Data Mining Techniques

Course Category:

• Professional Development course

Instructor:

• Anthony Lea, PhD, CMRP

Data mining (D-M) covers a range of concepts, problems and methods for exploratory data analysis and predictive modeling designed to gain insight for informing marketing decisions. D-M methods are used to search (typically large) databases to find relationships amongst variables that provide insight into customer behavior, especially in cases of weak or non-existent theory. The value of D-M can be to increase the efficiency and/or decrease the cost of marketing by increasing customer loyalty, cross-sell, up-sell or by decreasing churn or credit risk.

Exemplary D-M problems and case studies will be integrated into the course materials and used to help to explain different frameworks, methods and techniques. The course starts with a review of alternative concepts of D-M. All D-M approaches and methods have challenges in dealing with data. Stress is given to evaluating data quality, finding and developing indicators and surrogate variables, and "data overlays". The course then turns to deal with missing values in the data -- a common challenge.

The greatest emphasis is given to describing the methods used for D-M and the advantages of each for different applications. We cover both traditional statistical techniques such as correlation analysis, analysis of variance, multiple regression, principal components analysis, and cluster analysis, and then a wide range of new techniques for data mining, some of which escape from the traditional hypothesis testing framework of classical statistics. The 'new' methods include regression trees (CHAID and CART), types of categorical data analysis models, neural networks, genetic algorithms, and artificial intelligence. As part of the course there are exercises in which small groups discuss how they would deal with exemplary DM type projects.  An overview will be provided on software being positioned as DM software.

• 101-Introduction to Marketing Research
• 204-Marketing Research Statistics & Data Analysis
• 401-Advanced Analysis Techniques
• 203-Marketing Research Design: An Applied Course
  

For researchers who have a good understanding of concepts covered in Marketing Research Statistics and Data Analysis.

It will be assumed that participants are familiar with marketing research issues and methods in general and have taken at least a course in introductory statistics so they are familiar with concepts such as data sets, observations, variables, relationships between variables, variance, correlations and statistical explanation/prediction.

Suggested Audience

	Members seeking CMRP designation				Client-Side Researcher		Research Supplier
	Little or no exposure		Less than 2 years experience		2-8 years experience		8+ years experience

Major topics covered in this course include

• Key marketing problems subject to data mining
• Analytical Customer Relationship Management aCRM
• One-to-one marketing; database marketing
• Exploratory analysis of data
• Customer behaviour insights
• Sampling Theory and Practice
• Searching for meaningful/exploitable relationships amongst variables
• Traditional statistical methods for data mining
• Categorical methods for data mining
• Neural network and genetic algorithm based methods
• Other approaches to DM
• Judging the quality of data mining processes and methods
• Testing and validation of models; the role of judgment
• Overview of software for DM
• Knowing when you have found something important
• Implementing research findings in marketing practice
• Marketing campaign management
  

"Real life examples provided by (Anthony Lea)."

"Broadened my knowledge about the topic of data mining."

"Great balance of theory & experience."

NEW: Multi Course Bundle Savings

Multi course bundle savings will apply when more than 1 course is purchased by an individual in the same online transaction in the MRIA Portal:

2 courses = 10% off
3 to 5 courses = 15% off
6 or more courses = 20% off

• Course Length: 1 Day
• Check-in: 8:30 am
• Classes: 9 am - 5 pm
• Lunch will be provided
• For terms and conditions, click here

The venue address will be sent to you as part of your course registration confirmation.

MRIA courses and their administration are subsidized by members' fees. Therefore, members enjoy a reduced cost for courses.