Marketing challenges through data-driven solutions

Lecturer

Stephen Samaha

About the lecturer

Stephen Samaha is a marketing expert from the USA, specialising in customer relationship management and digital marketing. He currently combines an academic career in the UK where he incorporates his practical data analytics perspective to understand marketing strategy and improving customer relationships through data-driven solutions. His research has been published in top marketing journals and he lectures at the UK’s Warwick Business School on the Executive MBA program.

Course Description

3 day seminar will go through the main marketing topics like segmentation, loyalty, customer acquisition, customer retention, cross-selling, etc. and help to see these through analytical perspective and finding the solutions through the data perspective. As modern marketing involves significant amount of the data, then it is important to use them well, to analyze them and to use them to make smarter marketing decisions. Thus the best place to increase your data analytics perspective for improved marketing perspective.

Course Goals

Identify marketing problems and help to find the solutions using the data.
Apply statistical techniques, such as regression, clustering, and time series analysis based on the program insights.
Extract valuable insights from customer data to inform business decisions.
Create compelling data visualizations to communicate findings clearly.
Use data analytics to address practical business challenges.

After the course participants will be able to:

Gain a solid foundation in key marketing analytics concepts and techniques.
Develop proficiency in using popular data analysis tools and software.
Learn how to leverage data to improve customer acquisition, retention, and satisfaction.
Acquire the ability to extract meaningful insights from data and translate them into actionable recommendations.
Learn how to use data to inform and optimize marketing strategies.

Course will be:

In Person

Prerequisites:

Anyone interested in marketing through data-driven perspective are welcomed.
Professor’s favourite analytics tool is RStudio, so if you have the opportunity – please take the free basic online training to get more value from the training – https://www.datacamp.com/courses/free-introduction-to-r

Teaching methods used:

Active learning
Class discussion
Group work
Lecture
Case study
In-class assignments and solutions

Day 1

Introduction to Regression Analysis
Simple Linear Regression
Dummy Variables Regression
Multiple Regression
Fit Statistics
Hold Out Groups
Predicted Values
In-Class Exercise: Satisfaction Asymmetry

Day 2

Introduction to Logistic Regression
Assessing Model Fit: Classification Tables/ ROC Curves
In-Class Exercise: Customer Acquisition
Introduction to Multinomial Logistic Regression
In-Class Exercise: Next Product to Buy/ Cross-Sell
Introduction to the Discrete-Time Hazard Model
In-Class Exercise: Predicting When a Customer Will Leave

Day 3

Introduction to Customer Segmentation
RFM Segmentation: Recency, Frequency, Monetary Value
In-Class Exercise: Applying RFM for Customer Segmentation
K-Means Cluster Analysis
In-Class Exercise: Applying Cluster Analysis to Customers
Advanced Topics: Customer Segments of Size One

Marketing challenges through data-driven solutions

This course has three parts and is available:

March 12, 13, and 14 |

The exact time will be announced after registration. For more information please contact us at lift@rbs.lv or call us at 20318250

APPLY