By the end of this course, learners will be able to analyze marketing performance using data, apply key marketing metrics, evaluate customer behavior, and build data-driven strategies using R and Microsoft Excel. Learners will gain practical skills in interpreting marketing data, measuring campaign effectiveness, assessing customer satisfaction, and predicting customer churn across real-world business scenarios.

Analyze Marketing Performance Using R and Excel

Analyze Marketing Performance Using R and Excel
This course is part of Apply R for Business Analytics Projects Specialization

Instructor: EDUCBA
Access provided by Masterflex LLC, Part of Avantor
Recommended experience
What you'll learn
Analyze marketing performance using key metrics and real-world datasets.
Apply R and Excel to evaluate customer behavior, satisfaction, and churn.
Build data-driven marketing strategies using segmentation and predictive analytics.
Skills you'll gain
- Sales Management
- Customer Analysis
- R Programming
- Marketing Analytics
- Customer Service
- Loyalty Programs
- Advanced Analytics
- Predictive Analytics
- Customer Retention
- Case Studies
- Data-Driven Decision-Making
- Performance Metric
- Marketing Effectiveness
- Market Analysis
- Customer Insights
- Business Metrics
- Skills section collapsed. Showing 10 of 16 skills.
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12 assignments
February 2026
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There are 3 modules in this course
This module introduces learners to the fundamentals of marketing and marketing analytics, emphasizing the role of data, metrics, and analytical tools such as R and Microsoft Excel in evaluating marketing performance, planning strategies, and improving customer service outcomes.
What's included
7 videos4 assignments
This module focuses on applying marketing metrics and analytics through real-world case studies, sales channel evaluation, customer loyalty measurement, and persuasion analysis to derive actionable insights that improve customer experience and marketing effectiveness.
What's included
7 videos4 assignments
This module explores advanced marketing analytics techniques such as conjoint analysis, market segmentation, churn prediction, product-service bundling, and algorithmic modeling, with applications across multiple industries including airlines and telecommunications.
What's included
8 videos4 assignments
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