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.

Customer Analytics

Customer Analytics
This course is part of Business Analytics Specialization



Instructors: Eric Bradlow
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Skills you'll gain
- Business Marketing
- Data-Driven Decision-Making
- Advanced Analytics
- Model Optimization
- Data Collection
- Correlation Analysis
- Business Analytics
- Predictive Modeling
- Customer Data Management
- Customer Analysis
- Data-Driven Marketing
- Customer Insights
- Consumer Behaviour
- Predictive Analytics
- Regression Analysis
- Marketing Analytics
- Analytics
- Descriptive Analytics
- Revenue Management
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Reviewed on Apr 5, 2017
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.
Reviewed on May 31, 2023
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
Reviewed on Mar 23, 2021
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
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