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
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Skills you'll gain
- Predictive Modeling
- Data-Driven Marketing
- Predictive Analytics
- Customer Analysis
- Business Marketing
- Marketing Analytics
- Analytics
- Descriptive Analytics
- Business Analytics
- Correlation Analysis
- Customer Data Management
- Consumer Behaviour
- Regression Analysis
- Advanced Analytics
- Data Collection
- Model Optimization
- Data-Driven Decision-Making
- Customer Insights
- 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 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




