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
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Customer Analytics
This course is part of Business Analytics Specialization



Instructors: Eric Bradlow
310,086 already enrolled
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11,981 reviews
Skills you'll gain
- Descriptive Analytics
- Data-Driven Marketing
- Analytics
- Advanced Analytics
- Customer Analysis
- Customer Insights
- Regression Analysis
- Data-Driven Decision-Making
- Marketing Analytics
- Model Optimization
- Predictive Analytics
- Correlation Analysis
- Consumer Behaviour
- Data Collection
- Business Analytics
- Customer Data Management
- Predictive Modeling
- Revenue Management
- Business Marketing
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Reviewed on Feb 5, 2019
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.
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
Reviewed on Oct 15, 2017
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.






