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

Great introduction to concepts. I value these courses because they hold the potential to optimize education and provide skills that will be necessary and essential for today's and tomorrow's markets.

In 3rd week Video ,there is less content.Also some question cant be answered though there is no explanation given in video syllabus(Questio_ Genuine data mining Technique) as asked in assignment

This my first course on Coursers. It has been a wonderful experience learning Customer Analytics From Wharton Business School. I gained a lot insights on how Customer analytics work in real life.

Interesting look at how analytics can be used at the individual customer level. Not intended to help participants do the actual data work, but good for providing awareness about what is possible.

The first lecturer sounds boring, but the quality of other lectures is increasing. I enjoy the last lecture most where I can see the real value of analytics in business. Thanks for a nice course.

Good course, however very theoretical, but i guess thats the objective, to give an overview into Customer Analytics. It would be good to have the quizzes a bit more quantitative than Qualitative

It was great, but the last week went pretty fast. Too much information and I felt there wasn`t enough analysis to understand better the situation. But overall, it covers pretty good the subject.

The undoubted plus is comprehensible for learners content. A big thank you for that!

But in my opinion course is also too abstract, it may be better to give more practical examples of data usage.

I got a broad view of basic business analytics, which is great. But some of the quiz is not that relevant to the lectures. I was confused by some of them. But for the overall course, not bad.

The course is good, but could be improved by adding more structure to the content and by correcting the tests. week 2 and 5 tests have questions that weren´t explained in the videos/readings.

I have two comments

The prescriptive analytics content is very weak. Also the quiz for predictive analytics contains questions not covered in the content (eg. diagnostic on a model's validity)

Was really interesting...but the predictive Analysis part wasn't well detailed, the clumsiness was something else. I mean the illustrations and all. But all the same,it was really impactful.

I found this course productive and useful. Highly recommend it to people who are interested in learning 21st-century marketing. Thanks to Wharton School and Coursera for creating the course.

I learned new information on how to look at customer data and evaluate customer loyalty. I am not sure how I will use this information, but it may be valuable in models I may need to build.

Course provides the essential information on the topic from a top level, providing a broad range of knowledge, however it doesn't go into depth as to how to execute the models discussed.

Good eye-opener for the theme. Definitely a starting point for either people interested in pursuing this career, but also for consume to better understand the business world around them.

This course was very insightful and informative for the understanding of what to look for (types of questions to investigate) and how to go about constructing the data on our customers.

It was a very good course with valuable aspects to learn and explore. All the professors were very fine in sharing the information especially Prof. Iyengar.

All together worth the time.

We need to work more on the information flow through the lectures, students can easily lose track (except, the fifth week was great in reiterating the outline).otherwise great material

This is a very useful program to understand the basic concept. Faculty explanation was crisp and easy to understand for beginners. Expecting more such courses but at an advanced level.

Was useful study. Would be great if more in depth data set models covered by any of the professor with real life case, by applying techniques likes RFM models, Market Basket Analysis.

It was a great opportunity to study on Customer Analytics. Though I have read some techniques during my under grad study but I was not aware that when and where to apply these models.

Would have liked to see more quantitative parts!

Maybe for next time an assignment where we get an excel sheet and we need to identify ourselves which customers are the most profitable

Great amount of theory was covered, only the PREDICTIVE one was going over the head, but was able to google and map the concept/context and understand.

Thanks you for this.

Babuprasad

I'm a non-business major student and I find myself learn some interesting theories and facts through this course. Though I hope there will be more technological contents included.