You can see that the teachers now what they are talking about... but this seems to be a stripped and then again stripped version of a real class. Some courses at coursera are the entire university classes and you learn a lot from them. In those 5 weeks of this course there is not that much content, so you end up thinking... where can i get more information about each single topic mentioned. References to external resources are pretty weak so far. I've loved the classes, but it each "week" could be a course on its own, with much more content.

Unfortunately I did not feel that this course entirely delivered on its objective. At moments I felt that the number of topics being covered was too large and the scope too broad. Probably the best lecture was week 3, followed by week 2 and week 5. Topics covered should build on each-other in a more natural progression and some introduction of practical examples and actual modeling exercises would allow the learners to try to apply some of the concepts being covered. More examples and tie-ins to real-world usage are a must.

Pros: Concentrated material covered clearly and efficiently. For the limited number of video material (~1/week), there is a lot of basic concepts explained well.

Cons: Few specific examples, which I think reinforce the abstract material presented. I think going though some numbers really drives a point home, and not having examples left me feeling a bit adrift.

Overall: Good information and food for though, but not a lot of actual analytics. Take if you don't have but want experience in this area.

1) Lack of hands on practice with the Buy Til You Die model.

2) The concepts in Weeks 2 to 5 are already well covered in technology blogs and news sites - I'd have liked to see more current material such as 'Overview of Different Types of Marketing Attribution (Heuristic, Algorithmic..), 'Cohort Analyses', 'How Digital Advertising / Programmatic Media works', 'Web Analytics' etc.

3) Hands-on exercises with R or Excel would be ideal.

I found this course interesting. I have just completed my MBA and I found that the course covered quites few topics of what I had learned. It also helped link them better. The examples quoted from companies that are implementing analytics was helpful in understanding how it could be implemented effectively.

One of the suggestions I would have is to include hands on implementation of some of the analytics tools that could be used.

I really enjoyed lectures by Prof. Iyengar and prof Bradlow. They were very helpful in understanding the basics and the applications. I also like Dr. Peter Fader's approach of teaching a concept though a story. I hope Dr. Berman can innovate and come up with more interesting ways to hold the audience and teach the concepts as currently sitting through his lectures is quite a task.

Classes were interesting, although a bit light. I would also have liked to have more explanations on the quizzes to make sure the material was fully understood. And reading references would have added to the experience. It felt a bit like the class was kept basic in order to make the corresponding "specialization" package more attractive. Slightly disappointing.

Predictive Analysis (week 2) and Application / Case Studies (week 4), were the best part of the course, and I genuinely learned things that I will try to implement in my small family business. However, Weeks 1 and 3 were highly disappointing (to put it mildly). Maybe I was expecting something more concrete or advanced, but the material provided was too basic.

The part on predictive analytics and the case studies are actually very good. The other two ... not so (and I stop here). Overall the course is too easy, unnecessarily spread over 5 weeks: e.g. week one and two are material for 2 days. Whilst successfully demonstrating the benefit of CA, the course never enters the nitty gritty of how to.

They didn't teach badly per se, but much of the information was WAY too basic compared to what I hoped to learn. The Marketing Analytics course from University of Virginia teaches a set of skills to use for marketing/customer analytics, whereas this course only briefly describes what could be done in marketing/customer analytics.

Great qualitative overview but thats where the good parts end. I wish they actually teach you how to do the math part. It would be a perfect course if we can work on case studies and calculate customer life time value and RFM. This is definitely great course if you have no idea of customer analytics or you are in executive level.

First 2,5 weeks are incredibly boring and really hard to listen to. I almost dropped out because I hated the thought that I needed to listen to these lectures. Thankfully starting week 3,5 the situation improved significantly and the contents became relevant. Really liked the last week lectures and the way the quiz was designed.

In general terms I think the course is very useful to learn and understand basic concepts around customer analytics field, with the latest platforms, studies, etc within this field.

However, I was expecting to get a little bi deeper into the concepts, with more complex analysts regardin what firms is doing nowadays.

The most interesting part were the examples at the end. I think the course would have been better if the last week's material was at the beginning. Also, more assignments would be appreciated. I find the information interesting and resources helpful, but I would like practice and some guidance on its application.

The course provided exposure to some of the new topics and techniques in Customer Analytics. Most of the video lectures were exciting but too short for any "major" in-depth learning.

Course can be improved by adding some rigorous assignments and an improved list of additional reading materials.

Kudos to the team!

As a beginner in the area, this churse was a good choice. I think I got a pretty good overview of the issue, unfortunately only on a theoretical level. I would rather more practical examples that students have to analyze themselves, try to decision which models want to use and than discuss their decision.

The course brought to me lot of insights on data, data exploration, predictive analytics and prescriptive analytics. The broad definition of the terms have been understood and few example have helped to know the subject. However, even more in-depth knowledge and study material should have been provided.

Definitely a lot of useful information. I had a little difficulty with some of the tests. I think I would have done better had there been some exercises to help bridge the concepts to application. Also, some points were tested, and it wasn't clear that those points were so necessary to know.

A large gap between the presented oversimplistic modeling approaches and the presented applications. I would expect more "meat" in between. The applications part was nice, the regression and predictive part a little too basic, and the prescriptive part not really worth the time.

The contents are quite theoretical. It could be improved by adding more practical examples.

I don't know if it is just me, but the sound for this course is too soft that I could not hear clearly through built-in speaker. Nevertheless, it works just fine with a headphone.

I did not find the structure of the course useful. Also even though there were a lot of examples (some of which were quite lengthy) I wish they went a bit deeper into the math behind the models.

Quizzes seemed to test your memory more than understanding of the material.

Comenta sobre uso de dados mas não traz exemplos de data-sets, como analisar informações coletadas ou mesmo como coletar os dados. Modelos apresentados são básicos.

Uma ótima introdução para aqueles que não entendem do assunto, porém superficial para cientistas de dados.

If you are looking for an overview and have not had much exposure so far, this is a good course. If you want to go deep, it will not be sufficient for you. I would prefer a deeper dive with more examples to work with. But still this is a good start.

Not bad, most of the times boring because there were no real examples and scenarios. The professors are knowledgeable and should deliver that to us even though we pay waaaaay less than Wharton students who are fortunate to have rich families...

Very interesting course but I missed more detailed information on the presentation slides and additional reading papers. It is very helpful to introduce initial concepts about customer analytics but it misses the opportunity to go dipper on...