Course Purpose

The Purpose of Mkt 404: Data-Driven Marketing Is to Equip Students with The Knowledge and Skills Necessary to Leverage Data Analytics in Marketing Decision-Making. This Course Focuses on Understanding Data Sources, Statistical Tools, And Marketing Insights Derived from Data-Driven Approaches.

Learning Outcomes

At the end of this module, you will be able to:

Analyze customer data and marketing information to identify patterns and insights.

Design data-driven marketing strategies and campaigns based on analytical insights.

Welcome

Welcome to Data-Driven Marketing.

Learning Approach

Introduction to Data-Driven Marketing: Definition of Concepts and Importance of data-driven Marketing; Overview of Data Analytics in Marketing; Evolution of Data in Marketing; Role of Data in Modern Marketing Strategies. Data Collection Methods in Marketing: Primary and Secondary Data Sources; Online and Offline Data Collection Techniques; Surveys, Experiments, and Observational Methods; Data Privacy and Ethical Considerations. Data Management and Cleaning in Marketing: Exploratory Data Analysis (EDA);- Data Cleaning and Preparation, Data Storage and Management Solutions, Handling Missing Data and Outliers; Descriptive Analytics for Marketing: Summarizing Marketing Data, Data Visualization Techniques, Creating Dashboards and Reports: Consumer Behaviour Analysis: Understanding Consumer Needs and Preferences; customer analysis:-Segmentation, Targeting, and Positioning (STP); Analysis; Data Analysis Techniques for marketing;-Descriptive and Inferential Statistics; Predictive Analytics and modelling in Consumer Behaviour; Applications in Predictive Marketing; Future Trends in Data-Driven Marketing. Market Basket Analysis: Association Rule Mining; Cross-Selling and Up-Selling Strategies; Applications in Retail Marketing. Marketing Mix Modelling: Analysing the 4Ps (Product, Price, Place, Promotion); Attribution Modelling; Budget Allocation and Optimization. Marketing Metrics and KPIs. Key Performance Indicators (KPIs) in Marketing; Customer Lifetime Value (CLV); Return on Marketing Investment (ROMI) Digital Marketing Analytics: Web Analytics and SEO; Social Media Analytics (Measuring Social Media Engagement); Email Marketing Metrics; Sentiment Analysis; Pay-Per-Click (PPC) Analytics; Conversion Rate Optimization. Customer Relationship Management (CRM): CRM Systems and Data Integration; Analysing Customer Data for Insights; Personalization, Targeting and Customer Retention Strategies; Measuring CRM Performance. Ethical Considerations in Data-Driven Marketing: Privacy and Data Security Issues; Ethical Use of Consumer Data; Regulatory Compliance (e.g., GDPR); Developing and Presenting Data-Driven Marketing Strategies; Real-World issues of Data-Driven Marketing; Case Study Analysis.