a broad but very usefull introduction in number crunching: you will discover methods and techniques that you can learn to improve the quantitative approach in your company

I think the information on this course is presented really well, and it is a good way to learn about the terms and different information sources, but it is a bit outdated

Very useful course to understand the customer analytics. The course curriculum is beautifully designed.

Expecting more of application based examples in the video lectures.

Very good explanation of the basic concepts and marketing practices in data analytics.

Would have been much nicer to work on some practical models on excel with big data.

I loved the whole course generally and best was "Applications". I would love to see some more math and models applied to the real world, in small and large businesses.

Very good course for beginners in this field. I would have appreciated more if there was more maths involved in this course as many topics are not explained in depth.

A practical course filled with business acumen. Learn the nuances of Customer Analytics from Wharton School. A few case studies can make the learning more effective.

The course was ideal to give the student insight on what they can focus to improve productivity and efficiency of an organization. I am grateful for the opportunity.

This course has been very useful to me. I have a much complete idea of what customer analytics means. Also I feel more confident abour business analytics as a whole.

The course is a great introduction to customer analytics, but no more than a introduction. I would have liked to see some better and deeper examples and aplications.

Very interesting coarse with good information for anyone not familiar with customer analytics. My only suggestion would be to update some of the data to 2019/2020.

It was quite interesting to know the modern customer retention and predictive strategies used by big firms.Thanks to all the professors for their valuable efforts.

Course is not at high level nor low level , it helps the students to approach level by level with difficulty . Most of the real time examples are worth ! Thanks !

Topics were pretty interesting an very well explained in simple and concise manner. More detailed step-by-step explanation and illustration may be helpful though.

If the professor could give more maths insights and mathematical deductions on his paper, I will definitely give 5 stars!! Really a nice introduction on customers!

Interesting and insightful course, but too much theory. Some practical sessions with hands-on calculations would have been great to manifest the learning content.

Would have loved to understand the calculations behind the probability models in the predictive analytics section, giiven that this is a beginners level course.

The lectures are great, I have been imparted a lot of knowledge, and like Mr. Eric said, it's not just because it's good to know, but it will have applications!

A lot of concepts to learn and a high level of abstraction that sometimes is difficult to comprehend. Sometimes I missed some hooks to illustrate the concepts.

Amazing coursework for an all-round knowledge about marketing analytics and how is it used by the industry. I hope to do an advanced course soon on this topic.

I followed the course to learn more about RFM models. There's a nice introduction to it, but it's not covering this topic in depth. Still looking for more now.

Really like it, it is helpful too, except that some slides can be a bit too wordy + boring. Try to use different types of media in terms of teaching please :)

It was a great experience, well paced and the subject matter was clearly explained. It could use more, deeper content - it feels like scratching the surface.

Very intesting introduction to Customer Analytics. My first Coursera course but will definitely want to complete other courses of University of Pennsylvania.

All the slides were filled with information. Still my favourites is Eric Bradlow as he connects more by giving more indepth examples which we can relate to.