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.

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

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.

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.

An excellent course to understand the value of data, how companies are collecting and harnessing their data an efficiently applying AI/ML concepts to provide better services and products to their customers.

I really enjoyed the class. Analytics are such an important part of today's understanding of the customer but have other uses even beyond that. Professor Fader has really great insight on the subect.

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!

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.

Although several statistical terms may be confusing underway, a simple Google search can supplement you with understanding them. Other than that, minimal typographical/technological errors may be experienced in the course. All of the professors did an amazing job in mapping out possible points of interest, and did well in explaining concepts clearly. Descriptive Analytics was the standout lesson here that really encompassed various fields and mentioned useful apps to use in real life projects. Meanwhile on the learning side, data analysis is, of course, tricky for those without prior knowledge so although this is deemed as a Beginner-level course, do be ready to Google up some things along the way. Overall, the course is a great path to equipping yourself with managerial skills in predictive analytics through the use of data-driven studies.

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... :)

Really enjoyed this course, the interactive scenarios were most helpful in digesting the information and making it tangible. It’s a great managerial course! Not a math fanatic, and so pleased this course isn’t about performing the math, it’s about evaluating the story the data tells and making data driven decisions. Amazing to have the opportunity to be taught by world renowned scholars at a price I can afford! Can’t wait to get through the rest of the courses and receive my UPENN certificate! Might even get the hoodie to match ;)

Thanks for making this accessible!

This course was an amazing experience. It was very interesting to know how our small activities can have a much larger effect on the company's decisions and product policies. It was given a fundamental idea about the science behind marketing and how data analytics is coherently related to the business decisions. This course has encouraged me to start my learning on data analytics and data sciences too. Thank you all the instructors for coming up with such interesting content with relatable examples and explanations. I hope to complete the specialization.

The course was great. It gave me real great insights that how the data that we have in today's world and in the times coming can positively impact our customer lifetime value, profits, sales, and the overall business just by exploring it properly and then predicting accordingly to optimize and take important decisions. It also taught me the importance of the right model. It gave me a new point of view towards our world by the everything is connected. I got this course on financial aid and I am very thankful for it because this was very beneficial.