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Course Outline
Module 1
Introduction to Data Science and its Applications in Marketing
- Analytics Overview: Types of analytics - Predictive, Prescriptive, and Inferential
- Applying Analytics in Marketing
- Introduction to Big Data and Various Technologies
Module 2
Marketing in the Digital Era
- Introduction to Digital Marketing
- Overview of Online Advertising
- Search Engine Optimization (SEO) - Google Case Study
- Social Media Marketing: Tips and Strategies - Examples from Facebook and Twitter
Module 3
Exploratory Data Analysis and Statistical Modeling
- Data Presentation and Visualization - Understanding business data through histograms, pie charts, bar charts, and scatter diagrams - Rapid inference - Using Python
- Basic Statistical Modeling - Trends, seasonality, clustering, and classifications (covering only basics, different algorithms, and their usage, without detailed explanations) - Python code examples included
- Market Basket Analysis (MBA) - Case Study using association rules, support, confidence, and lift
Module 4
Marketing Analytics I
- Introduction to the Marketing Process - Case Study
- Leveraging Data to Enhance Marketing Strategy
- Measuring Brand Assets, Snapple, and Brand Value - Brand Positioning
- Text Mining for Marketing - Basics of text mining - Case study for social media marketing
Module 5
Marketing Analytics II
- Customer Lifetime Value (CLV) with Calculations - Case study on CLV for business decisions
- Measuring Cause and Effect through Experiments - Case Study
- Calculating Projected Lift
- Data Science in Online Advertising - Click-through rate conversion and website analytics
Module 6
Regression Basics
- What Regression Reveals and Basic Statistics (avoiding extensive mathematical details)
- Interpreting Regression Results - With a Case Study using Python
- Understanding Log-Log Models - With a Case Study using Python
- Marketing Mix Models - Case Study using Python
Module 7
Classification and Clustering
- Fundamentals of Classification and Clustering - Usage and mention of algorithms
- Interpreting Results - Python programs with outputs
- Customer Targeting using Classification and Clustering - Case Study
- Improving Business Strategy - Examples of email marketing and promotions
- The Need for Big Data Technologies in Classification and Clustering
Module 8
Time Series Analysis
- Trend and Seasonality - Using Python-driven Case Studies and visualizations
- Various Time Series Techniques - AR and MA
- Time Series Models - ARMA, ARIMA, ARIMAX (Usage and examples with Python) - Case Study
- Time Series Prediction for Marketing Campaigns
Module 9
Recommendation Engines
- Personalization and Business Strategy
- Types of Personalized Recommendations - Collaborative and Content-based
- Algorithms for Recommendation Engines - User-driven, Item-driven, Hybrid, Matrix Factorization (mentioning algorithms and their usage without mathematical details)
- Recommendation Metrics for Incremental Revenue - Detailed Case Study
Module 10
Maximizing Sales with Data Science
- Fundamentals of Optimization Techniques and Their Uses
- Inventory Optimization - Case Study
- Increasing ROI through Data Science
- Lean Analytics - Startup Accelerator
Module 11
Data Science in Pricing and Promotion I
- Pricing - The Science of Profitable Growth
- Demand Forecasting Techniques - Modeling and estimating the structure of price-response demand curves
- Pricing Decisions - Optimizing Pricing Decisions - Case Study Using Python
- Promotion Analytics - Baseline Calculation and Trade Promotion Model
- Using Promotion for Better Strategy - Sales Model Specification - Multiplicative Model
Module 12
Data Science in Pricing and Promotion II
- Revenue Management - Managing perishable resources across multiple market segments
- Product Bundling - Fast and Slow Moving Products - Case Study with Python
- Pricing of Perishable Goods and Services - Airline and Hotel Pricing - Mention of Stochastic Models
- Promotion Metrics - Traditional and Social
Requirements
There are no specific prerequisites for attending this course.
21 Hours
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 3900 € + VAT*
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Testimonials (1)
Hands-on exercises related to content really helps to understand more about each topic. Also, style of start class with lecture and continue with hands-on exercise is good and helpful to relate with the lecture that presented earlier.
