By riyanshi j

•

Dec 2, 2021

nice

By waseem s

•

May 1, 2020

tttt

By yash t

•

Apr 28, 2020

nice

By 马雨禾

•

Nov 17, 2019

easy

By Yash D

•

May 31, 2019

good

By thulasiram .

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Sep 11, 2016

good

By venky s

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Mar 2, 2016

good

By M.Hymavathi P

•

Jan 16, 2018

g

By Govind R A

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Aug 1, 2017

F

By Javier C R

•

Jan 22, 2025

I really enjoyed the first modules. I found the information given and their applications really interesting and engaging. Modules 4 and 5 I was almost unable to pay attention to. Why? A couple of possibilities come to mind. Firstly, I felt like a lot of the information given was too specific to the cases discussed but gave no generalizable lessons other than what they said in the introduction. A second reason may be that, at a personal level, this matter is not as interesting to me, or practicable for my case and, since I couldn't see the use I just couldn't come to listen or find value in whatever I listened to. Still, the fact is that I made the effort to pay attention at the beginning, and after a couple of videos without finding anything worth annotating, I disconnected.

By Hemant M

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Jun 10, 2020

It was a good hands on basic Introduction for Customer analytics. However The introduction of descriptive,predictive and prescriptive analytics was mixed with marketing so the amount of time that could be dedicated to marketing was dedicated to introducing analytics. This course was more general knowledge and E-Commerce rather than marketing. I wanted the course to be more specific: How marketing theories help in building predictive models and What a marketing analyst knows that other data analysts don't know. If you are an absolute beginner in analytics, give it a try. Otherwise it may be too simple for you.