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
Customer Data Analytics for Marketers
This course is part of Data Science for Marketing Specialization
Instructor: Tony Cox, Jr.
Access provided by Interbank
2,091 already enrolled
Gain insight into a topic and learn the fundamentals.
12 reviews
Intermediate level
Recommended experience
2 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Key statistical concepts and simple linear regression to improve data-driven marketing decisions.
Skills you'll gain
- Analytics
- Customer Analysis
- Customer Insights
- Marketing Analytics
- Statistical Modeling
- Statistical Visualization
- Statistical Analysis
- Marketing Effectiveness
- Regression Analysis
- Statistical Hypothesis Testing
- Marketing Strategies
- Data Ethics
- Data-Driven Decision-Making
- Statistical Methods
- Correlation Analysis
- Exploratory Data Analysis
- Data Analysis
- Probability & Statistics
- Descriptive Statistics
Details to know
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Assessments
33 assignments
Taught in English
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This course is part of the Data Science for Marketing Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 4 modules in this course
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MA
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.
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