This course introduces marketing data analytics, focusing on the crucial concepts of correlation and causality. Learners will explore statistical concepts and tools to analyze and interpret marketing data, leading to more informed and impactful marketing strategies. The course begins with core statistical concepts, such as standard deviation, variance, and normal distributions, in the context of marketing decisions. It shows how to visualize correlations and causal networks using techniques such as Structural Equation Modeling (SEM) and Path Analysis. The course discussions of analytics ethics, guiding participants to identify and avoid common pitfalls in data interpretation. This course is an invaluable resource for anyone looking to enhance their marketing strategies through trustworthy data-driven insights.

Customer Data Analytics for Marketers
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Customer Data Analytics for Marketers
This course is part of Data Science for Marketing Specialization

Instructor: Tony Cox, Jr.
2,352 already enrolled
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What you'll learn
Key statistical concepts and simple linear regression to improve data-driven marketing decisions.
Skills you'll gain
- Analytics
- Data-Driven Marketing
- Probability & Statistics
- Customer Analysis
- Regression Analysis
- Predictive Analytics
- Data-Driven Decision-Making
- Statistical Analysis
- Statistical Visualization
- Customer Retention
- Marketing Analytics
- Customer Insights
- Analytical Skills
- Descriptive Statistics
- Data Analysis
- Statistical Modeling
- Data Ethics
- Correlation Analysis
- Descriptive Analytics
- Statistical Hypothesis Testing
Details to know

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University of Illinois Urbana-Champaign
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Reviewed on Jul 21, 2024
One of the best courses I have ever taken on Coursera. Looking forward to gaining even more knowledge by completing the other courses in the specialization.







