Marketing Analytics with R and Tableau Training Course

Course Outline

Module 1: Introduction to Marketing Analytics

• Overview of marketing data sources
• Basics of R for data analytics
• Data acquisition techniques
• Data cleaning and preprocessing
• Practical session: Importing and cleaning marketing data in R

Module 2: Exploratory Data Analysis (EDA) in Marketing

• Understanding EDA concepts
• Descriptive statistics in marketing data
• Identifying patterns and trends
• Anomaly detection in marketing data
• Practical session: Conducting EDA on marketing datasets in R

Module 3: Customer Segmentation and Profiling

• Introduction to customer segmentation
• Techniques for customer profiling
• Cluster analysis
• RFM analysis (Recency, Frequency, Monetary)
• Practical session: Customer segmentation in R

Module 4: Marketing Campaign Analysis

• Analyzing campaign performance
• Attribution modeling
• Marketing mix modeling
• Return on investment (ROI) analysis
• Practical session: Campaign performance analysis using R

Module 5: Data Visualization with Tableau

• Introduction to Tableau
• Connecting R with Tableau
• Creating basic visualizations
• Advanced visualization techniques
• Practical session: Visualizing marketing data in Tableau

Module 6: Predictive Analytics in Marketing

• Basics of predictive analytics
• Introduction to regression models
• Churn prediction
• Customer lifetime value (CLV) prediction
• Practical session: Building predictive models in R

Module 7: Social Media Analytics

• Introduction to social media data
• Sentiment analysis
• Social network analysis
• Measuring engagement and reach
• Practical session: Analyzing social media data using R

Module 8: Web Analytics

• Overview of web analytics
• Analyzing web traffic data
• Conversion rate optimization
• A/B testing
• Practical session: Web analytics using R

Module 9: Sales Data Analysis

• Understanding sales data
• Sales forecasting techniques
• Market basket analysis
• Cross-selling and upselling strategies
• Practical session: Sales data analysis in R

Module 10: Data Integration and Reporting

• Combining multiple data sources
• Data integration techniques
• Creating interactive dashboards in Tableau
• Reporting and presentation skills
• Practical session: Integrating and reporting marketing data

Module 11: Advanced Statistical Analysis

• Introduction to advanced statistical methods
• Hypothesis testing in marketing
• Multivariate analysis
• Time series analysis
• Practical session: Applying advanced statistical methods in R

Module 12: Machine Learning Applications in Marketing

• Basics of machine learning
• Supervised learning techniques
• Unsupervised learning techniques
• Real-world applications in marketing
• Practical session: Building machine learning models in R

Module 13: GIS in Marketing Analytics

• Introduction to Geographic Information Systems (GIS)
• GIS data for marketing
• Mapping and spatial visualization
• GIS-based marketing analysis
• Practical session: Using GIS for marketing analytics

Module 14: Case Studies in Marketing Analytics

• Review of successful case studies
• Lessons learned from real-world projects
• Best practices in marketing analytics
• Developing a project plan
• Practical session: Analyzing case studies and project planning

Module 15: Scenario Analysis and Decision Support

• Introduction to scenario analysis
• Developing marketing scenarios
• Decision support systems
• Implementing scenario analysis in R
• Practical session: Conducting scenario analysis in R

Module 16: Data Ethics and Privacy in Marketing

• Understanding data ethics
• Data privacy regulations
• Ethical considerations in data analysis
• Implementing data privacy measures
• Practical session: Addressing ethical issues in marketing data

Module 17: Advanced Tableau Techniques

• Advanced features in Tableau
• Custom calculations and parameters
• Advanced chart types
• Dashboard interactivity and design
• Practical session: Creating advanced visualizations in Tableau

Module 18: Capstone Project

• Integrating all learned concepts
• Designing a comprehensive project
• Data analysis and visualization
• Presentation of project findings
• Practical session: Capstone project execution and presentation

Trainer Experience

Our trainers are industry experts with extensive experience in marketing analytics, R programming, and Tableau. They have successfully led numerous projects and have a deep understanding of the challenges and opportunities in the field.

Quality Statement

We are committed to providing high-quality training that meets the needs of our participants. Our courses are designed to be practical, interactive, and relevant to current industry trends.

Tailor-Made Courses

We offer tailor-made courses to suit the specific needs of organizations. Contact us to discuss your requirements and how we can customize the training for your team.

Payment Information

Payment should be made a week before the training starts.

Accommodation and Airport Pick-Up

We provide assistance with accommodation and airport pick-up for participants traveling from outside Nairobi. Please contact us for more information.