ND
Jan 30, 2019
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!
MA
Aug 4, 2020
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.
By Ivan K S
•Dec 5, 2022
Awesome real time study cases related to high technology applications!
By Rami M
•Jul 10, 2022
Great information gained and very good explanation
By Matias C M
•Jul 7, 2022
Sirve para asentar las bases y como introducción.
By Vedika G
•Jun 21, 2022
Course is super informational.
By Amanda E
•Jul 6, 2022
I really enjoyed this course.
By asyiffa a
•Jun 15, 2022
very well course content
By Tony G
•Jun 25, 2022
This course was great!
By bhayangkara K
•Dec 6, 2022
Excellent Course
By Akshay K
•Oct 7, 2018
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.
By Jackson L
•May 14, 2022
A good high level introduction to customer analytics
By Sanjay D
•Dec 27, 2021
Good High Level Introductions to several important concepts. I wish the course included more practice examples and models for true hands-on-learning. If you add more practice exercises, and share for instance details on how to include churn in the CLV example, this would make the course more appealing. Also, there should be a way for students to ask weekly questions from instructors or teaching assistants. The forums are pretty much unmoderated. With that said, I learned a number of important marketing and analytics concepts, and am looking forward to applying them in real work.
By Pinks S
•Dec 23, 2021
At this point, this course feels a little out of date (6+ years old). Given the emphasis on "cutting edge approaches", it's especially noticeable. It'd be great to see Coursera update the content. Would also like to see richer projects built into the content.
By Snehitha P
•Jul 11, 2021
My sincere thanks to all the instructors who gave an informative rundown on customer analytics. Myself Pamidi Snehitha - 24 years old, i have done my graduation in National Institute of Technology, India in Electrical and Electronics Engineering. I have got a great interest in how business strategies work and optimization of profit. My father is a retired business man to whom i have looked up since my childhood on how he manages a small business , how he maintains good relationship with customers, how he takes feedback from customers constructively. Since then i have had a deep passion on marketing and business development. With that zeal i have enrolled to this Course through financial aid and i am more than delightful after completing this course as my outlook towards Customer analytics is more broadened than ever. Thanks to Coursera . I thoroughly enjoyed the applications part of this course where many companies have diverse goals and analytical strategies to acquire customer interests where they are both benefiting customers as well as themselves.
By Mirjana 1
•Jan 9, 2023
A truly interesting course that explains in a very interactive way the concepts of data analysis and targeting it to one of the most prominent categories on the market. It will certainly serve to gain better insights into the functioning of the market and its further shaping.
The concept of consumer can be used in different ways
approaches and therefore the meaning and use of this term can often vary. When economists and marketing experts talk about consumers, they are mostly talking about a person who has his own individuality, because each individual is a distinctive consumer on the market. In today's era, an individual approach to the consumer is increasingly applied, because in free markets, consumers dictate which and what kind of products they want. Consumers have resources, that is, money that they will spend on the product that suits them best according to some criteria, which are most often price and quality. All thanks to the teachers who brought this to us in such an effective way.
By ARVIND K S
•May 8, 2018
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.
By John P
•Feb 7, 2016
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
By Sudeep B
•Nov 20, 2020
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.
By Tom S
•Feb 2, 2018
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
By Mustafa A A
•Sep 3, 2019
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.
By Katherine B
•Jan 24, 2021
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!!!!
By Ihsan M I
•Apr 20, 2021
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.
By Dave M
•Dec 16, 2015
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.
By Jose B
•Jul 18, 2018
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... :)
By Shari O
•Mar 27, 2020
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!
By Muhammad S S
•May 23, 2020
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.