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

The course gave a deep insight into the exciting world of customer analytics. It is not a thing of the future but it is actually happening now and the course helped me to understand these concepts at their very simplistic yet most appreciable form. The course tutors were extremely well versed with their topics and the lectures were having a mine of information which required me to refer to the course slides many times over as each time I discovered a crucial bit of insight which I missed earlier. Overall it was a great learning experience, one which would help me to at least take the first courageous step and start implementing some of the basic analytic models I learned in this course in my present job roles and responsibilities.

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.

THANK YOU!

This course was very informative and with today's digital arena I am very grateful I took the class!

BUT, I almost didn't pass, because it was so difficult in the beginning - I did not know nor did I see a "prerequisite" listing for the class. So I stopped at week 4 and began "Introducton To Marketing", passed that course and then came back today, the last day to finish "Customer Analytics", and finished with a 92% grade!

I have found that printing info ahead of time and following along with the instructor's, making personal notes was THE BEST WAY for me to learn!!

Thank You to all the lecturers for an awesome job!!!!

The Customer Analytics course gives great insight into the world of firm-customer relationship. This course will expose learners to multiple ways a firm can probe into its customer data, help learners understand the possibilities that an immaculately dissected customer data can offer, guide learners to find penetrative insight in a sea of historical customer behaviour data, et cetera. The course is delivered in a very structured way, and the instructors keep students engaged with some interesting examples. If you'd like to learn about the potential that a set of customer data can offer, I'd definitely recommend this course.

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.

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

Great Course, even though some of the videos have some year now. I would be an added value if could add some case of studies in deeper development of the Predictive model, Optimization and Decision to make. I find the extra material (as the paper "probability model for customer base") outstanding even those material has awakened of my desire to look into the predictive model refresh calculus and statistical for better understanding. still, a have some problem to implement the CLV formula ... looking forward to the next course

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.

This course was very informative and in detail. It is beginner friendly and gives insight into how to turn in potential customers at the same time making profits for a firm. This course thought me how even the slightest changes in any configuration of a business model can have a huge impact on the firm. The last few lessons of the course were my favourite! We got to look into real time examples and how different organizations took up different marketing models to bring in profits.

This course was phenomenal which gave overview of exploratory, descriptive , Predictive and Prescriptive analytics. Learnt Different way of survey's and top companies which can do for you. Regression, Importance of RFM, CLV and probability models and Customer analytics scenario from 1960 to till date. How data will be monetized and Top companies uses advanced analytics for data collection and analyze using NLP's and so much. Best course if you are keen on analytics and marketing.

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.

The course Customer Analytics is really helpful in understanding and exploring how a customer is merely not a customer but a lot of data points connected together. The applications discussed in the course are really an eye-opener and helps you relate to how customer lifetime value and advertisements are targetted. I would strongly recommend this course for anyone who would like to start a career in the field of analytics as this helps in getting the applications right.

This has been a very interesting course and I recommend it to all who are in any field of business as in the end its about your customers or consumers, getting to know how to track customer behavior and how firms use this data to analyze predict and re-target is the today and the future of business and consumer loyalty! Great methodology and curriculum of teachers!

Thank you, every minute spent on this course was worth it!. I will continue my research...

Suzie K.T.

Hello everyone, taking this course at Wharton Online has allowed me to become aware that, in reality, here in Peru our service companies does not been aware of the importance of organizing the information that is available about the habits and preferences of customers, ignoring the value that it will bring to our return on investment, translating into low profits and low profitability. Only with good training and listen to their customers, improvement can be started.

The course provides a good overview of various analytical methods used in Business. The course instructors did a very good job of formulating and delivering high-quality content. I especially liked the references from various academic research on the topic. The study material and powerpoints were very well organized. However, the addition of some assignments on basic analytical problems using excel/R/SPSS, etc. could have added to the effectiveness of the course.

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.