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.
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!
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por Joel E E•
I want to thank the University of Pennsylvania and the team of professors for sharing their knowledge in relation to the topic of client analysis. I leave my observations at the level of Strengths and Weaknesses from my perception:
1. The course has a certain level of updating in the topics according to the context of some typical companies that are in the international reference, it seems to me that it is necessary to put in the platform others very valuable in this topic
2. The course is more for a basic level - and allows to know the generality of the analytical model in its three pillars: descriptive, predictive and prospective
3. It is a first source to generate a self-training program or to enroll in a more complete program
AREAS OF OPPORTUNITY:
1. the slides have a lot of opportunity for improvement: it is not aligned with the prestige of the University, nor with the marketing theme, the slides leave a lot to be desired, they do not integrate the main models, nor the key concepts, slides of the themes are missing. One as a student has to complete the graphic models and give a structure to the visual presentation
2. There is no parallel between the visual aids and the expertise of the teachers. The teachers are very good, but the visual material is very poor
3. some tools, most of which are only talked about, but the level of support with tools that one can lower is very low. The student has to carry out a double process, follow the course and get tools on his own
4. Some material that is technical, of analysis of numbers, is talked about and no exercise of accompaniment is made
5. The threads of the forums both in the platform and in those that open in whatsapp, are not being managed by a third party as a facilitator. so it is left free to that if someone asks, that both await a response, ie the authority as a university does not follow up to meet spaces of feeding
6. This same exercise of course assessment should be done for each class, that is for each week with an individual level of approach, in other words, there is no congruence between what is given in the subject: to give value to the client /CLV) towards the future is to consider individually that value starting from the individual data, to make predictions and make decisions for the "clients" students who follow are mostly benefited in these courses.
6. I have the doubt if these same comments will really be considered in 2 ways: one: that the University returns to whoever generated them as attention and take them into account for improvement.
Conclusion: I believe that I will continue in the program of the training package that I acquired, but I do not stay yet with being a PROMOTING CLIENT, I hope that the University does something about it, and for my part not only as a student I am willing to support their improvement program.
por Daimon V•
My basic interest of taking this course was to learn more about analytics and I did. I am new into this field and I found it useful to take as I am Sales Manager and it is a trending topic in the marketplace. Having said this, I do think some improvements can be made:
* such as explaining how to compute the R2 in regression analysis (basically two weeks of course are related to it and as it is not explained we missed a basic core knowledge in order to completely comprehend),
*professor Ron needs to explain better his lessons (example #1 he is talking about calculations, however does not show how he did it so we spend lot of time trying to figure out what he is talking about; example #2 minute 6:23 to 7:08 related to WTP, he talks about many calculations and he do not show in the slides how he did those calculations nor draw his conclussions and he moves forward without explaining so)
*Profesor Eric knows a lot and he has a lot of valuable information to share. However, he talks too fast and provides his lessons without clear structure. It is almost like he did not have a clear path while providing the classes so he is mixing examples randomly, going back and forward and at the end you somehow feel a bit confused about this teaching method.
Professor Raghu and Peter Fader are passionated and their teaching methodology is flawless, though quite different among them.
Professors need to answer all questions from students. I constantly review the discussion forum and there are unanswered questions.
Examples provided on week five are outdated. If you are charging in 2020 for it, you should update examples. Otherwise, provide a discount on it as it is outdated and most of five week is about examples.
As a wrap up, it is my first online course ever and I will certainly take more courses from Coursera. Hope you take in consideration my suggestions :)
por Martin G•
This course gives you a basic understanding of what Customer Analytics is all about. In that regard it delievers just what you are promised in the beginning. What you need to know is that some of the course content dates back a few years. So don't expect up to date materials. At the same time of course one has to say that basics don't run old, so for a basic course that's ok.
It helps however if you already have a basic understanding of statistics. There are a couple of slides and models that will fall easier into place with you if you are at least a bit used to statistics. Not saying that it's impossible to pass this course without it (not at all), but if you really want to understand what is explained, the videos simply won't be enough. Again: That's ok for a basic course, because it has to start somewhere, and you can't teach on a certain expertise level if you have to start from scratch. Just be prepard that if you take this course you will come across a couple of results of data calculations where you might ask yourself where these results are coming from. The ansers to this questions are in some parts up to you to find.
All in all the videos are very intersting and (apart from the calculation and statistics stuff) easy to follow. In some part it is even entertaining - and that will probably will ignite further interest in Customer Analytics. At least that was the case with me.