Data Analytics for Marketing Program

Module 1: Foundations of Marketing Data Analytics

• Importance of data-driven decision-making in marketing

• Key marketing metrics: impressions, CTR, CPC, CPA, CLV, ROI

• Building data literacy and understanding data structures

• AI integration:

  • Use ChatGPT to outline KPIs and draft measurement frameworks

  • Generate initial metric explanations for client or stakeholder decks

Module 2: Data Collection and Preparation

• Identifying and integrating data sources (web analytics, CRM, social, ads, email)

• Data cleaning fundamentals: deduplication, missing data handling, formatting

• Data privacy and compliance basics

• AI integration:

  • Use AI tools to automate initial data summaries and highlight inconsistencies

  • Generate cleanup checklists and data quality reports using AI

Module 3: Excel for Marketing Analytics

• Key formulas and functions for marketing analysis (SUMIF, COUNTIF, VLOOKUP, INDEX/MATCH)

• Pivot tables for segmentation, performance trends, and channel analysis

• Building basic dashboards and charts in Excel

• AI integration:

  • Use ChatGPT to generate insights from pivot tables and suggest optimizations

  • Automate formula explanations and provide quick data summaries

Module 4: SQL for Marketing Analysts

• SQL fundamentals: SELECT, WHERE, GROUP BY, ORDER BY

• Combining datasets using JOINs

• Segmenting audiences and analyzing campaign performance

• Calculating key metrics (ROI, CAC, churn rates)

• AI integration:

  • Use AI to generate, debug, and optimize SQL queries

  • Summarize SQL outputs into plain-language marketing insights for presentations

Module 5: Marketing Performance Analysis

• Campaign performance tracking and attribution models

• Multi-channel data analysis (social, paid ads, email, web)

• Funnel analysis and customer journey mapping

• AI integration:

  • Use AI to generate automated performance summaries

  • Create AI-driven forecasts and suggest actionable improvements

Module 6: Data Visualization and Dashboarding (Looker Studio & Power BI)

• Principles of effective data storytelling

• Creating interactive dashboards to track key KPIs

• Connecting multiple data sources and integrating marketing platforms

• AI integration:

  • Use AI to draft narrative summaries and annotate dashboards

  • Automate identification of anomalies or trend changes in visualizations

Module 7: Advanced Marketing Analytics Techniques

• Audience segmentation and cohort analysis

• Customer lifetime value (CLV) and retention metrics

• Attribution modeling (first touch, last touch, multi-touch)

• AI integration:

  • Use AI to identify and describe key audience segments

  • Apply predictive churn and upsell models to guide strategy

Module 8: Predictive and Prescriptive Analytics

• Forecasting performance based on historical data

• Scenario analysis and budget optimization

• AI-powered recommendation systems

• AI integration:

  • Simulate budget and channel scenarios using AI-driven models

  • Generate prescriptive strategies (next best action, cross-sell suggestions)

Module 9: AI and Automation in Marketing Analytics

• Overview of AI-powered analytics tools (ChatGPT, BigQuery ML, GA4 predictive features)

• Automating reporting and marketing dashboards

• Real-time monitoring and automated alerting systems

• AI integration:

  • Use AI to auto-generate weekly or monthly performance reports

  • Build AI agents for real-time campaign monitoring and optimization suggestions

Module 10: Final Capstone Project & Portfolio Development

• Complete end-to-end analysis of a chosen or simulated marketing campaign

• Document data collection, cleaning, analysis, visualization, and final insights

• Prepare an executive summary and an actionable strategy plan

• Develop a professional presentation and analytics portfolio piece

• AI integration throughout:

  • Use AI to co-draft reports, generate presentation content, and refine visual storylines

  • Create a polished portfolio-ready case study with AI-assisted editing

Key Tools Covered

• Excel (advanced functions and dashboards)

• SQL (PostgreSQL/MySQL or cloud variants)

• Looker Studio

• Power BI

• Google Analytics 4

• ChatGPT and advanced AI copilots for data (e.g., GPT-4 Advanced Data Analysis, Claude)

• Automation tools (Zapier, Make)

Key Outcomes

• Master end-to-end marketing analytics workflows and tools

• Confidently interpret and present data insights to stakeholders

• Automate reporting and leverage AI for data-driven campaign strategy

• Build a professional portfolio-ready project to showcase analytical expertise