Data about our browsing and buying patterns are everywhere. From credit card transactions and online shopping carts, to customer loyalty programs and user-generated ratings/reviews, there is a staggering amount of data that can be used to describe our past buying behaviors, predict future ones, and prescribe new ways to influence future purchasing decisions. In this course, four of Wharton’s top marketing professors will provide an overview of key areas of customer analytics: descriptive analytics, predictive analytics, prescriptive analytics, and their application to real-world business practices including Amazon, Google, and Starbucks to name a few. This course provides an overview of the field of analytics so that you can make informed business decisions. It is an introduction to the theory of customer analytics, and is not intended to prepare learners to perform customer analytics.
About this Course
학습자 경력 결과
공유 가능한 수료증
완료하는 데 약 12시간 필요
학습자 경력 결과
공유 가능한 수료증
완료하는 데 약 12시간 필요
Eric BradlowProfessor of Marketing, Statistics, and Education, Chairperson, Wharton Marketing Department, Vice Dean and Director, Wharton Doctoral Program, Co-Director, Wharton Customer Analytics Initiative
Peter FaderProfessor of Marketing and Co-Director of the Wharton Customer Analytics Initiative
The University of Pennsylvania (commonly referred to as Penn) is a private university, located in Philadelphia, Pennsylvania, United States. A member of the Ivy League, Penn is the fourth-oldest institution of higher education in the United States, and considers itself to be the first university in the United States with both undergraduate and graduate studies.
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고객 분석의 최상위 리뷰
The material was interesting, current and communicated clearly. However, i did feel that some of the quiz questions were poorly phrased which created confusion. Would certainly recommend it to others.
I enjoyed the content. Some of the professors were more concise than others. I would prefer more slides that watching professors talk. I am looking forward to the other classes in this specialization.
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!
The course is very good. I have learned a lot from the course. A lot of interesting topics and help me to under the marketing. I will for sure continue learning more courses from this specialization.
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.
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.
Great introduction to concepts. I value these courses because they hold the potential to optimize education and provide skills that will be necessary and essential for today's and tomorrow's markets.
Good intro to the course. Would like it if the course had more use cases or technical skills taught, just so we can use the knowledge learned in real life situations. But the overall course is great!
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.
The undoubted plus is comprehensible for learners content. A big thank you for that!\n\nBut in my opinion course is also too abstract, it may be better to give more practical examples of data usage.
This was my first course on coursera and i think it was definitely worth spending time. This was my first step towards analytics and this course has helped me gain insights about customer analytics.
The course is very useful and opened a whole new set of interests for me. I'll keep learning and digging into customer analytics for sure, I can see it's a very valuable set of skills and knowledge.
This course is designed with highly skilled faculties. The way they explains carry a lot of meaning in small format. One may easily understand without having any prior knowledge of this whole area.
Provides very good overview and understanding of cutomer analytics, how to collect data, measure, predict outcomes and what techniques to use in different scenarios. Highly recommend for beginners.
Immensely informative and sets up the context for Customer Analytics. Its a privilege to get industry experience by Peter Fader and Eric Bradlow (especially on Marketing Analytics and BTYD model).
A fantastic course to start wading into making sense of data and people. Would love to see some more exposure to the processes and approaches (CLV) at a deeper level, but outstanding non the less.
Fantastic course. The instructors were great, the real world examples were very interesting, and the course materials were relevant to the daily tasks I face as a Data & Customer Insights Analyst.
The first lecturer sounds boring, but the quality of other lectures is increasing. I enjoy the last lecture most where I can see the real value of analytics in business. Thanks for a nice course.
I have two comments\n\nThe prescriptive analytics content is very weak. Also the quiz for predictive analytics contains questions not covered in the content (eg. diagnostic on a model's validity)
Interesting look at how analytics can be used at the individual customer level. Not intended to help participants do the actual data work, but good for providing awareness about what is possible.
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