Comentários e feedback de alunos de Análises do cliente da instituição Universidade da Pensilvânia

Professors are great, especially Mr. Iyengar Just one improvement suggested that to be more clear when speaking as the professors teach a whole lot of things but everything comes in the exams in twisted form as it takes a lot of time to understand the things taught and answering it in exams.

It's both useful and interesting to see how analytics can be leveraged in marketing practices. I hope this 4-week course could be longer and introduce more assignments of interactive types rather than simple choice questions. Anyway, thanks to three insightful professors from Wharton School!

Thanks for such an amazing course to drive down the knowledge in very specific manner and being concise with the definitions, models and examples. More recommendations in reading part would actually get me learn more insights about the topic as I'm a newbie. Thanks a lot for this !!!

In the quizzes I would prefer to have at least one numeric problem to solve (i.e. a simple regression model), for the sake of students, that are not aware what is regression (as in this course it is just briefly talked about), to learn how to define a model and to solve it.

My 2 cents

Learnt a lot in this course. Really good examples to make you understand the theory and its application. But I think the videos were made in 2012 and some of the concepts cannot be put to practice now but it definitely lays a strong foundation for your marketing analytics endeavor.

The course was very fruitful learning experience with very obtrusive knowledgeable content in slides, which gives you deep understanding of customer analytics trends in real world time. However during few lectures the speed of teaching was bit fast. Overall it was good experience!

The module taught by Professor Peter Fader needs more emphasis how he came up with the model, and the material he teaches does not cover much of the quiz questions. I enjoyed Eric Bradlow module the most, which was pretty much based on real cases and applications in today's world.

It is a great course, and would recommend it to anyone.

A little more in depth explanation in terms of the various calculations / formula's used throughout the course would have been beneficial.

But overall a great course to take, specially if you are running your own business.

Had some really great examples of actual companies and their usage of analytics, as well as some basic concepts. The instructors are knowledgeable and passionate about analytics.

I wish there was a bit more in the way of assignments that used the formulas taught in the class.

This class was very informative and made me think critically. I learned a lot of new skills. My only concern with the class was that some of the test questions seemed to be very "hidden" within the information provided and didn't seem to be the "main points" of the class.

The course is good for introductory understanding of some concepts. Some quiz questions were a bit tough esp. the ones from Peter and did not appear from the course. I recommend this course if you its been a while since you did a graduate or undergrad business course.

There's a lot of discussion around what customer analytics is but not a lot of practical application to implement. I know in the beginning it said the course wouldn't be a lot of in-depth research, but the knowledge I've learned from this is extraordinarily high-level.

Theoretical part of the course is fantastic! Everything is explained nice and clearly. I wish there was more practical use of knowledge involved.

I have always dreamed to do MBA at Wharton Business School and thanks to Coursera I am one step closer to my dream school.

Thus far very informative, I'd give it the 5th star if it had had more practical content and maybe more case studies to work at and apply the knowledge acquired. In any case it opens up many more options to work with customer data and provides very valuable insights.

This course deals with what are the different types of data available and how to collect them and analyse them from the scratch. But could be better if they teach how to do programming atleast with excel so that the regression models and all can be easily understood.

Well thought out course - great start for beginners as it equips you with foundational knowledge. But, since the knowledge has a great depth to it, it makes it even more valuable for those looking to take these foundations and apply them in a more advanced manner.

The course is very useful and surprisingly easy to follow and understand. However, I felt sometimes the lessons and literature was too simple for the complex issues/subjects that are taught. Some more supporting literature would drastically improve the course.

The course content was good. The right level that I was expecting.

However there are some areas of improvement.

1) Some of the explanations were 'incomplete'. It felt like the math was skipped at times.

2) The right answers to quiz questions are never displayed.

Interesting and well planned course to get started in the concepts of customer analytics. Good examples and explanations, useful, simple and accessible. You learn to understand how to face the first steps to perform customer analytics and focus on data models.

It is good in general and it covers quite a lot os aspects. Nevertheless, It is very basic at first if you have basic business knowledge. By far, the last week with Eric Bradlow is the best.

By the way, the indian professor speaks too fast for me to understand.

Very interesting and very insightful. Before I took this course I thought I was going to analyze huge datasets using R or Excel but it turned out not to be so. The course content is solid but personally I think it must be fused with some real data analysis.

Great Introductory course. Tests, in my opinion, were not the best. For Example in week 3 there was a question about attribution problem. The attribution problem was not covered till week 5. I also could not find some of the answers to the questions asked.

A good course that will be useful for anyone looking to understand more about business data.

I wish the instructors walked through the regression models a little more to show how to make estimates when there isn't any existing price or quantity data points.

It's very helpful when the professors lay out a model and then a use case to follow. Predictive Analytics with Peter Fader was hard for me to follow, it felt less analytical and more abstract. Otherwise, it laid a great foundation for customer analytics.

Solid overview of customer analytics and how descriptive, predictive and prescriptive analytics interconnect to support firm-level decision making. Content not overly difficult. Challenging quizzes required reflection and thought, vs regurgitating content.