The course talks about various techniques and methodologies. But does not get into details. For example, churn analysis. They talk about churn analysis but does not get into the details on how to perform a churn analysis.

Theoretical

Good as an introductory course for customer analytics.

If you are completely new to analytics in general, this might be a good course to start with. However, if you have some prior exposure, you might not learn anything substantial. This was supposed to be a five week course, but I was able to complete it in less than seven days.

How this course can be improved:

I wish that the course included more quantitative elements. I wish that the course included some assignments for the students to actually develop and run some models.

Good survey of the topic but only focused on B2C. If that were my focus, I'd give it a higher rating. I was hoping for insights on B2B as that is my field, even if only a short video to address differences/similarities/peculiarities.

Wow! This was so insightful into how our social media and daily habits are used. I don't like feeling like a sheep, so this awareness is appreciated. I'm still trying to design how I could apply this to my Trade.

Amazing course for even beginners in the field of customer analytics. Highly recommend to do this course for enhancing the analytical skills. Examples and case studies explains the concept very well.

Insightful and a great introduction to a very complex topic. Probably would recommend having a grasp of statistical analysis before starting (not required) as it would help understand some of the concepts better.

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!

Perfect Course for those who want to inquire insight and knowledge of how tons of data that we generate in our day to day life is being utilized by big organizations in optimizing their productivity.

Brilliant Course !! Loved going through all the materials and the lectures !!

Very Detailed course on Customer Analytics. And it presented quite a few case studies too, to understand the concepts better. But I felt that a hands on experience of applying Customer Analytics to a problem in a step wise fashion would have cemented the knowledge gained by this course.

I would like to hear more about models especialy predictive one but all the things about models are bullshit. They generaly talk about demand curve which is a lesson of a economics more than customer analytics. They should choose more appropriate example. Moreover, I expect to see at least the type of models and where it is used generally. It was a waste of time. That's why I am not gonna take other modules. Adios !

Hi,

I have enrolled into the Curriculum with aspirations of becoming expert in the field of Business Analytics. So, frankly, I took a calculated decision/question/probability regarding how much it would be beneficial and how much I will be knowledgeable by the time I complete the certification program.

Now that I just completed my my very 1st course, Customer Analytics, I got answer to my question that my money, my time and efforts I have put is ABSOLUTELY worth and more than that I become knowledgeable in the domain.

Especially the respected professors Mr. Iyengar, Mr. Peter Fader, Mr. Eric and Mr. Ron have explained each concept in a very vert understandable way. The way or the navigation, introduction to the subject, the problem, explanation, breakdown of the solution and conclusion and their applications with business cases and scenarios are too good.

Now, I feel very confident and CAN confidently say that my basics, foundation in Customer Analytics are very strong and I can apply them to any tool, any scenario, any domain and for any problem in a any situation.

Thanks to my Professors.

Regards

A very interesting module emphasizing the importance of meaningful data, how to use it for predictive and prescriptive customer analytics. The insights into customer behaviour and how marketing has evolved to the present form of the all-encompassing digital marketing and how to use it for customer analytics has been very revealing. A combination of online and offline marketing is the way to go in future. I can look back in retrospect and just wonder at the number of customers with Indian banks who would not pass muster on any predictive model. While analytics was still at a nascent stage in Indian banks when I retired, I still feel that even where predictive models are used, there is hardly any follow-up action. I saw the hallowed halls of Wharton for the first time and really hope to see them in person at least once.

Highly recommended. Delivered by leading faculty for the Wharton school, we are first shown what exactly customer analytics is. The approach from the Wharton School is to look at each individual customer (or rather group customers according to their habits and demographics). We are shown the three types of analytics: descriptive, predictive and prescriptive. The predictive week delves into regression analyses, but at a high level. Very interesting is the Buy Til You Die probability model, which seeks to model how past customer activities will translate into future lifetime value. We also look at profit maximisation (MR=MC), and conclude with some real world examples of applying these techniques for profit in the real world.

Overall, an excellent primer.

Content: 10/10

Presenters: 10/10

Presentation: 10/10

A great course. I was hoping to get a deeper dive by working on some case studies where I get to estimate CLV and customer using some statistical models and make some recommendations. Perhaps this will be part of the capstone project. I see a lot of value in using this to do intangible asset valuations such as customer bases. Using CLV analysis may enable me to ascribe a value to existing customer bases of an acquisition target and also estimating possible churns of these customers. Such analysis can be useful when planning the integration of the acquisition target and also for purchase price allocations where the purchase price is allocated to good will, intangible assets and tangible assets in the financial statements

I have really enjoyed this course. I did my MBA in marketing around 17 years back and have been working in the finance function for the last 15 years or so. It was really nice to refresh my memory on marketing strategies and tactics, but the most important thing I learned was how marketing concepts are changing from mass to an individual. It is happening all around me right now and it was very exciting to see how it works. I hope I will be able to share this knowledge with my marketing colleagues and ask them to do more of individual marketing through Customer Analytics. Thanks, Corsera & Wharton team for providing us with this wonderful opportunity.

This is a well thought out course with exposure to concepts and principals in customer analytics that are disrupting and re-shaping the retail and on-line world today. Whatever your perceptions of customer behaviors, be prepared to have everything turned on its head. And then to predict what the individual customer will do with actionable data... Priceless! The Wharton team is well prepared and enthusiastic about teaching customer analytics. This is the future of retailing, and as an executive, an understanding of its use and purpose will be necessary to lead an effective team or organization. Thank you, Wharton.

Great intro to descriptive, predictive and prescriptive. Good simple excel examples. Quizz questions are convoluted at times IMHO and I am PhD. (not talking about the anti-regurgitation questions. I liked those.) It hard to make quizz questions to really test knowledge... KEY concepts RFM, NPS, regression. missing: correlation matrix perhaps. would like to see a full case such as capital one or UPS. review of industry tools in descriptive was useful. Cool that you show the campus... This is my desk, this is my backyard where I had this aha moment, here is the cafeteria... :)

Excellent course material and very simply put together lecture. The pdf continuity is incomplete without listening to the AV of the lecture. It is very akin to physically attending a live lecture. Excellent resources with indepth and professional approach, suiting the SOP s in the real commercial world.And can be immediately adapted to practice. A well thought blend of the current SOPs with the course material can bring about customized solution for all the sectors, especially the service sector where customer satisfaction equals to quality

I really enjoyed the module. It was brief but opened up new perspectives nonetheless. I love the flow and structure of the course. Every professor was concise and great teachers - I personally found the summary at the end of each week's module particularly useful. I also want to say thanks to Prof Fader and Prof Bradlow for their impassioned lecture modules. It was such a great privilege to be able to be part of this Customer Analytics module on Coursera offered by the Wharton School.

Cheers, Koey, from Singapore.

This course of customer analyticis is very useful for all those involved in the decision making of a company, as it allows you to solve problems from the calculation of optimal prices, determine the cancellation of a membership among other practical cases.

For this it is based on a methodology of five points and is based on subjects such as economics, marketing and statistics.

As an economist I highly recommend this course if you wish to learn how to analyze and solve a problem in the information age.

Great content, besides week one, all the tests are challenging. The only problems I see is that the last time the staff answer a question was three years ago, the peers/network aspect could be better and also some of the more difficult part of the content was not really explained (they actually give you directions if you want to have a deeper understanding, still some question on the quizzes were about those subjects). Nonetheless, i found it amazing and quite practical.

It is a inspiring course where people get some ideas on where to start on analytics in marketing. The idea provided in the course is also interesting. Good for those who are new to marketing with analytics. Upon completion, I would like to get some statistics courses to bring my ideas into real testable experiments. Besides, the session introducing the study on measure corporate value with their customer values is also inspiring. I do love this course! Thanks!

Last lecturer was the best -- most engaging and exciting. Regression was easy (but also glossed over) much more could be said there.

The dean lecturer (with the Mary/Sharmila example) was good too, but there was a little racial bias at making Sharmila (the black female sounding name) the customer who was likely to churn.

This seems to me to be the most exciting all the 4 types of analytics. I would definitely take a whole course based on just this topic alone.