Introducing :  

Certificate in Marketing Analytics

About the course:

Organizations, whether large or small, are often overwhelmed with data of the consumer and their choices. It is this wealth of information that needs to be interpreted. Marketers are increasingly expected to use analytics to evaluate profound insights into customer preferences and trends, which can be further used for future marketing and business decisions.

In this course, we introduce the tools that learners will need to convert raw data into marketing insights so that businesses can understand what drives consumer actions, refine their marketing campaigns and optimize their return on investment.

The course will enable you to make data-driven marketing decisions, define and evaluate brand, measure customer lifetime value, test hypotheses, and interpret outputs.

Program Outline:

  • The program aids the learner with a holistic understanding of marketing as a function and embedding it with analytics to achieve the following outcome:
  • Measuring the impact of marketing efforts on the brand value over a period.
  • Measure customer lifetime value and use that information to evaluate strategic marketing alternatives
  • Design basic experiments so that you can assess your marketing efforts and invest your marketing spent most effectively
  • Learn the marketing metrics and how to apply them to your data
  • Know how to ask the right questions from your data
  • Build a marketing initiative forecast model from the ground level
  • Build a dynamic dashboard to summarize your analysis

Course Coverage:

Module 1:

  • Introduction to Marketing Analytics
  • How to use Marketing Analytics
  • Applications
  • STP Marketing
  • Market Mix
  • Cross Selling and upselling

Module 2:

  • A/B Testing Marketing Analytics
  • Best element to A/b test

Module 3:

  • Customer Analytics
  • Know your customer - what they want
  • Customer Acquisition - Cost and life time value

Module 4:

  • Markvo Model

Module 5:

  • Market basket analysis
  • Association rule in data mining
  • Market Basket Analysis In Python

Module 6:

  • Final business intelligence
  • Dashboard understanding
  • Power BI Desktop understanding
  • Functions in Power BI Desktop

Module 7:

  • Introduction to problem statement
  • Data loading in power BI
  • Overview of the final dashboard
  • Power query editor and data modelling
  • Visualisations- header and card visuals
  • Visualisations- line and stacked column chart
  • Visualisations- line chart
  • Visualisations- matrix
  • Visualisations- decomposition tree
  • Visualisations- slicer and navigation button

 

 

 

 

 

 

   
For queries, feedback or assistance

Contact EY Virtual Academy Support