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Transform your future with AAIS Learning

Marketing Analytics Courses

Master data-driven marketing with AAIS, from foundational data analysis through predictive analytics, attribution modeling, and AI-powered marketing techniques.

Course curriculum

Four levels, a clear path through

Every learner starts where they are. Move from Beginners through to Expert at your own pace.

Beginners Level
Intermediate Marketing Analytics
Advanced Marketing Analytics
Expert Marketing Analytics
📘

Introduction to Marketing Analytics

  • Understanding the role of data in marketing decision-making
  • Overview of marketing analytics tools and techniques
  • Exploring real-world applications of marketing analytics
📙

Fundamentals of Data Analysis

  • Introduction to data collection and data types
  • Data cleaning and preprocessing techniques
  • Descriptive statistics and data visualization
  • Introduction to statistical analysis for marketing
📗

Introduction to Market Research

  • Understanding the importance of market research in marketing analytics
  • Exploring different types of market research methodologies
  • Conducting surveys and interviews for data collection
  • Analyzing and interpreting market research data
📕

Introduction to Customer Segmentation

  • Segmentation strategies for target marketing
  • Demographic, psychographic, and behavioral segmentation
  • Analyzing customer segments using clustering techniques
  • Creating customer profiles and personas
📘

Predictive Analytics for Marketing

  • Introduction to predictive modeling and forecasting
  • Data mining techniques for marketing analytics
  • Building predictive models using regression and decision trees
  • Evaluating model performance and accuracy
📙

Customer Lifetime Value Analysis

  • Understanding customer lifetime value (CLV) and its significance
  • Calculating CLV using various approaches
  • Analyzing customer profitability and retention strategies
  • Applying CLV insights for marketing decision-making
📗

Marketing Mix Modeling

  • Introduction to marketing mix modeling (MMM)
  • Understanding the impact of marketing variables on sales
  • Analyzing the effectiveness of marketing campaigns
  • Optimizing marketing spend and allocation
📕

Social Media Analytics

  • Introduction to social media analytics for marketing
  • Monitoring and analyzing social media metrics
  • Sentiment analysis and brand perception measurement
  • Creating social media strategies based on analytics insights
📘

Advanced Data Visualization for Marketing

  • Advanced techniques for visualizing marketing data
  • Interactive dashboards and data storytelling
  • Using data visualization tools for effective communication
  • Design principles for impactful visual representations
📙

Customer Relationship Management (CRM) Analytics

  • Introduction to CRM analytics and customer analytics
  • Analyzing customer behavior and preferences
  • Implementing CRM systems for data-driven marketing
  • Personalization and targeting strategies using CRM analytics
📗

Marketing Attribution Modeling

  • Understanding marketing attribution and its challenges
  • Different approaches to attribution modeling
  • Analyzing the impact of marketing channels and touchpoints
  • Optimizing marketing strategies based on attribution insights
📕

Project Management and Client Relations

  • Analyzing e-commerce data for marketing insights
  • Conversion rate optimization and funnel analysis
  • Recommendation systems and personalized marketing
  • Applying A/B testing for website optimization
📘

Advanced Marketing Analytics Techniques

  • Advanced statistical analysis methods for marketing
  • Time series analysis and forecasting in marketing
  • Conjoint analysis and discrete choice modeling
  • Machine learning algorithms for marketing analytics
📙

Marketing Automation and AI

  • Introduction to marketing automation platforms
  • Using AI in marketing campaign optimization
  • Chatbots and virtual assistants for customer engagement
  • Automating personalized marketing strategies
📗

Text and Sentiment Analysis in Marketing

  • Analyzing text data for sentiment and emotion analysis
  • Natural language processing (NLP) techniques for marketing
  • Social media listening and brand reputation management
  • Extracting actionable insights from textual data
📕

Marketing Analytics in a Global Context

  • Understanding the challenges of international marketing analytics
  • Cross-cultural analysis and market entry strategies
  • Multilingual sentiment analysis and language-specific trends
  • Global marketing analytics case studies
📓

Data Ethics and Privacy in Marketing Analytics

  • Ethical considerations in marketing analytics
  • Data privacy regulations and compliance
  • Protecting customer data and ensuring transparency
  • Responsible use of data in marketing decision-making

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