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Course Outline
Module 1
Introduction to Data Science & Applications in Marketing
- Analytics Overview: Type of analytics- Predictive, Prescriptive, Inferential
- Analytics Practice in Marketing
- Use of Big Data and Different Technologies - Introduction
Module 2
Marketing in a Digital World
- Introduction to Digital Marketing
- Online Advertising - Introduction
- Search Engine Optimization (SEO) – Google Case Study
- Social Media Marketing: Tips and Secret – Example of Facebook, Twitter
Module 3
Exploratory Data Analysis & Statistical Modeling
- Data Presentation and Visualization – Understanding the Business data using Histogram, Pie-chart, Bar Chart, Scatter Diagram – Fast inference – Using Python
- Basic Statistical Modeling – Trend, Seasonality, Clustering, Classifications (Only basics, different Algorithm and usage, not any detail) – Ready code in Python
- Market Basket Analysis (MBA) – Case Study using Association rules, Support, Confidence, Lift
Module 4
Marketing Analytics I
- Introduction to Marketing Process – Case Study
- Utilizing Data to Improve 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 Calculation – Case Study of CLV for business decisions
- Measuring Case and Effect through Experiments – Case Study
- Calculating Projected Lift
- Data Science in Online Advertising – Click-rate Conversion, Website Analytics
Module 6
Regression Basics
- What Regression Reveals and basic Statistics (not much details of Mathematics)
- Interpreting Regression Results – With Case Study using Python
- Understanding Log-Log Models – With Case study using Python
- Marketing Mix Models – Case study using Python
Module 7
Classification and Clustering
- Basics of Classification and Clustering – Usage; Mention of Algorithms
- Interpreting the Results – Python Programs with Outputs
- Customer Targeting using Classification and Clustering – Case Study
- Business Strategy Improvement – Example of Email Marketing, Promotions
- Need of Big Data Technologies in Classification and Clustering
Module 8
Time Series Analysis
- Trend and Seasonality – Using Python driven Case Study - Visualizations
- Different Time Series Techniques – AR and MA
- Time Series Models – ARMA, ARIMA, ARIMAX (Usage and Examples with Python) – Case Study
- Time Series Prediction for Marketing Campaign
Module 9
Recommendation Engine
- Personalization and Business Strategy
- Different Types of Personalized Recommendations – Collaborative, Content based
- Different Algorithms for Recommendation Engine – User driven, Item Driven, Hybrid, Matrix Factorization (Only mention and usage of the algorithms without Mathematical details)
- Recommendation Metrics for Incremental Revenue – Detailed Case Study
Module 10
Maximizing Sales using Data Science
- Basics of Optimization Technique and its Uses
- Inventory Optimization – Case Study
- Increasing ROI using Data Science
- Lean Analytics – Startup Accelerator
Module 11
Data Science in Pricing & Promotion I
- Pricing – The Science of Profitable Growth
- Demand Forecasting Techniques - Model and estimate the structure of price-response demand curves
- Pricing Decision – How to Optimize Pricing Decision – 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 - How to manage perishable resources with multiple market segments
- Product Bundling – Fast and Slow Moving Products – Case Study with Python
- Pricing of Perishable Goods and Services - Airline & Hotel Pricing – Mention of Stochastic Models
- Promotion Metrics – Traditional and Social
Requirements
There are no specific requirements needed to attend this course.
21 Hours
Delivery Options
Private Group Training
Our identity is rooted in delivering exactly what our clients need.
- Pre-course call with your trainer
- Customisation of the learning experience to achieve your goals -
- Bespoke outlines
- Practical hands-on exercises containing data / scenarios recognisable to the learners
- Training scheduled on a date of your choice
- Delivered online, onsite/classroom or hybrid by experts sharing real world experience
Private Group Prices RRP from €6840 online delivery, based on a group of 2 delegates, €2160 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.
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Public Training
Please see our public courses
Testimonials (4)
Understanding big data beter
Shaune Dennis - Vodacom
Course - Big Data Business Intelligence for Telecom and Communication Service Providers
Subject presentation knowledge timing
Aly Saleh - FAB banak Egypt
Course - Introduction to Data Science and AI (using Python)
It is great to have the course custom made to the key areas that I have highlighted in the pre-course questionnaire. This really helps to address the questions that I have with the subject matter and to align with my learning goals.
Winnie Chan - Statistics Canada
Course - Jupyter for Data Science Teams
The example and training material were sufficient and made it easy to understand what you are doing.
