Data Exploration for Marketing Analytics
Before you model, you explore. This module builds the habits and intuitions that separate analysts who get lucky from those who consistently find insight — using real marketing data and professional tools.
Chapter Section Outline (11 Sections)
Topics and managerial frameworks covered in Data Exploration for Marketing Analytics:
- 1. Why Explore Before You Model
- 2. Understanding Variable Types in Marketing Data
- 3. Distributions: What Your Data Is Actually Doing
- 4. Outliers and Missing Data: The Stuff Nobody Wants to Deal With
- 5. Binning: Turning Continuous Into Categorical
- 6. Exploring Relationships Between Variables
- 7. Cross-Tabulation — Exploring Categorical Relationships
- 8. Putting It All Together: A Full EDA Walkthrough
- 9. Data Exploration in the Age of AI
- 10. Case Application — NovaBikes E-Commerce Transaction Audit
- 11. Your EDA Checklist
Interactive Concept Mini-Widgets Embedded in This Chapter (2)
Students manipulate these interactive visual simulations directly inside the chapter reading before answering gated check-in questions:
Variable Type Sorter
Students sort all 16 marketing variable cards into four buckets (Nominal, Ordinal, Interval, Ratio) by drag-and-drop, or by clicking / pressing Enter on a card and then on a bucket. Check Answers colours each card and prints the hint inline on every wrong o...
Compare Normal vs Skewed Right-Tailed Curves
Students adjust skewness + sample size sliders to see how distribution shape affects mean vs. median.
Paired Browser-Based Analytics Calculators (3)
This chapter connects directly to these full MktPraxis analytical apps (with pre-loaded business case scenarios, CSV upload, and reproducible Python export):
📊 Univariate Analyzer
Explore a single variable's distribution, outliers, and summary stats. Always start here.
Pre-loaded Business Scenarios: Influencer Campaign Performance Analysis · Customer Satisfaction Survey Analysis · E-commerce Transaction Analysis · Email Marketing Campaign Analysis · Customer Lifetime Value Analysis · Social Media Post Analytics · A/B Test Results — Messy Data Challenge! · PetPost Subscriber Health Analysis
🔗 Pearson Correlation
Check if two continuous metrics move together (e.g., ad spend vs. revenue).
Pre-loaded Business Scenarios: Paid Social Spend vs Trial Signups · Awareness vs Consideration – Q3 Brand Tracker · Net Promoter Score vs Loyalty Retention · Full-Funnel KPI Matrix – Finding the Leak · Email Send Volume vs Revenue – and the Third Column
▦ Chi-Square Test
Check if two categorical variables are related (e.g., Device vs. Signup).
Pre-loaded Business Scenarios: Holiday Email Creative Test · Channel vs. Purchase Behavior Test · Landing Page Layout Test · Loyalty Nudge Test (Raw Data) · D&D Class Survival Test