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Learner Reviews & Feedback for Customer Analytics by University of Pennsylvania

4.6
stars
9,568 ratings
2,127 reviews

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

ND

Jan 31, 2019

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!

MA

Aug 05, 2020

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.

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1276 - 1300 of 2,066 Reviews for Customer Analytics

By Kuljeet K

Mar 07, 2017

Good

By Rajshree R

Nov 01, 2016

Good

By Rukal V S K

Mar 28, 2016

good

By Mathew B

Nov 15, 2015

good

By Boitumelo S

Aug 13, 2020

wow

By Charu M

Oct 07, 2019

Cou

By chetan s

Aug 30, 2020

OK

By 吴小芮

Jul 14, 2020

很棒

By RUOXI L

Apr 15, 2019

gg

By 안효선 안

Jul 27, 2020

.

By Rahul R

Jun 10, 2020

.

By DHIRENKUMAR P

Oct 01, 2019

A

By Sergio R F

Jun 06, 2018

i

By Chandrajit P

Apr 10, 2018

G

By Sri H

Nov 03, 2017

Q

By Laurent H

Jun 23, 2017

V

By Douglas M

Mar 02, 2017

V

By Lynda F

Dec 24, 2016

g

By Sanjay S

Nov 18, 2016

.

By Snehal K

Jun 01, 2016

-

By P K S

Dec 15, 2015

C

By Laurentiu B

Dec 09, 2015

G

By 赵丹

Oct 07, 2015

v

By Joel E E

Jun 10, 2020

I want to thank the University of Pennsylvania and the team of professors for sharing their knowledge in relation to the topic of client analysis. I leave my observations at the level of Strengths and Weaknesses from my perception:

STRENGTHS:

1. The course has a certain level of updating in the topics according to the context of some typical companies that are in the international reference, it seems to me that it is necessary to put in the platform others very valuable in this topic

2. The course is more for a basic level - and allows to know the generality of the analytical model in its three pillars: descriptive, predictive and prospective

3. It is a first source to generate a self-training program or to enroll in a more complete program

AREAS OF OPPORTUNITY:

1. the slides have a lot of opportunity for improvement: it is not aligned with the prestige of the University, nor with the marketing theme, the slides leave a lot to be desired, they do not integrate the main models, nor the key concepts, slides of the themes are missing. One as a student has to complete the graphic models and give a structure to the visual presentation

2. There is no parallel between the visual aids and the expertise of the teachers. The teachers are very good, but the visual material is very poor

3. some tools, most of which are only talked about, but the level of support with tools that one can lower is very low. The student has to carry out a double process, follow the course and get tools on his own

4. Some material that is technical, of analysis of numbers, is talked about and no exercise of accompaniment is made

5. The threads of the forums both in the platform and in those that open in whatsapp, are not being managed by a third party as a facilitator. so it is left free to that if someone asks, that both await a response, ie the authority as a university does not follow up to meet spaces of feeding

6. This same exercise of course assessment should be done for each class, that is for each week with an individual level of approach, in other words, there is no congruence between what is given in the subject: to give value to the client /CLV) towards the future is to consider individually that value starting from the individual data, to make predictions and make decisions for the "clients" students who follow are mostly benefited in these courses.

6. I have the doubt if these same comments will really be considered in 2 ways: one: that the University returns to whoever generated them as attention and take them into account for improvement.

Conclusion: I believe that I will continue in the program of the training package that I acquired, but I do not stay yet with being a PROMOTING CLIENT, I hope that the University does something about it, and for my part not only as a student I am willing to support their improvement program.

Thank you

By Daimon V

May 28, 2020

My basic interest of taking this course was to learn more about analytics and I did. I am new into this field and I found it useful to take as I am Sales Manager and it is a trending topic in the marketplace. Having said this, I do think some improvements can be made:

* such as explaining how to compute the R2 in regression analysis (basically two weeks of course are related to it and as it is not explained we missed a basic core knowledge in order to completely comprehend),

*professor Ron needs to explain better his lessons (example #1 he is talking about calculations, however does not show how he did it so we spend lot of time trying to figure out what he is talking about; example #2 minute 6:23 to 7:08 related to WTP, he talks about many calculations and he do not show in the slides how he did those calculations nor draw his conclussions and he moves forward without explaining so)

*Profesor Eric knows a lot and he has a lot of valuable information to share. However, he talks too fast and provides his lessons without clear structure. It is almost like he did not have a clear path while providing the classes so he is mixing examples randomly, going back and forward and at the end you somehow feel a bit confused about this teaching method.

Professor Raghu and Peter Fader are passionated and their teaching methodology is flawless, though quite different among them.

Professors need to answer all questions from students. I constantly review the discussion forum and there are unanswered questions.

Examples provided on week five are outdated. If you are charging in 2020 for it, you should update examples. Otherwise, provide a discount on it as it is outdated and most of five week is about examples.

As a wrap up, it is my first online course ever and I will certainly take more courses from Coursera. Hope you take in consideration my suggestions :)