30 de jan de 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!
4 de ago de 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.
por Emem M•
2 de jan de 2019
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.
por Prashanth R•
30 de ago de 2016
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.
por Sofya A•
16 de jan de 2020
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.
por Oscar C•
2 de abr de 2020
The information is good, the professors are good, but the innovation of the methods and the point of view i think that is not on a high and actualizated level and the conclusions are so normals. I hope the next formation blocks will turn on another point of view on me. In all cases, thanks for all, i'm so happy for this.
por Ulisses P•
9 de dez de 2016
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.
por Vanol F F J•
1 de ago de 2020
The most interesting part was 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.
por Rajat T•
22 de mai de 2016
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!
por Lenka M•
26 de ago de 2019
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.
por Kaushik C•
6 de nov de 2019
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.
por Dedrick S•
27 de jun de 2016
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.
por Boris L•
5 de out de 2015
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.
por Koustav D•
30 de mai de 2020
The course is informative and the same time quite challenging.
However the main reason behind giving a three stars would be:
1) No quiz at the end of each lesson
2) No hands on experience
3) You need to grasp the concepts at one go or else you will end up failing in the test
por Voravich C•
21 de nov de 2019
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.
por Ekaterina T•
18 de mar de 2019
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.
por BRUNO L P•
27 de out de 2017
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.
1 de jun de 2020
The flow of the course is adequate, but some questions of the quizzes were not fully discussed in the lecture slides or material. In some other cases, I would appreciate if you could include the complete procedures of the models mentioned in the lecture slide deck.
2 de mai de 2020
Overall is good content. I like Eric most!
The quiz part is not ideal - it does not show the explanation of the questions/answers, which is somehow frustrating to know the reason behind the answers. Additionally, the subtitles of one of the courses are not correct.
por Amol B•
10 de jul de 2020
The information provide by the faculties is really insightful for a person having no marketting background. One gets to learn lots of new things. However, i feel the slides and probability model in predictive analytics can be explained in a better way.
por Martina F•
4 de dez de 2016
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.
por Shawn E•
15 de out de 2022
The professor speaks to fast and with his accent it is a little difficult to follow or understand what he is saying. Also, I feel that he needed to offer better explanations to the concepts rather than assuming the student knows the new material.
por Bojan B•
6 de fev de 2016
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...
por Guilherme B P•
16 de ago de 2018
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...
por John L B•
21 de nov de 2016
Overall this was a fairly interesting course, but some weeks were much more engaging and challenging than others. I really enjoyed the challenge of week 3, but unfortunately it was followed by week 4 which was not engaging and lacked content.
por Lisa M•
13 de ago de 2016
Good introduction of topics, but it did assume some working knowledge of the topic. Some of the quiz questions did not seem to have any supporting material information in the course, making trying to determine the right answer frustrating.
por Stephanie P•
23 de jan de 2023
Solid program - not sure how to apply everything in a service based industry (management consulting firm). We do not have a "product" we "sell" our expertise and it was not clear how to use some of the recommendations in our environment.