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. Course Learning Outcomes: After completing the course learners will be able to... Describe the major methods of customer data collection used by companies and understand how this data can inform business decisions Describe the main tools used to predict customer behavior and identify the appropriate uses for each tool Communicate key ideas about customer analytics and how the field informs business decisions Communicate the history of customer analytics and latest best practices at top firms
AA
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.
ZH
enjoyed the lectures especially from Fader and Bradlow, wish the course had more details on model construction and data analysis but i guess they do not fall into the scope of an introductory course
JB
Excellent for learning different types of analytics, the different tools, learning which type of analytics and tool to use in a specific situation. Furthermore how to implement analytics in business
EG
Well, this course is like a front page of Wharton for coursera users. At the end of the course the only thing I wanted was enroll in Wharton College, crazy idea - it very prestigious thus costly.
AG
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.
DM
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.
KV
The undoubted plus is comprehensible for learners content. A big thank you for that!But in my opinion course is also too abstract, it may be better to give more practical examples of data usage.
PK
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.
BM
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).
JL
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!
SJ
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.
JS
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.
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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.
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.
Theoretical
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.
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 !
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.
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.
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.
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.
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.
Entry level discussion on Customer Analytics. Some of the material is a bit dated.
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.
Excellent couse on "Customer Analytics", my first ever. Excellent teaching quality and the video-lectures are with the Wharton stamp. I am excited to complete the "Business Analytics 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 material was good, but quizzes are riddled with issues.
Covered some important foundation topics quickly to properly synch in with examples etc. and the last week of content was outdated from 2015 because so much has changed in last 6 years.
Course Material is too old. Material is already 5-6 years old. Most of the information is becoming obsolete. You need to update the knowledge being delivered as well.
Basic course on customer analytics, was expecting a little more advanced content looking at the course content and structure.