Marketing Analytics

Program Overview

Through this course, you’ll learn how to source raw data from both secondary and primary data sources, including prospects, consumption patterns, and more. Using marketing analytics, you’ll transform this data into actionable insights and predictions to make better marketing decisions to support the growth objectives of the organization. Discover the relationships between variables, trends, and seasonality using advanced decomposition techniques to develop marketing strategies that maximize customer value and financial sustainability. By the end of the program, you’ll be equipped with the tools and knowledge necessary to take your marketing career to the next level with marketing analytics as part of your competency toolkit. 

Details

Program Objectives:

1. Give clients the knowledge to organize their marketing department or division to be able to gather and process marketing-related data from prospects and clients. 
2. Know how data should be gathered, cleansed, archived, and organized to make it ready for processing for analytics purposes.
3. Revisit and refresh knowledge of Descriptive statistics and statistics. Revisit some fundamental statistics theories such as probability theory and the normalized bell curve.
4. Be able to use good visualization to understand and communicate data.
5. Use Different statistical and mathematical techniques to quantify relevant marketing variables for decision-making.
6. Get introduced to intermediate-level prescriptive analytics techniques and understand how the data inputs and relationships can be the inputs to programs and even Machine Learning/ Artificial Intelligence.

What You Will Learn:

1. Give students ways to organize their marketing department or division to be able to gather and process marketing-related data from prospects and clients systematically. 
2. Know how data should be gathered, cleansed, archived, and organized to make it ready for processing for analytics purposes. 
3. Revisit and refresh knowledge of Descriptive statistics and statistics. Revisit some fundamental statistics theories such as probability theory and the areas of the normalized bell curve. 
4. Be able to use good visualization in understanding the data and communicating data to the student’s target audience. 
5. Use different regression techniques for predictive analytics (simple and multiple regression, linear regression, exponential regression, polynomial regression, and logarithmic regression) in creating relationship models for marketing variables and finding the best fit. 
6. Get introduced to intermediate-level prescriptive analytics techniques and understand how the data inputs and relationships can be the inputs to programs and even Machine Learning/ Artificial Intelligence. 
7. Share attributes of human psychology such as language and mannerisms to garner insights on background and preferences. 

Key Benefits:

1. Use marketing data and insights to introduce or create products and services that can deliver the best value to clients. 
2. Familiarize with an assortment of qualitative and quantitative tools to gather and get insights on customer sentiments and insights. 
3. Help Transform the marketing department from a department that gets ad hoc information to a department that systematically gathers data. 
4. Use quantitative tools to learn customer consumption and product demand behavior to be able to decide where marketing efforts and resources should be spent. 

Who Should Attend:

This course is designed for audiences between the Supervisor level to Middle Management and lower High-level management. 

• Marketing practitioners such as marketing managers, brand managers, advertisers and other marketing professionals who want to upgrade their skillsets in marketing analytics. 
• Professionals who are considering entering the marketing field 
• Company Management who want to be able to find ways how they can improve the marketing department. 
• Students and Academe who want to see applications of quantitative approaches tailor-fitted for marketing practice.