Training

Business and Management

Market Research Analysis Comprehensive Course

Start: Sep 2017       Type: Evening / Weekend Classes       Duration (hr): 180

COURSE DESCRIPTION: 
This unique comprehensive hands-on course provides solid knowledge in Marketing and Data Analysis. Students will acquire fundamental skills necessary to be an effective Market Research Analyst. Students will learn fundamentals of Data Analysis with SPSS, advanced Excel techniques, basics of SQL Databases, Data Visualization with Tableau. Also, students will learn Marketing Fundamentals, Basics of Market Research design, Google Analytics and basics of Marketing Automation using HubSpot. In the end of the course students will polish their knowledge practicing projects. 
 
COURSE CONTENT: 
 
1. Statistics Basics – students will review basic concepts and terminology in Statistics.
 
2. Data Analysis with SPSS – Statistical Package for the Social Sciences (SPSS) is commonly used software for statistical analysis. SPSS is good for non-programmers, because it does not require any initial knowledge of programming. Students will learn how to read, manage and edit data and implement basic inferential statistics in SPSS. Students will learn the following topics: variables, preliminary analyses (frequencies, means, descriptives, crosstabs), normality, reliability, graphs, manipulating data, Normality, One-Sample Test (T tests, Chi Square test), ANOVA etc. 
 
3. Data Visualization with Tableau – the module includes: using the Tableau interface/paradigm to create data visualizations, creating calculations, building Dashboards, advanced chart types and visualization, complex calculations to manipulate data, use statistical techniques to analyze data, implement advanced geographic mapping techniques and visualizations of non-geographic data, prep data for analysis, combine data sources using data blending. 
 
4. Advanced Excel Techniques – in this module students will learn Excel advanced techniques, including Math Functions, Logical Functions, Statistical Functions, Lookup, Sort/Filter Data, Pivot Tables and Pivot Charts, Data Analysis Tools etc.
  
5. Introduction to SQL Databases – this module provides students with the understanding of database concepts and the essentials of relational database with the SQL language.The module includses: data types, table structure, essential SQL commands, retrieving data, queries, group functions, data manipulation, control transactions etc. 
 
6. Marketing Fundamentals – this module teaches basic concepts of marketing including customer behavior, segmentation and targeting, 4Ps/7Ps, Product Life Cycle (PLC), brands, pricing, promotion and distribution, SWOT marketing effectiveness. For better understanding students will analyze case studies.
 
7. Marketing Research Design Basics – this module provides essentials of Marketing Research Design. Students will learn structure of Marketing Research, the planning process, goals, obtaining data - quantitative techniques (customer surveys, analysis of secondary data) and qualitative techniques (focus groups, interviews, ethnography), survey software overview, basic concepts of measurement, designs questionnaires, basics of sampling procedures, reporting.
 
8. Google Analytics – students will learn fundamentals of Web Analytics, including understanding of concepts, analysis and reporting of web data. 
 
9. Marketing Automation Basics – this module provides basic knowledge in Marketing Automation, including understanding concepts and terminology. Students will get an overview of Marketing Automation software using HubSpot. 
 
10. Project - students will polish their knowledge practicing Market Research, Data Analysis and Data Visualization.
 
*180 instructor-led hours
 
Prerequisites:  
Basics of Statistics and Excel. Related education or work experience is a plus.
 
 
  
Note: Marketing Fundamentals and Statistics Basics modules can be waived for students with similar college credits (Statistics, Marketing). For students familiar with SPSS, this module can be replaced with Data Analysis with Python Programming.
 
 

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